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Quantification of Competitive Game Demands of NCAA Division I College Football Players Using Global Positioning Systems
Abstract
The aim of the present study was to examine the competitive physiological movement demands of NCAA Division I college football players using portable global positioning system (GPS) technology during games, and to examine positional groups within offensive and defensive teams, to determine if a player's physiological requirements during games are influenced by playing position. Thirty-three National Collegiate Athletic Association (NCAA) Division I Football Bowl Subdivision football players were monitored using GPS receivers with integrated accelerometers (GPSports, Canberra, Australia) during 12 regular season games throughout the 2014 season. Individual datasets (n = 295) from players were divided into offensive and defensive teams, and subsequent position groups. Movement profile characteristics including total, low-, moderate-, high-intensity and sprint running distances (m), sprint counts, and acceleration and deceleration efforts, were assessed during games. A one-way ANOVA and post-hoc Bonferroni statistical analysis were used to determine differences in movement profiles between each position group within offensive and defensive teams. For both offensive and defensive teams, significant (p < 0.05) differences exist between positional groups for game physical performance requirements. The results of the present study identified that wide receivers (WR) and defensive backs (DB) completed significantly (p < 0.05) greater total distance, high-intensity running, sprint distance, and high-intensity acceleration and deceleration efforts compared to their respective offensive and defensive positional groups. Data from the present study provide novel quantification of position specific physical demands of college football games and support the use of position-specific training in the preparation of NCAA Division I college football players for competition.
... American football is a field-based collision sport characterized by high intensity multidirectional movements and repeated high-velocity sprints separated by periods of rest [1,2]. The combination of high-intensity accelerations and decelerations, high-velocity running, and collisions from blocking and tackling, collectively, may place American football players at an increased risk for injury compared to other team sports [3]. In the National Football League (NFL), 60% of all injuries occur in the lower extremity, resulting in a considerable number of player-days missed [4]. ...
... A deeper understanding of the position-specific game demands may assist practitioners in developing training programs to prepare athletes for competition and potentially mitigate injury risk [11]. Furthermore, understanding competitive demands may provide increased insight to position-specific training programs to better optimize on-field performance [3,11]. ...
... Much of the reported data associated with game and training demands in American football have been conducted at the high school [19] and collegiate [3,[20][21][22] levels. These studies have generally found that players on the offensive and defensive lines accumulated less total distance and high velocity distance compared to non-linemen [3,19,20]. ...
Understanding the in-game demands placed on athletes may allow practitioners to design improved training protocols to prepare athletes for competitive demands. This study aimed to quantify the competitive movement demands of professional American football athletes and to determine any inter-positional differences that may exist. Player tracking data were collected from 2018 to 2020 regular season games of the National Football League. Distance, maximum velocity, high-velocity efforts and distance, and acceleration and deceleration efforts and distance were used to evaluate competitive movement demands. To determine position-specific demands, each player was classified by their designated position, and velocity data from competitive games were used to develop position-specific velocity thresholds. One-way ANOVA and post hoc Bonferroni statistical analysis were used to determine inter-positional difference. Significant (p < 0.05) positional differences were found for all load metrics with respect to competitive game demands. Generally, wide receivers and defensive backs had faster maximum velocities, higher distances, and more acceleration and deceleration efforts and distance than other positions. Linebackers accumulated the most high-velocity efforts and distance. Lineman had the lowest values for all assessed metrics. These findings may assist the performance staff in developing improved training and return-to-play protocols with the aim of improving player performance and mitigating injury.
... Non-GPS systems (e.g., video based tracking) were also excluded due to previously reported differences in locomotor distance and speed outcomes when simultaneously comparing data obtained across these systems, particularly in short high-speed movement actions (Buchheit, Allen, et al., 2014). An arbitrary threshold of > 2.5 m·s -2 was used to classify high-intensity acceleration and deceleration occurrences, as previous studies have utilized values at or closely around this threshold (Wehbe et al., 2014;Wellman et al., 2015). Data extracted were organised according to the sample studied (sport, position, age, body mass, stature), competition details (type, year, number of matches and data files) and classification of 'eliteness' (semi-elite, competitive elite, successful elite, worldclass elite). ...
... The characteristics of the nineteen included studies are summarised in table 2.3. One study investigated American Football (Wellman et al., 2015), two Australian Football Johnston et al., 2015c), one hockey (Morencos et al., 2018), four rugby league (Cummins et al., 2016;Dempsey et al., 2018;Kempton et al., 2015;Oxendale et al., 2016), three rugby sevens (Furlan et al., 2015;Higham et al., 2012;Suarez-Arrones et al., 2016), two rugby union (Cunningham, Shearer, Drawer, Pollard, et al., 2016;M. R. Jones et al., 2015), and six soccer (Akenhead et al., 2013;de Hoyo, Cohen, et al., 2016;Russell et al., 2015;Russell, Sparkes, Northeast, Cook, Love, et al., 2016;Tierney et al., 2016;Wehbe et al., 2014). ...
... Sixty-three percent (n = 12) of studies used GPS with a raw 10Hz sampling frequency, with the remaining 32% (n = 7) of studies using 5Hz. Four of the studies (Cummins et al., 2016;Furlan et al., 2015;Suarez-Arrones et al., 2016;Wellman et al., 2015) that captured data at 5Hz incorporated an interpolation algorithm that resulted in a 15Hz output. The MED used to delineate the minimal time required to be above the specified high intensity acceleration or deceleration threshold for an effort to be recorded was reported in four studies Kempton et al., 2015;Russell, Sparkes, Northeast, Cook, Love, et al., 2016;Suarez-Arrones et al., 2016) and ranged between 0.2 and 1 s. ...
Horizontal accelerations and decelerations are crucial components underpinning the many fast changes of speed and direction that are performed in team sports competitive match play. Extensive research has been conducted into the assessment of horizontal acceleration and the underpinning neuromuscular performance determinants, leading to evidence-informed guidelines on how to best develop specific components of a team sport players horizontal acceleration capabilities. Unlike horizontal acceleration, little scientific research has been conducted into how to assess horizontal deceleration, meaning the neuromuscular performance determinants underpinning horizontal deceleration are largely based on anecdotal opinion or qualitative observations. Therefore, the overall purpose of this thesis was to investigate the neuromuscular determinants of maximal horizontal deceleration ability in team sport players. Furthermore, since there are no recognised procedures on how to assess maximal horizontal deceleration ability, an important and novel aim of this thesis was to develop a test capable of obtaining reliable and sensitive data on a team sport player’s maximal horizontal deceleration ability. In part one of this thesis (chapter three) a systematic review and meta-analysis identified that high-intensity (< -2.5 m.s-2) decelerations were more frequently performed than equivalently intense accelerations (> 2.5 m.s-2) in most elite team sports competitive match play, signifying the importance of developing maximal horizontal deceleration ability in team sport players. In chapter four, a new test of maximal horizontal deceleration ability (named the acceleration-deceleration ability test – ADA test), measured using radar technology, identified a number of kinematic and kinetic variables that had good intra- and inter-day reliability and were sensitive to detecting small-to-moderate changes in maximal horizontal deceleration ability. The ADA test was used in chapters five to seven to examine associations with isokinetic eccentric and concentric knee strength capacities and countermovement and drop jump kinetic and kinematic variables, respectively. Using the neuromuscular and biomechanical determinants identified to be important for horizontal deceleration ability within this thesis, in addition to other contemporary research findings, the final part of this thesis developed an evidence-based framework that could be used by practitioners to help inform decisions on training solutions for improving horizontal deceleration ability – named the dynamic braking performance framework.
... American football is an intermittent, contact sport characterised by physical demands that include HSR, accelerations, decelerations, and changes of direction [100]. The game is play-by-play in nature across four 15-min quarters, with multiple stoppages and commercial breaks, extending the game length, in actual time, to upwards of three hours (Fig. 2). ...
... Differences in running, assessed via HSR, and non-running, assessed via total inertial movement analysis (IMA) from the IMU, characteristics were notable across position groups during a professional training camp [102]. Similar differences have been illustrated in training and competition characteristics at the collegiate level [100,103,104]. While the use of IMU data may help to capture sport-specific actions (e.g., throwing, contact, and collisions) and be developed into position-specific metrics [105], this technology may still be unable to fully quantify some characteristics that rely less on movement tracking, such as the high isometric demands of grappling and blocking. ...
... Ward and colleagues (2017) used a HSR threshold above 70% of the maximum speed for the respective position group, derived from training sessions within the previous year. Absolute speed zones for the entire team, which may over-and under-estimate demands for faster and slower athletes respectively [100], have also been utilised. However, it is also important to note that research in other sports (soccer) found the use of relative speed thresholds did not better quantify the dose-response and, in fact, the application of a player's peak speed to establish speed zones may result in erroneous interpretations [107]. ...
Seeking to obtain a competitive advantage and manage the risk of injury, team sport organisations are investing in tracking systems that can quantify training and competition characteristics. It is expected that such information can support objective decision-making for the prescription and manipulation of training load. This narrative review aims to summarise, and critically evaluate, different tracking systems and their use within team sports. The selection of systems should be dependent upon the context of the sport and needs careful consideration by practitioners. The selection of metrics requires a critical process to be able to describe, plan, monitor and evaluate training and competition characteristics of each sport. An emerging consideration for tracking systems data is the selection of suitable time analysis, such as temporal durations, peak demands or time series segmentation, whose best use depends on the temporal characteristics of the sport. Finally, examples of characteristics and the application of tracking data across seven popular team sports are presented. Practitioners working in specific team sports are advised to follow a critical thinking process, with a healthy dose of scepticism and awareness of appropriate theoretical frameworks, where possible, when creating new or selecting an existing metric to profile team sport athletes.
... In collision-based team sports such as rugby union (21,45,57), rugby league (22,28,43), and Australian Football (8,9,19,67), IT has become an integral part of sport performance analysis, more specifically in terms of both match and training analysis (1). In contrast, only a few studies are available in the literature documenting the use of IT in American collegiate football (23,52,53,(60)(61)(62)(63)65). ...
... These differences were consistent within positional drills, team drills and total practice alike. In the first of a series of studies, Wellman et al. (60) examined the competitive physiological movement demands of NCAA Division I college football players during regular season games. Total, low-intensity, moderateintensity, high-intensity, and sprint distances (m), maximal velocity achieved (km·h-1), and the number of sprints, accelerations and decelerations were quantified using both GPS and IA. ...
... The main criteria for selecting a player were two-fold: (a) the player was very likely to carry the ball many times during the course of a game and (b) the player would play on both offense and special teams. More specifically, RB were subject to the most severe collisions (63) while WR cover greater total distance, high-intensity running, sprint distance, and high-intensity acceleration and deceleration efforts than the other positions (60). As such, players selected for this study were RB and WR. ...
Advancements in wearable technologies such as Global Positioning System (GPS) and accelerometers allow coaches and practitioners to gain a better understanding of the physiological and biomechanical demands of a sport. This study documents and describes the movement demands of Canadian university football during training and competition over
the course of two seasons. GPS data from sixteen players were collected daily during 29 training sessions and 8 games in 2016 and 31 training sessions and 9 games in 2017, respectively. Data revealed that players covered on average 3006 +/- 1536 and 3860 +/- 1189 meters of total distance during training sessions in 2016 and 2017, respectively. Of this distance, high-speed running (165 +/- 141; 287 +/- 181 m), high metabolic load distance (370 +/- 243; 548 +/- 247 m), sprints(10 +/- 9; 17 +/- 10); acceleration (216 +/- 113; 200 +/- 67) and deceleration efforts (191+/- 99; 180 +/- 64) were also obtained. Movements demands were higher during games, revealing that players covered on average 5954 +/-1053 and 6155 +/- 509 meters of total distance in 2016 and 2017, respectively. High-speed running (445 +/- 128; 541 +/- 74 m), high metabolic load distance (784 +/- 184; 900 +/-103 m), sprints (23 +/- 5; 26 +/- 3); acceleration (277 +/- 49; 316 +/- 35) and deceleration efforts (263 +/- 49; 295 +/- 35) were also higher in games than in training sessions. This study provides novel insight into the movement demands of Canadian university football, which should be supported by the regular assessment and training of lower-body muscular strength, sprinting speed and repeated-sprint ability.
... These findings were partially consistent with those of previous studies, especially with respect to larger size and greater absolute strength for bench press and back squat [2,4,6]. Wellman et al. [21] explained the characteristics of linemen's movements. Although there are some differences in positional requirements, usually they accelerate and decelerate for blocking or chasing a ball, requiring quick changes in direction. ...
... Compared with linemen, skill positions have more complicated tactics. For example, regarding offensive positions, ball carriers such as running backs and wide receivers do not only carry or catch the ball but also block or contribute to making a pass route [21,25]. On the other hand, as a defensive position, defensive backs, who are the last line of defense, cover a wide range of defensive positions while mainly matching up with wide receivers [21,25]. ...
... For example, regarding offensive positions, ball carriers such as running backs and wide receivers do not only carry or catch the ball but also block or contribute to making a pass route [21,25]. On the other hand, as a defensive position, defensive backs, who are the last line of defense, cover a wide range of defensive positions while mainly matching up with wide receivers [21,25]. In both positions, players repeatedly run at high speed with quick acceleration and deceleration, meaning that their intermittent sprint ability seems be important for performing their positional requirements. ...
BACKGROUND: Few studies have investigated the variations in body composition and performance in Japanese collegiate American-football players. OBJECTIVE: To clarify what characterizes competitors at the highest levels – in the top division or on the starting lineup – we compared players’ body compositions and performance test results. METHODS: This study included 172 players. Each player’s body composition and performance (one-repetition maximum bench press, one-repetition maximum back squat, and vertical jump height) were measured; power was estimated from vertical jump height and body weight. Players were compared according to status (starter vs. non-starter), position (skill vs. linemen), and division (1 vs. 2). Regression analysis was performed to determine characteristics for being a starter. RESULTS: Players in higher divisions and who were starters were stronger and had more power, greater body size, and better performance test results. Players in skill positions were relatively stronger than those in linemen positions. Vertical jump height was a significant predictor of being a starter in Division 1. CONCLUSION: Power and vertical jump may be a deciding factor for playing as a starter or in a higher division.
... A recent consensus statement established guidelines and best practices regarding monitoring athlete training loads, including how to best define training load, methods of measurement, and applications across different sports (Bourdon et al. 2017). The monitoring of training loads has been used in collision-based team sports, such as Australian Rules football (Gray and Jenkins 2010), American football (DeMartini et al. 2011;Wellman et al. 2016Wellman et al. , 2017a and rugby (McLellan and Lovell 2013;Cummins et al. 2018) to quantify competition demands, examine trends throughout different phases of the season, and to examine relationships between training load, recovery, and injury risk. Monitoring training loads throughout the season, may enable practitioners to identify the players at a higher risk of injury, which has been shown in Australian Rules football (Rogalski et al. 2013;Colby et al. 2014), American football (Wilkerson et al. 2016), and rugby (Gabbett and Domrow 2007). ...
... American football (AF) is a collision-based team sport, consisting of high-intensity running mixed with jumping, backpedaling, accelerating, decelerating, and lateral movement (Wellman et al. 2016. At the American collegiate level, the typical play duration is ~5 sec. ...
... In AF, each position group has a unique role and tactical strategy, which subsequently leads to differences in movement profiles and training loads in practice and competition (Wellman et al. 2016(Wellman et al. , 2017aDeMartini et al. 2011). Such discrepancies in movement demands across position groups may warrant the individualization of training loads to elicit necessary physiological adaptation. ...
Background: The purpose of this study was to examine the relationship between training load and next-day recovery in collegiate American football (AF) players during pre-season.
Methods: Seventeen athletes (Linemen, n = 6; Non-linemen, n = 11) participated in the 14-day study wearing monitoring (accelerometer + heart rate) sensors during on-field practice sessions throughout pre-season to assess the physiological (PL), mechanical load (ML) and recording of session RPE (sRPE load) immediately post-practice. Prior to practice, participants completed a drop-jump reactive strength index (RSI) test and reported perceived recovery status (PRS). Loaded counter movement vertical jump was assessed before and after pre-season.
Results: For every one unit increase in sRPE load, RSI declined by 0.03. Non-linemen had a lower RSI value of 73.1 units compared to linemen. For every one unit increase in ML, the PRS decreased by 0.01. Non-linemen recorded higher average ML during week 2 (ES = 1.17) compared to linemen. Non-linemen recorded higher RSI values in weeks 1 (ES = −1.41) and 2 (ES = −1.72) compared to linemen. All training load and recovery parameters were lower week 2 compared to week 1 (p < 0.05) for all players.
Conclusions: Next-day RSI values were influenced by sRPE load while next-day PRS appears to be more influenced by ML. No difference in PL or sRPE load was observed been groups despite non-linemen completing a higher ML throughout the preseason. A combination of training load and recovery metrics may be needed to monitor the fatigue and state of readiness of each player.
... The characteristics of the 19 included studies are summarised in Table 3. One study investigated American Football [42], two Australian Football [43,44], one hockey [18], four rugby league [29,[45][46][47], three rugby sevens [36,48,49], two rugby union [41,50] and six soccer [10,16,17,19,20,51]. Across all seven team sports investigated, the total sample included 469 players with a mean age ranging from 18 to 29 years. ...
... Sixty-three percent (n = 12) of studies used GPS with a raw 10-Hz sampling frequency, with the remaining 32% (n = 7) of studies using 5 Hz. Four of the studies [29,36,42,49] that captured data at 5 Hz incorporated an interpolation algorithm that resulted in a 15-Hz output. ...
... The most common threshold used to classify the start of high-intensity acceleration or deceleration was 3 m·s −2 (n = 11, 58%). Six studies [20,36,42,[48][49][50] also used a very high intensity threshold starting at either 3.5 m·s −2 (n = 1) or 4 m·s −2 (n = 5). Variables used to report high or very high intensity acceleration and decelerations included frequency (n = 17 studies), distance covered (n = 3 studies) and time spent (n = 1 study). ...
Background
The external movement loads imposed on players during competitive team sports are commonly measured using global positioning system devices. Information gleaned from analyses is employed to calibrate physical conditioning and injury prevention strategies with the external loads imposed during match play. Intense accelerations and decelerations are considered particularly important indicators of external load. However, to date, no prior meta-analysis has compared high and very high intensity acceleration and deceleration demands in elite team sports during competitive match play.
Objective
The objective of this systematic review and meta-analysis was to quantify and compare high and very high intensity acceleration vs. deceleration demands occurring during competitive match play in elite team sport contexts.
Methods
A systematic review of four electronic databases (CINAHL, MEDLINE, SPORTDiscus, Web of Science) was conducted to identify peer-reviewed articles published between January 2010 and April 2018 that had reported higher intensity (> 2.5 m·s⁻²) accelerations and decelerations concurrently in elite team sports competitive match play. A Boolean search phrase was developed using key words synonymous to team sports (population), acceleration and deceleration (comparators) and match play (outcome). Articles only eligible for meta-analysis were those that reported either or both high (> 2.5 m·s⁻²) and very high (> 3.5 m·s⁻²) intensity accelerations and decelerations concurrently using global positioning system devices (sampling rate: ≥ 5 Hz) during elite able-bodied (mean age: ≥ 18 years) team sports competitive match play (match time: ≥ 75%). Separate inverse random-effects meta-analyses were conducted to compare: (1) standardised mean differences (SMDs) in the frequency of high and very high intensity accelerations and decelerations occurring during match play, and (2) SMDs of temporal changes in high and very high intensity accelerations and decelerations across first and second half periods of match play. Using recent guidelines recommended for the collection, processing and reporting of global positioning system data, a checklist was produced to help inform a judgement about the methodological limitations (risk of detection bias) aligned to ‘data collection’, ‘data processing’ and ‘normative profile’ for each eligible study. For each study, each outcome was rated as either ‘low’, ‘unclear’ or ‘high’ risk of bias.
Results
A total of 19 studies met the eligibility criteria, comprising seven team sports including American Football (n = 1), Australian Football (n = 2), hockey (n = 1), rugby league (n = 4), rugby sevens (n = 3), rugby union (n = 2) and soccer (n = 6) with a total of 469 male participants (mean age: 18–29 years). Analysis showed only American Football reported a greater frequency of high (SMD = 1.26; 95% confidence interval [CI] 1.06–1.43) and very high (SMD = 0.19; 95% CI − 0.42 to 0.80) intensity accelerations compared to decelerations. All other sports had a greater frequency of high and very high intensity decelerations compared to accelerations, with soccer demonstrating the greatest difference for both the high (SMD = − 1.74; 95% CI − 1.28 to − 2.21) and very high (SMD = − 3.19; 95% CI − 2.05 to − 4.33) intensity categories. When examining the temporal changes from the first to the second half periods of match play, there was a small decrease in both the frequency of high and very high intensity accelerations (SMD = 0.50 and 0.49, respectively) and decelerations (SMD = 0.42 and 0.46, respectively). The greatest risk of bias (40% ‘high’ risk of bias) observed across studies was in the ‘data collection’ procedures. The lowest risk of bias (35% ‘low’ risk of bias) was found in the development of a ‘normative profile’.
Conclusions
To ensure that elite players are optimally prepared for the high-intensity accelerations and decelerations imposed during competitive match play, it is imperative that players are exposed to comparable demands under controlled training conditions. The results of this meta-analysis, accordingly, can inform practical training designs. Finally, guidelines and recommendations for conducting future research, using global positioning system devices, are suggested.
... Until recently, it has been extremely difficult to determine how much work/activity a player performs or goes through during a practice. The development of wearable technology and the use Global Positioning Systems (GPS) have allowed coaches and practitioners to monitor and analyze player training loads and activity during practices and games [1][2][3][4] . Due to the nature of college football and limited access to college football players, research is scarce at best. ...
... Due to the nature of college football and limited access to college football players, research is scarce at best. There is a handful of studies that address workload of games ranging from video analysis of work to rest ratios [5] , competition modeling [6] , and demands quantified by GPS [4,7,8] . Fewer studies have looked at the physiological demands of practice. ...
... The use of GPS and Heart Rate (HR) data are common in soccer [14] , rugby [15] , and Australian Rules football [16] . Common measurements include speed zones [4,8,11,16,17] , workload [9,17] , and HR derived data [11,17] . To date there is only one study that has analyzed physiological load in college football players using both HR and GPS data [11] . ...
Purpose: The aims of this study was to determine the physiological demand of practice in National Collegiate Athletic Association Division I football players through Global positioning system, accelerometers and Heart Rate monitoring across position groups. Approach: Thirty players wore a portable integrated monitor unit for 10-weeks during the fall football season. They were divided into position groups and compared across different speeds zones, HR zones, accelerations, work variables and distance traveled at different speeds. Results: For all of the speed and distance variables there was significant (P<0.05) differences between position groups with wide receivers, running backs and defensive backs, running at high speeds and covering more distance. For HR data there was no major significant differences between position groups. For work variables, quarterbacks had the smallest work to rest ratio, while wide receivers, running backs and defensive backs had the smallest ratios. Compared to game data, practice is performed at slow speeds but covers greater distances. Conclusion: Overall, skilled positions in football run at high speeds and cover more ground than their counterparts and accelerate the most while heat rate data indicated that internal demands of practice are similar across position groups.
... Recently, sports teams have begun implementing movement-based sensors, such as those mentioned, to actively monitor player training loads and player metrics during high-acuity training sessions [10,14,16]. A recent study in January 2016, comprised of 33 National Collegiate Athletic Association (NCAA) Division I football players, were monitored with portable differential GPS and integrated tri-axial accelerometers over 12 regular season games [17]. The acquired data showed that the use of wearable sensor technology helped create a systematic approach to position and game specific physical conditioning [17]. ...
... A recent study in January 2016, comprised of 33 National Collegiate Athletic Association (NCAA) Division I football players, were monitored with portable differential GPS and integrated tri-axial accelerometers over 12 regular season games [17]. The acquired data showed that the use of wearable sensor technology helped create a systematic approach to position and game specific physical conditioning [17]. ...
... The study correlated differences in total running volume and high intensity movement demands to specific player position on the field showing the ability of wearable technology to quantify player fatigue, recovery time, and game day performance requirements [17]. Another 2016 study, conducted by a major American sports network, showed that athletes who used wearable technology during their workouts were 60% less likely to experience soft-tissue injuries during the course of the season [18]. ...
The digital health field has seen a surge in product development over the last decade, with product introductions ranging from wrist monitors, epidermal electronics, electronic pills and smart garments, much of these precipitated through the commercialisation and commoditisation of sensor technology. The emergence of wearable technology has recently garnered heightened interest by physicians and the general public. The convenient use of wireless technology to track and monitor physiological parameters, such as heart rate, distance, sleep and stress, has emerged to become relevant to patient care and human performance assessment. However, collecting data is not enough to inform clinical decision-making. It is essential to translate the acquired data into information relevant to clinicians. Our experiences tell us that team competencies must mirror the interdisciplinary technology itself. Thus, an interdisciplinary team blending expertise from engineering, medicine, and nursing is believed to be essential in translating wearable technology into the field. This review discusses the application of wearable sensors to monitor human performance assessment in domains necessitating accurate, reliable, and timely transmission of acquired bio-metric and bio-vital data. A key result disseminating from our investigations is the need to develop predictive models based off of the data acquired from wearable devices to necessitate the development of athlete-centred treatment plans to expedite the return-to-play time and to maximise performance.
... The prevalence of micro-sensor technology and improved precision of video performance analysis techniques in recent years has seen the quantification of running demands become more relevant in AF (61,74). Although there may be conjecture around the values which constitute high speed running and sprinting, using a sprint speed value of >22.5 km/h, Wellman et al. (74) reported the total distance covered (mean ± SD) in a Division I collegiate football game for offensive players ranged from 9.3 ± 11.3 metres (m) for offensive linemen to 315.8 ± 163.2 m for wide receivers. ...
... The prevalence of micro-sensor technology and improved precision of video performance analysis techniques in recent years has seen the quantification of running demands become more relevant in AF (61,74). Although there may be conjecture around the values which constitute high speed running and sprinting, using a sprint speed value of >22.5 km/h, Wellman et al. (74) reported the total distance covered (mean ± SD) in a Division I collegiate football game for offensive players ranged from 9.3 ± 11.3 metres (m) for offensive linemen to 315.8 ± 163.2 m for wide receivers. While 74 for the defensive positions Wellman et al. (74) reported distances ranging from 7.7 ± 10.9 m (defensive tackles) to 247.0 ± 113.1 m (defensive backs). ...
... Although there may be conjecture around the values which constitute high speed running and sprinting, using a sprint speed value of >22.5 km/h, Wellman et al. (74) reported the total distance covered (mean ± SD) in a Division I collegiate football game for offensive players ranged from 9.3 ± 11.3 metres (m) for offensive linemen to 315.8 ± 163.2 m for wide receivers. While 74 for the defensive positions Wellman et al. (74) reported distances ranging from 7.7 ± 10.9 m (defensive tackles) to 247.0 ± 113.1 m (defensive backs). These position specific distances were later supported by the work of Sanders et al. (61), where the defensive backs covered 324.7 ± 157.5 m, whereas the wide receivers covered 295.1 ± 166.9 m ( Although understanding the total amount of work or distance covered by an athlete within certain intensity bands during a game is important, it is also highly relevant for the strength and conditioning coach to understand what accelerations and decelerations were undertaken by the player relative to their position. ...
Strength and conditioning for collegiate American football (AF) players follows basic principles of training, adapted within numerous contextual challenges. Some challenges include seasonal calendars, contact time restrictions, academic model and, academic requirements. The greatest expertise of the strength and conditioning coach in an academic setting is finding the most efficient way to increase the physical abilities specific to the collegiate AF player within these contexts. The purpose of this article is to orient the reader to collegiate AF player demands, define the challenges based
upon the academic model of athletics in the United States, and provide programming recommendations based upon application of scientific literature within this academic model. An analysis of the current literature involving anthropometric and performance data with reference to the collegiate AF player was performed. Successful strength and conditioning programs for collegiate AF players involve an emphasis on maximal strength and power development, coupled with metabolic conditioning based on player positions, relevant to specific in-game demands and tactics. A microcycle template is provided to contextualise and further understand how to effectively integrate physical abilities such as maximal strength and power in a weekly periodisation model. An example of metabolic conditioning is shown so that the reader can increase their understanding of the physical demands placed on the AF player. Although training time is limited due to the academic model, it is possible to overcome these constraints and develop the key strength and power requirements of AF athletes. The considerations provided will aid the reader to develop a sound and evidence-based strength and conditioning program which can be individualised according to training level, maturation, and eligibility of the collegiate AF players.
... These tracking devices are capable of accumulating substantial amounts of movement-related data during competition and practice and have been used to collect activity profiles of athletes in Australian football, cricket, hockey, rugby, and soccer (2), but reports of such use in American football is much more rare. For example, a study by Wellman et al. (11) sought to examine movement demands of NCAA Division I football players at various positions through GPS. Another study by the same principal author examined impact profiles by positions using GPS technology (12). ...
... All players' physical characteristics are included in Table 1. Participants were chosen based on equitable percentage of total snaps, which, similarly to another study (11), required all subjects participating in this study to have accumulated a minimum of 75% of total snaps ( x 5 59.1 6 4.7) in at least 2/3rd of the 9 conference games. Characteristics of the participants are illustrated in Table 1. ...
... 0.05), WR traveled 4 and 9.7% further than DL and OL, respectively. These results are not in full agreement with others (5,11,13), in that the results suggest that nonlineman (i.e., DB and WR) cover significantly greater distances than lineman during practice and games. Logically, much depends on the style of offense and defense played. ...
Bayliff, GE, Jacobson, BH, Moghaddam, M, and Estrada, C. Global positioning system monitoring of selected physical demands of NCAA Division I football players during games. J Strength Cond Res 33(5): 1185-1191, 2019-Global positioning system (GPS) tracking of athletes in selected sports is a new innovation into obtaining comprehensive data regarding physical output with respect to distance travelled (DT), acceleration, and change of direction. The purpose of this study was to determine selected physical demands of American football players during the course of games and to compare such data by player position. Offensive lineman (OL) (n = 14) and defensive lineman (DL) (n = 9) and offensive wide receivers (WRs) (n = 10) and defensive backs (DBs) (n = 10) were fitted with GPS monitors during games. Collected data included DT, maximum velocity (MV), and acceleration (AC), deceleration (DC) distance at 2 intensities. Results indicated that DBs travelled significantly (p < 0.05) greater distances than OL and WR, but not DL. For MV, DBs and WRs were not significantly different but were significantly different from OL and DL. Also, DL was significantly different than OL. For the most intense acceleration (3-10 m·s), WR accelerated significantly further than all other positions and DBs accelerated further than DL and OL. There was not significant difference between DL and OL. For deceleration at the high-intensity measure, significant differences existed among all positions. Underestimation of workload during games could be a factor for the overuse and soft-tissue injuries and more serious injuries. Furthermore, using GPS tracking of similar variables as found in this study may benefit coaches and trainers in many other high-intensity sports.
... A merican football is a physically demanding contact sport comprising substantial impact loads and intermittent bouts of high-intensity activity (45,46). Injury rates are correspondingly high and likely associated with the heavy contact loads; however, .25% of injuries are attributed to preventable noncontact injury (8). ...
... Workload monitoring is indeed commonplace, with global positioning systems (GPSs) and built in inertial measurement units (IMUs) typically used in college football to quantify training and match workloads (37,(45)(46)(47). Across a range of contact team sports, including American college football, increased injury risks have consistently been observed when "spikes" in current (acute) relative to accumulated (chronic) GPS-/IMU-derived acute:chronic workload ratios (ACWRs) are observed (7,19,37). ...
... Playerload was the chosen workload measure given its suitability for encompassing both indoor and outdoor training comprising acceleration, deceleration, sprint, and contact efforts (4,34) and the frequency of these activities in college football (45,46). Increased injury risks were observed at lower ACWRs than those commonly reported; however, the characteristic "U" curve depicting a "sweet spot" at moderate ACWR and injury risks 2.5 to 3 times greater with lower and higher ratios (13) was apparent. ...
Acute:chronic workload ratios (ACWRs) are associated with injury risk across team sports. In this study, one season of workload and wellness data from 42 collegiate football players were retrospectively analyzed. Daily 7:21 day exponentially weighted moving average (EWMA) ACWRs were calculated, and z-score fluctuations (“normal,” “better,” and “worse”) in sleep, soreness, energy, and overall wellness were assessed relative to the previous day ACWRs and considered as an interactive effect on the risk of noncontact injury within 0–3 days. Fifty-five noncontact injuries were observed, and injury risks were very likely higher when ACWRs were 2 SDs above (relative risk [RR]: 3.05, 90% confidence interval [CI]: 1.14–8.16) and below (RR: 2.49, 90% CI: 1.11–5.58) the mean. A high ACWR was trivially associated (p < 0.05) with “worse” wellness (r = −0.06, CI: −0.10 to −0.02), muscle soreness (r = −0.07, CI: −0.11 to −0.03), and energy (r = −0.05, CI: −0.09 to −0.01). Feelings of “better” overall wellness and muscle soreness with collectively high EWMA ACWRs displayed likely higher injury risks compared with “normal” (RR: 1.52, 90% CI: 0.91 to 2.54; RR: 1.64, 90% CI: 1.10–2.47) and likely or very likely (RR: 2.36, 90% CI: 0.83 to 674; RR: 2.78, 90% CI: 1.21–6.38) compared with “worse” wellness and soreness, respectively. High EWMA ACWRs increased injury risk and negatively impacted wellness. However, athletes reporting “better” wellness, driven by “better” muscle soreness presented with the highest injury risk when high EWMA ACWRs were observed. This suggests that practitioners are responsive to, and/or athletes are able to self-modulate workload activities.
... Also, it is beneficial to examine loads across quarters to obtain an in-depth analysis of volume and intensity of game play and to identify the fluctuation of demands within the game. Because tactical requirements are basketballposition-specific, the exploration of external loads across positions is warranted because loads may vary based on the differing physical demands (6,42,43). ...
... The exploration of external load across position type in other team-based field sports (21,25,26,34,41,42) has provided insight into position-specific demands that can inform programming and training strategies. Although such data are limited for basketball (36), a recent 4-year longitudinal study in collegiate women basketball athletes reported that guards experienced higher PL and PL·min 2 1 than forwards (34). ...
Brown, FSA, Fields, JB, Jagim, AR, Baker, RE, and Jones, MT. Analysis of in-season external load and sport performance in women’s collegiate basketball. J Strength Cond Res XX(X): 000–000, 2023—Quantifying and monitoring athlete workload throughout a competitive season is a means to manage player readiness. Therefore, the purpose of the current study was to quantify practice and game external loads and to assess the relationship between such loads and basketball-specific performance metrics across a women's collegiate basketball season. Thirteen National Collegiate Athletic Association Division I women basketball athletes (age 20.08 ± 1.55 years) wore Global Positioning Systems sensors equipped with triaxial accelerometers for 29 games and 66 practices during the 2019–20 season. A multivariate analysis of variance was used to assess differences in external load between high- and low-minute players and across quarters within games ( p < 0.05). Bivariate Pearson correlation coefficients were run to determine relationships between external loads and metrics of basketball performance. Findings indicated that high- and low-minute athletes experienced different loads during games and practices ( p < 0.001). External loads differed by quarter, such that player load (PL) was highest in Q4 ( p = 0.007), PL·min ⁻¹ was highest in Q1 and lowest in Q4 ( p < 0.001), and explosive ratio (i.e., ratio of PL and explosive efforts) was lowest in Q3 ( p = 0.45). Relationships existed between PL·min ⁻¹ and field goals ( r = 0.41; p = 0.02) and between the explosive ratio and free throws ( r = 0.377 p = 0.04). These results can be used to inform design of training sessions with the intent to prepare athletes for the demands of the competitive season. It is recommended that future research continue to explore the relationship of sport-specific performance metrics and athlete external load.
... Yet, similar to previous research we found no significant difference in HR mean between non-skill and skilled players [4]. Positions on both sides of the ball such as wide receivers, defensive backs, and linebackers have been found to cover greater distances and may require additional training to meet the physiologic demands of their position [22]. The simplicity of HR monitoring and developing of new methods of analyzing the data collected may provide a clearer picture of current training practices and how to adapt programs to better prepare players. ...
... Defensive players were found to spend more time at a vigorous intensity (≥90% HR max ) compared to offensive players. Defensive players may consistently employ tactics involving less contact and more high-velocity movements such as backpedaling and accelerating [2,22,23] resulting in more total time in vigorous intense-type activity. In addition, defensive players are required to respond to an unknown set of circumstances, thus defensive players may maintain a higher intensity state in order to respond to the offensive strategies employed. ...
This study aimed to describe the physical demands of American football players using novel performance analysis techniques. Heart rate (HR) and accelerometer-based activity levels were observed across two pre-season scrimmages in 23 Division I collegiate football players (age: 19 ± 1 y, height: 1.90 ± 0.06 m, weight: 116.2 ± 19.4 kg). Data were analyzed using a MATLAB program and inter-rater reproducibility assessed using inter-class correlations (ICC). Players were analyzed by side (offense/defense) and position (skill/non-skill). Performance variables assessed in bursts of activity included burst duration, HRmean and HRmax (bpm), and mean activity (vector magnitude units [vmu]). Exercise intensity was categorized as time spent in % HRmax in 5% increments. The burst duration (8.1±3.9 min, ICC = 0.72), HRmean (157 ± 12 bpm, ICC = 0.96) and mean activity (0.30 ± 0.05 vmu, ICC = 0.86) were reproducible. HRmean (p = 0.05) and HRmax (p = 0.001) were greater on defense. Offense spent more time at 65–70% HRmax (p = 0.01), 70–75% HRmax (p = 0.02) while defense spent more time 90–95% HRmax and ≥95% HRmax (p = 0.03). HRmean (p = 0.70) and HRpeak (p = 0.80) were not different between positions across both sides. Skilled players demonstrated greater mean activity (p = 0.02). The sport-specific analysis described HR and activity level in a reproducible manner. Automated methods of assessing HR may be useful in training and game time performance but ultimately provides support to coaching decision making.
... Sports scientists continually seek newer technologies, data platforms, and therapies to help athletes perform at their highest level while reducing the risk of injury over an arduous season. Sports teams have recently utilized wearable sensors such as the Catapult OptimEye S5 (Wellman et al., 2016;Li et al., 2020), Zebra RFID tag (Zebra and The NFL, 2019), and Zephyr BioHarness (Nazari et al., 2018) to provide a quantifiable measure of the exertional output of the athlete, described as "workload." The collection of such data has allowed some professional teams to show a relationship between workload and injury rates . ...
... Substantially increased injury risk with a low chronic workload emphasizes the need for proper load management, especially in athletes with multiple game or training absences. Wellman et al. utilized the Catapult SPI HBU GPS sensor to monitor and compare movement profiles (distance, velocity, and acceleration) among various position groups in Division I American Football players to study the physical demands during competitive play (Wellman et al., 2016). Data showed that wide receivers and defensive backs had more high-intensity acceleration bursts and traveled greater distances compared to other positions. ...
Wearable sensors enable the real-time and non-invasive monitoring of biomechanical, physiological, or biochemical parameters pertinent to the performance of athletes. Sports medicine researchers compile datasets involving a multitude of parameters that can often be time consuming to analyze in order to create value in an expeditious and accurate manner. Machine learning and artificial intelligence models may aid in the clinical decision-making process for sports scientists, team physicians, and athletic trainers in translating the data acquired from wearable sensors to accurately and efficiently make decisions regarding the health, safety, and performance of athletes. This narrative review discusses the application of commercial sensors utilized by sports teams today and the emergence of descriptive analytics to monitor the internal and external workload, hydration status, sleep, cardiovascular health, and return-to-sport status of athletes. This review is written for those who are interested in the application of wearable sensor data and data science to enhance performance and reduce injury burden in athletes of all ages.
... The players are exposed to collisions, and blunt force trauma as a result of frequent repeated contact with opponents, and the ground during tackling, blocking, and ball handling activities. This induces additional stress on players, which is not common in other forms of physical activity [34,35]. Despite this stress, it is important that players have and maintain their high-level perceptual-cognitive functions, and advanced sensorimotor characteristics during the games to gain points, to advance the ball, to intercept injuries by preventing possible collisions with the opponents, to move quickly to empty spaces without colliding, and to throw the ball to their teammates at the right time by reading the game well. ...
... Despite this stress, it is important that players have and maintain their high-level perceptual-cognitive functions, and advanced sensorimotor characteristics during the games to gain points, to advance the ball, to intercept injuries by preventing possible collisions with the opponents, to move quickly to empty spaces without colliding, and to throw the ball to their teammates at the right time by reading the game well. In the literature, there are some studies that evaluate the performance characteristics of American football players such as sprint and jump (9), match performance [35], running and non-running activities [2], impulse control [36], executing motor responses in the face of distraction [10], and impact profiles which they are exposed to [5] according to the their playing positions. There is limited study comparing the perceptual-cognitive, and sensorimotor characteristics of American football players such as CAT, reaction time, and dynamic balance performance by their playing positions. ...
Purpose: The aim of this study was to compare the coinciding anticipation timing (CAT), reaction time and dynamic balance performances of American football players according to their playing positions.
Material: Thirty-five American football players, who train at least 3 days a week, and compete in Universities Protected Football 1st League, participated in this study, voluntarily. The players were divided into two playing positions: offensive (17 players, mean age: 20.76 ± 1.30 years) and defensive (18 players, mean age: 21.94 ± 2.87 years). The CAT at different stimulus speeds (6 mph, 12 mph), reaction time (visual, auditory, mixed), and dynamic balance performance (anterior-posterior, medial-lateral, perimeter lenght) were measured in the laboratory environment. The CAT, reaction time, and dynamic balance performance of players were determined by Bassin Anticipation Timer, Newtest 1000, and Technobody Prokin-200, respectively.
Results: The data obtained were analyzed in SPSS (20.0) program. Firstly, the raw data for CAT performance (6mph, 12 mph) were converted to absolute error score. According to Shapiro-Wilk test result, the all data showed normal distribution. Independent Sample t test was used to determine the differences between the two playing positions. In addition, the effect size between the two playing positions was calculated in parameters with showing significant differences, and Cohen’s d (1988) values were taken into account. Compared with the defensive players (20.15±3.81 ms), the absolute error scores at fast stimulus speeds (12 mph) of offensive players (17.45±3.48 ms) was found to be significantly lower (t(33) =-2.181, p=.036). The visual reaction time of offensive players (318.11± 17.47 ms) was significantly shorter than defensive players (340.58± 32.60 ms, t(26322) =-2.560, p=.017). In terms of dynamic balance parameters such as perimeter lenght, anterior-posterior, and medial-lateral, there was no statistically significant difference between the playing positions (p>0.05).
Conclusions: Perceptual-cognitive characteristics such as CAT, and reaction time performance differ according to the playing positions, and this difference may be related to the physical, and cognitive demands required by their playing positions.
... In American football, as in most team sports, athletes typically repeat short-duration, high-intensity bouts of movement such as sprinting, interspersed with brief periods of low-intensity activity [1]. As such, repeated-sprint ability (RSA) is an important determinant of performance in American football, especially for the skilled players (i.e., wide receivers, running backs, quarterbacks, tight ends, defensive backs, and linebackers) who execute the greatest numbers of sprints throughout a match [1]. ...
... In American football, as in most team sports, athletes typically repeat short-duration, high-intensity bouts of movement such as sprinting, interspersed with brief periods of low-intensity activity [1]. As such, repeated-sprint ability (RSA) is an important determinant of performance in American football, especially for the skilled players (i.e., wide receivers, running backs, quarterbacks, tight ends, defensive backs, and linebackers) who execute the greatest numbers of sprints throughout a match [1]. Research has demonstrated that improving RSA through physical training has clear benefits for team-sport athletes [2,3], with a likely advantageous transfer to the playing field [4,5]. ...
Team-sport athletes and coaches use varied strategies to enhance repeated-sprint ability (RSA). Aside from physical training, a well-conducted warm-up enhances RSA via increased oxidative metabolism. Strategies that impede blood flow could potentiate the effects of a warm-up due to their effects on the endothelial and metabolic functions. This study investigated whether performing a warm-up combined with blood-flow restriction (WFR) induces ergogenic changes in blood volume, muscle oxygenation, and RSA. In a pair-matched, single-blind, pre-post parallel group design, 15 American football players completed an RSA test (12 × 20 m, 20 s rest), preceded by WFR or a regular warm-up (SHAM). Pressure was applied on the athletes’ upper thighs for ≈15 min using elastic bands. Both legs were wrapped at a perceived pressure of 7 and 3 out of 10 in WFR and SHAM, respectively. Changes in gastrocnemius muscle oxygen saturation (SmO2) and total hemoglobin concentration ([THb]) were monitored with near-infrared spectroscopy. Cohen’s effect sizes (ES) were used to estimate the impact of WFR. WFR did not clearly alter best sprint time (ES −0.25), average speed (ES 0.25), total time (ES −0.12), and percent decrement score (ES 0.39). While WFR did not meaningfully alter average SmO2 and [THb], the intervention clearly increased the maximum [THb] and the minimum and maximum SmO2 during some of the 12 sprint/recovery periods (ES 0.34–1.43). Results indicate that WFR positively alters skeletal muscle hemodynamics during an RSA test. These physiological changes did not improve short-term RSA, but could be beneficial to players during longer activities such as games.
... To paint a current picture of research in AmF, projects commonly include: injury epidemiology [e.g., 26,27,28,29,30], prediction of combine performance to NFL production [e.g., 31,32], relationship of combine performance to draft success [e.g., 33], physical development of athletes [e.g., [34][35][36][37][38], body composition [e.g., 39,40], body and performance changes over high school or collegiate careers [e.g., [41][42][43], athlete height/weight trends over time [e.g., 44,45], GPS/accelerometry in college games or practice [e.g., [9][10][11]46,47], and reviews intended to translate knowledge for coaches [e.g., 13,[48][49][50]. Most studies are descriptive in nature, with few studies exploring on-field performance or concepts contributing to it. ...
Despite enormous revenue production and a recent trend of investment in sport medicine research, American football has yet to make a measurable investment in sport performance science research. As a result, available knowledge is presently skewed toward technical and tactical domains, with very little knowledge development occurring in other areas within the sport science realm. In this editorial, we discuss plausible contributing factors to the current situation, and suggest ways to resolve this issue and move forward for the betterment of the sport.
... In any respect, not every team sport shows this tendency. For example, American football players have been shown to perform a greater amount of high-intensity accelerations while lacrosse shows similar frequencies (44,125). Furthermore, individual sports such as tennis or squash also require multiple decelerations and CODs (35,122). ...
Eccentric resistance training has been shown to elicit beneficial effects on performance and injury prevention in sports because of its specific muscular and neural adaptations. Within the different methods used to generate eccentric overload, flywheel eccentric training has gained interest in recent years because of its advantages over other methods such as its portability, the ample exercise variety it allows and its accommodated resistance. Only a limited number of studies that use flywheel devices provide enough evidence to support the presence of eccentric overload. There is limited guidance on the practical implementation of flywheel eccentric training in the current literature. In this article, we provide literature to support the use of flywheel eccentric training and present practical guidelines to develop exercises that allow eccentric overload.
See Supplemental Digital Content 1, http://links.lww.com/SCJ/A380 for a video abstract of this article.
... Sports scientists constantly research newer technologies, data platforms, and any therapies able to help athletes to perform at their best level while minimizing their risk of injuries. Regarding sports teams, many wearable technologies have been recently utilized to quantify their workload (1)(2)(3) and to prove a link between it and injury rates (4). According to Vamathevan et al. (5), the opportunity of having open-source repositories of wearable data may simplify collaborations between academics, sports teams, and Personal Protective Equipment (PPE) manufacturers to maximize the health and performance of athletes. ...
While the term “safety vests” has been used to capture these products to reduce the potential for harm in jockeys under the Personal Protective Equipment (PPE) umbrella, much of the research in this area has focused on factors typically echoing health, well-being, physiological and cognitive function, and performance of horse riders with very little work about examining how its design may reduce the severity of jockeys' injuries. Due to the recent advances in technology and wearable sensors, the author considered a qualitative study focusing on the analysis of a real-life example involving end and co-dependent users in the design development of jockeys' safety vests. This little article offers an overview of the most popular jockeys' injuries, why there is a need for better protection, and also describes how data were collected and present a summary of the key findings to encourage future research in this field, aiming to create a new prototype. High-impact sports may potentially create severe injuries or deaths to athletes: thus, there is a strong faith in the application of wearable sensor data and data science to also enhance jockeys' safety vest performance.
... These data provide locomotor variables (e.g., distance, number of sprints, player load) [3], movement variables (e.g., velocity, acceleration) [4] and sport-specific patterns (e.g., player skills) [5]. These variables have been used to improve physical performance [6], monitor technical and tactical performance [7] and improve the injury prevention and recovery processes [8]. ...
A.; Reche-Soto, P.; Pino-Ortega, J. Use, Validity and Reliability of Inertial Movement Units in Volleyball: Systematic Review of the Scientific Literature. Sensors 2023, 23, 3960. Abstract: The use of inertial devices in sport has become increasingly common. The aim of this study was to examine the validity and reliability of multiple devices for measuring jump height in volleyball. The search was carried out in four databases (PubMed, Scopus, Web of Sciences and SPORTDiscus) using keywords and Boolean operators. Twenty-one studies were selected that met the established selection criteria. The studies focused on determining the validity and reliability of IMUs (52.38%), on controlling and quantifying external load (28.57%) and on describing differences between playing positions (19.05%). Indoor volleyball was the modality in which IMUs have been used the most. The most evaluated population was elite, adult and senior athletes. The IMUs were used both in training and in competition, evaluating mainly the amount of jump, the height of the jumps and some biomechanical aspects. Criteria and good validity values for jump counting are established. The reliability of the devices and the evidence is contradictory. IMUs are devices used in volleyball to count and measure vertical displacements and/or compare these measurements with the playing position, training or to determine the external load of the athletes. It has good validity measures, although inter-measurement reliability needs to be improved. Further studies are suggested to position IMUs as measuring instruments to analyze jumping and sport performance of players and teams.
... Position-derived evaluation using the global positioning system (GPS) and local positioning system (LPS) have been used to assess external physical loads in various competitive sports (Coutts and Duffield, 2010;Waldron et al., 2011;Cummins et al., 2013;Johnston et al., 2014;Wellman et al., 2016;Mujika, 2017;Linke et al., 2018). The travel distance, speed, and acceleration of the players were evaluated using time-series changes in the player's position (Johnston et al., 2018;Clemente et al., 2019). ...
Introduction: With the widespread use of wearable sensors, various methods to evaluate external physical loads using acceleration signals measured by inertial sensors in sporting activities have been proposed. Acceleration-derived external physical loads have been evaluated as a simple indicator, such as the mean or cumulative values of the target interval. However, such a conventional simplified indicator may not adequately represent the features of the external physical load in sporting activities involving various movement intensities. Therefore, we propose a method to evaluate the external physical load of tennis player based on the histogram of acceleration-derived signal obtained from wearable inertial sensors. Methods: Twenty-eight matches of 14 male collegiate players and 55 matches of 55 male middle-aged players wore sportswear-type wearable sensors during official tennis matches. The norm of the three-dimensional acceleration signal measured using the wearable sensor was smoothed, and the rest period (less than 0.3 G of at least 5 s) was excluded. Because the histogram of the processed acceleration signal showed a bimodal distribution, for example, high-and low-intensity peaks, a Gaussian mixture model was fitted to the histogram, and the model parameters were obtained to characterize the bimodal distribution of the acceleration signal for each player. Results: Among the obtained Gaussian mixture model parameters, the linear discrimination analysis revealed that the mean and standard deviation of the high-intensity side acceleration value accurately classified collegiate and middle-aged players with 93% accuracy; however, the conventional method (only the overall mean) showed less accurate classification results (63%). Conclusion: The mean and standard deviation of the high-intensity side extracted by the Gaussian mixture modeling is found to be the effective parameter representing the external physical load of tennis players. The histogram-based feature extraction of the acceleration-derived signal that exhibit multimodal distribution may provide a novel insight into monitoring external physical load in other sporting activities.
... Eight papers [147,153,154,159,[164][165][166]168] measured internal load. Investigations of physical demands during practices were reported by five papers [144,151,157,163,167], whereas another five papers focused on game demands [145,148,150,158]. Furthermore, data extracted from accelerometers were used to assess the injury risks [146,155,161,162]. ...
American football is the sport with the highest rates of concussion injuries. Biomedical engineering applications may support athletes in monitoring their injuries, evaluating the effectiveness of their equipment, and leading industrial research in this sport. This literature review aims to report on the applications of biomedical engineering research in American football, highlighting the main trends and gaps. The review followed the PRISMA guidelines and gathered a total of 1629 records from PubMed (n = 368), Web of Science (n = 665), and Scopus (n = 596). The records were analyzed, tabulated, and clustered in topics. In total, 112 studies were selected and divided by topic in the biomechanics of concussion (n = 55), biomechanics of footwear (n = 6), biomechanics of sport-related movements (n = 6), the aerodynamics of football and catch (n = 3), injury prediction (n = 8), heat monitoring of physiological parameters (n = 8), and monitoring of the training load (n = 25). The safety of players has fueled most of the research that has led to innovations in helmet and footwear design, as well as improvements in the understanding and prevention of injuries and heat monitoring. The other important motivator for research is the improvement of performance, which has led to the monitoring of training loads and catches, and studies on the aerodynamics of football. The main gaps found in the literature were regarding the monitoring of internal loads and the innovation of shoulder pads.
... The variability in outcomes may be due to the wide range of symptoms experienced by those with COVID-19 infection and the heterogeneity of the positions played by the athletes and their unique physical demands. For example, Defensive Backs experience fewer high-energy collisions but run more than any other position on defense, covering about 3 miles per game [13,14]. Given the endurance component of their position compared to other defensive positions, this may explain why this group saw a statistically significant decrease in the mean number of snaps per game after returning from COVID-19 infection while other positions did not. ...
Objective
The objective of this study was to assess whether the National Football League (NFL) players with probable coronavirus disease 2019 (COVID-19) during the 2020 season experienced a decline in athletic performance and endurance.
Methods
All players who were listed on the NFL’s COVID-19 Injury Reserve (COVID-IR) list were screened for inclusion. Players were included in the study if they had spent ≥10 days on the COVID-19 IR list (which indicated a positive PCR test based on the NFL COVID-19 policies), had played in at least two games before and after going on the IR list, and primarily played an offensive or defensive position. The mean number of snaps played per game and Pro Football Focus (PFF) score per game were collected for each athlete, which served as surrogate measures of endurance and performance, respectively. The results were analyzed with players grouped by position, and then all players grouped as a whole. Within-group comparisons were performed via t-tests.
Results
A total of 78 players met the criteria for inclusion in the study. The overall mean PFF score pre-COVID-19 infection was 62.15 (SD: 6.93), while it was 61.73 (SD: 7.42) post-COVID-19 infection, showing a decrease of 0.42 after infection (n=78, p=0.33). The mean number of snaps played per game pre-COVID-19 infection was 38.99 (SD: 16.46) while it was 38.10 (SD: 17.05) post-COVID-19 infection, showing a decrease of 0.89 after infection (n=78, p=0.30). When grouped by position, statistically significant differences were seen with Defensive Backs’ mean snaps played per game decreasing by 18.30 (n=6, p=0.03) and Defensive Linemen’s mean PFF score decreasing by 3.77 points (n=21, p=0.03).
Conclusion
Based on our findings, COVID-19 infection negatively impacted endurance in Defensive Backs, and performance in Defensive Linemen. However, there was inconclusive evidence to show whether COVID-19 infection negatively impacted other positions when analyzed separately or all positions when analyzed together. Further studies with more participants are needed to fully assess the effects of COVID-19 on performance and endurance in elite athletes.
... American football is a collision sport that requires significant fitness, strength, power, speed, and quickness. The physical profiles of American football players differ between positional groups (17,30) because each position has distinct performance demands within the game (39). Linemen (offensive and defensive) are typically more involved in activities such as blocking or tackling, which often occur at close range, while other positions (e.g., skill players) involve a combination of high-speed running, cutting, and blocking and tackling techniques. ...
We aimed to examine the annual changes in various physical characteristics of Japanese Division I (D1) Collegiate American footballers according to their positional groups. We measured body mass, and assessed performance in three gym tests (bench press, back squat, and power clean) and three field tests (40-yard dash, pro-agility shuttle, and broad jump) at each pre-season from 2014 to 2016 for players from a Japanese D1 university. Data from 55 players who completed ≥ 50% (three out of six) of the performance measurements in consecutive years were used in this analysis. Performance data across the two positional groups (skill players and linemen) were analyzed using pairwise t-tests to determine annual changes. The skill players’ body mass increased from their freshman to sophomore years (p < 0.05, Cohen’s d > 0.8), but not from their sophomore to junior or junior to senior years. The skill players’ 40-yard sprint time was shorter between all the annual comparisons (p < 0.05, d > 0.8). The linemen’s body mass increased from their freshman to sophomore years, and maintained from their sophomore to junior years and junior to senior years. There were significant improvements in strength and power outputs, but limited improvements in the pro-agility run and broad jump among most of the annual class comparisons for each positional group. These results indicate that annual improvements in the physical characteristics occur nonlinearly for Japanese D1 footballers. They will benefit from targeted strength and conditioning programs. However, the improvements of jumping and agility performances may be limited.
... Absolute Velocity Bands (Wellman et al., 2016) ...
This study sought to examine the differences between absolute and relative velocity bands for quantifying external volume during American football practice.
... American football is a team sport that requires specific physical attributes (height and weight) and advanced fitness levels in strength, power, speed and agility. In an American football game, each position has distinct performance demands [44] and physical profiles [16,36], which have shown to be key determinants of the potential risk factors of injury [16]. These physical attributes correlate to the competition level within each positional group, as highlighted in the National Football League (NFL) draft status [26] and recruit rankings from high school [12]. ...
PurposeTo compare anthropometric and physical performance profiles of Japanese 11th and 12th grade American football players within each positional group.Methods
Fifty-two 11th and 12th grade American football players from two Japanese high schools participated in the study during the summer pre-season period. They performed anthropometric (height and body mass) and physical (vertical jump, broad jump, 40-yard dash, pro-agility shuttle 4-kg medicine ball chest throw, front throw, and back throw) testing. Vertical jump momentum and 10-yard sprint momentum were also calculated by multiplying the velocity and body mass. Athletes were divided into two groups by playing positions: skill players and linemen.ResultsSkill players in the 12th grade were better at medicine ball chest throw (d = 0.73, P = 0.04) and vertical jump momentum (d = 0.75, P = 0.03) than those in the 11th grade. However, there were no differences in any measurements (P > 0.05) between linemen from the two grades.Conclusion
The current study suggests that upper and lower body absolute power and momentum production can be improved for skill players even over 17 years old. On the other hand, body size and speed, attributes that did not change between 11th and 12th grades, seem to be essential talent identification criteria in the current environment. Further study is needed to monitor longitudinal performance improvements in implementing talent development programs by focusing on the quality of speed, agility and power development at the youth level.
... These include throwing the ball, tackling the opponent with the ball, or preventing opposing team members from moving the ball down the field. These movements are typically carried out in rapid bursts called plays, during which injuries can occur due to the force exerted on joints and muscles [40]. ...
Injuries are a significant aspect of every sport, with the ability to impact a player’s career and the success of a team in their season. As sensor data is able to pick up on a player’s physical state, recently it has been analyzed for its ability to predict player injuries. We inspect the predictive power of player stats, subjective player responses, GPS data, and training load data in forecasting game injuries from an NCAA American football team during the 2019 season. Data processing techniques are used to remove noise and decrease correlated data, and as large portions of the data is missing, multiple methods of data interpolation are tested. Survey data and player stats have the most predictive power for injuries with GPS and training load data performing at near-random levels. Overall, when modeling player stats and survey data together, injury predictions had a precision of .47, recall of .74, and an F1 score of .52 significantly outperforming random guessing.
... After collecting total and high-speed running, they constructed a linear model to examine the impact of player characteristics. The authors in [71] used GPS to assess the physical demands of Division I College Football. Gentles et al. [26] studied a women's college soccer season in its entirety, which includes 17 matches and 24 practices. ...
For the past several decades, machine learning has played an important role in sports science with regard to player performance and result prediction. However, it is still challenging to quantify team-level game performance because there is no strong ground truth. Thus, a team cannot receive feedback in a standardized way. The aim of this study was twofold. First, we designed a metric called LAX-Score to quantify a collegiate lacrosse team's athletic performance. Next, we explored the relationship between our proposed metric and practice sensing features for performance enhancement. To derive the metric, we utilized feature selection and weighted regression. Then, the proposed metric was statistically validated on over 700 games from the last three seasons of NCAA Division I women's lacrosse. We also explored our biometric sensing dataset obtained from a collegiate team's athletes over the course of a season. We then identified the practice features that are most correlated with high-performance games. Our results indicate that LAX-Score provides insight into athletic performance beyond wins and losses. Moreover, though COVID-19 has stalled implementation, the collegiate team studied applied our feature outcomes to their practices, and the initial results look promising with regard to better performance.
... Football code training is characterised by multidirectional and intermittent bouts of high-intensity running and sprinting interspersed with bouts of moderate-and low-intensity activity (e.g., jogging, walking, and repositioning [158][159][160][161]). Therefore, although football code training may involve athletes repeatedly performing short sprints (e.g., 5-20 m, 2-3 s) during and between sport-specific actions [2,23,158,159,162], this most likely has limited or no very-high-speed or sprint threshold running [160,161,163]. Such training methods do not meet the recommendations that athletes be exposed to multiple sprints where they maximally accelerate to achieve and maintain V max with complete recovery between efforts to effectively enhance sprint performance [130]. ...
Background
Within the football codes, medium-distance (i.e., > 20 m and ≤ 40 m) and long-distance (i.e., > 40 m) sprint performance and maximum velocity sprinting are important capacities for success. Despite this, no research has identified the most effective training methods for enhancing medium- to long-distance sprint outcomes.
Objectives
This systematic review with meta-analysis aimed to (1) analyse the ability of different methods to enhance medium- to long-distance sprint performance outcomes (0–30 m, 0 to > 30 m, and the maximum sprinting velocity phase [ V max ]) within football code athletes and (2) identify how moderator variables (i.e., football code, sex, age, playing standard, phase of season) affected the training response.
Methods
We conducted a systematic search of electronic databases and performed a random-effects meta-analysis (within-group changes and pairwise between-group differences) to establish standardised mean differences (SMDs) with 95% confidence intervals and 95% prediction intervals. This identified the magnitude and direction of the individual training effects of intervention subgroups (sport only; primary, secondary, tertiary, and combined training methods) on medium- to long-distance sprint performance while considering moderator variables.
Results
In total, 60 studies met the inclusion criteria (26 with a sport-only control group), totalling 111 intervention groups and 1500 athletes. The within-group changes design reported significant performance improvements (small–moderate) between pre- and post-training for the combined, secondary (0–30 and 0 to > 30 m), and tertiary training methods (0–30 m). A significant moderate improvement was found in the V max phase performance only for tertiary training methods, with no significant effect found for sport only or primary training methods. The pairwise between-group differences design (experimental vs. control) reported favourable performance improvements (large SMD) for the combined (0 to > 30 m), primary ( V max phase), secondary (0–30 m), and tertiary methods (all outcomes) when compared with the sport-only control groups. Subgroup analysis showed that the significant differences between the meta-analysis designs consistently demonstrated a larger effect in the pairwise between-group differences than the within-group change. No individual training mode was found to be the most effective. Subgroup analysis identified that football code, age, and phase of season moderated the overall magnitude of training effects.
Conclusions
This review provides the first systematic review and meta-analysis of all sprint performance development methods exclusively in football code athletes. Secondary, tertiary, and combined training methods appeared to improve medium-long sprint performance of football code athletes. Tertiary training methods should be implemented to enhance V max phase performance. Nether sport-only nor primary training methods appeared to enhance medium to long sprint performance. Performance changes may be attributed to either adaptations specific to the acceleration or V max phases, or both, but not exclusively V max . Regardless of the population characteristics, sprint performance can be enhanced by increasing either the magnitude or the orientation of force an athlete can generate in the sprinting action, or both.
Trial Registration
OSF registration https://osf.io/kshqn/ .
... In invasion/combat sports such as rugby league, where general play is contested in tight confines, acceleration load is highest compared to other football codes, indicating the ability to rapidly change velocity is important to successful performance in this code [6,[9][10][11]. Similarly, in American football, where players are also actively trying to gain or negate yardage, skill players such as wide receivers, defensive backs and linebackers accumulate substantial counts of high accelerations (> 3.5 m s − 2 ) per game (range 26-38 counts per game) [13]. ...
Background
Wearable tracking devices are commonly utilised to quantify the external acceleration load of team sport athletes during training and competition. The ability to accelerate is an important attribute for athletes in many team sports. However, there are many different acceleration metrics that exist in team sport research. This review aimed to provide researchers and practitioners with a clear reporting framework on acceleration variables by outlining the different metrics and calculation processes that have been adopted to quantify acceleration loads in team sport research.
Methods
A systematic review of three electronic databases (CINAHL, MEDLINE, SPORTDiscus), was performed to identify peer-reviewed studies that published external acceleration load in elite team sports during training and/or competition. Articles published between January 2010 and April 2020 were identified using Boolean search phrases in relation to team sports (population), acceleration/deceleration (comparators), and competition and/or training (outcome). The included studies were required to present external acceleration and/or deceleration load (of any magnitude) from able-bodied athletes (mean age ≥ 18 years) via wearable technologies.
Results
A total of 124 research articles qualified for inclusion. In total, 113/124 studies utilised GPS/GNSS technology to outline the external acceleration load of athletes. Count-based metrics of acceleration were predominant of all metrics in this review (72%). There was a lack of information surrounding the calculation process of acceleration with 13% of studies specifying the filter used in the processing of athlete data, whilst 32% outlined the minimum effort duration (MED). Markers of GPS/GNSS data quality, including horizontal dilution of precision (HDOP) and the average number of satellites connected, were outlined in 24% and 27% of studies respectively.
Conclusions
Team sport research has predominantly quantified external acceleration load in training and competition with count-based metrics. Despite the influence of data filtering processes and MEDs upon acceleration, this information is largely omitted from team sport research. Future research that outlines acceleration load should present filtering processes, MEDs, HDOP, and the number of connected satellites. For GPS/GNSS systems, satellite planning tools should document evidence of available satellites for data collection to analyse tracking device performance. The development of a consistent acceleration filtering method should be established to promote consistency in the research of external athlete acceleration loads.
... Nonlinemen are comparatively leaner and more aerobically fit to facilitate greater running demands. 2,11 Anthropometric and lifestyle characteristics predispose linemen to a variety of health conditions 12-14 that may negatively impact autonomic regulation and their capacity to adapt to inseason demands. It has recently been demonstrated that linemen exhibit significantly slower interday HRV recovery than nonlinemen. ...
Purpose:
To track cardiac-autonomic functioning, indexed by heart-rate variability, in American college football players throughout a competitive period.
Methods:
Resting heart rate (RHR) and the natural logarithm root mean square of successive differences (LnRMSSD) were obtained throughout preseason and ∼3 times weekly leading up to the national championship among 8 linemen and 12 nonlinemen. Seated 1-minute recordings were performed via mobile device and standardized for time of day and proximity to training.
Results:
Relative to preseason, linemen exhibited suppressed LnRMSSD during camp-style preparation for the playoffs (P = .041, effect size [ES] = -1.01), the week of the national semifinal (P < .001, ES = -1.27), and the week of the national championship (P = .005, ES = -1.16). As a combined group, increases in RHR (P < .001) were observed at the same time points (nonlinemen ES = 0.48-0.59, linemen ES = 1.03-1.10). For all linemen, RHR trended upward (positive slopes, R2 = .02-.77) while LnRMSSD trended downward (negative slopes, R2 = .02-.62) throughout the season. Preseason to postseason changes in RHR (r = .50, P = .025) and LnRMSSD (r = -.68, P < .001) were associated with body mass.
Conclusions:
Heart-rate variability tracking revealed progressive autonomic imbalance in the lineman position group, with individual players showing suppressed values by midseason. Attenuated parasympathetic activation is a hallmark of impaired recovery and may contribute to cardiovascular maladaptations reported to occur in linemen following a competitive season. Thus, a descending pattern may serve as an easily identifiable red flag requiring attention from performance and medical staff.
... GPS very often contains a built in accelerometer. From these devices, training loads [4,5] are calculated and other metrics such as speed zones, accelerations, and impacts [5][6][7][8][9] are often reported. For internal load, sRPE is a common measure simply reported by the athlete [10] and has been used to extrapolate training load by multiplying sRPE and the duration of the training session (sRPE-TL). ...
The aim of this study is to explore the relationships between internal and external load measures in American football. Thirty football players wore a portable integrated monitor unit for 10 weeks during the fall football season. Relationships between internal and external load measurements were determined. Internal load consisted of heart rate zones and heart rate-derived measures and session Ratings of Perceived Exertion (sRPE). External load consisted of distance in different speed zones, total distance traveled, and accelerations. There were many significant positive relationships, but the meaningful relationships (r > 0.5) were between heart rate-derived measures of load (Training Impulse and heart rate reserve) and low-intensity movement and total distance. Only accelerations between 1 and 1.99 m·s −2 were moderately correlated to heart rate-derived internal load. RPE values alone did not correlate strong enough with any of the measure but sRPE training load (sRPE-TL) correlated to most external values. Overall, moderate correlations were present between heart rate-derived internal load to total distance and lower intensity movement. sRPE-TL values had high correlations but were highly dependent on duration, not perceived exertion. When addressing load in American football, duration of the session is a key component in determining internal load as HR data and sRPE alone do not correlate highly with external loads.
... Although the movement demands of training are typically below game demands, the football codes are characterised by multidirectional and intermittent bouts of high-intensity running and sprinting interspersed between bouts of moderate and low-intensity activity (e.g., jogging, walking and repositioning [222][223][224][225]). Although during training and match play football code athletes repeatedly perform short-sprints (e.g., 5-20 m, 2-3 s) during and in between sport-specific actions [12,222,223,226,227] athletes are exposed to limited or no very high-speed or sprint threshold running [224,225,228] and incomplete rests between sprints. Recommendations for improving sprint performance state that sprints should be at 95-100% max effort with complete recovery [201]. ...
Background
Short-sprint (≤ 20 m) performance is an important quality for success in the football codes. Therefore, developing an evidence base for understanding training methods to enhance short-sprint performance is key for practitioners. However, current systematic reviews are limited by (1) a lack of focus on football code athletes, (2) a lack of consideration of all training modalities and (3) a failure to account for the normal training practices undertaken by intervention groups within their analysis. Therefore, this review aimed to (1) conduct a systematic review of the scientific literature evaluating training interventions upon short-sprint performance within football code athletes, (2) undertake a meta-analysis to assess the magnitude of change of sport-sprint performance following training interventions and (3) identify how moderator variables affect the training response.
Methods
A systematic search of electronic databases was conducted. A random-effects meta-analysis was performed to establish standardised mean difference with 95% confidence intervals. This identified the magnitude and direction of the individual training effects of intervention subgroups (primary, secondary, combined-specific, tertiary and combined training methods) on short-sprint performance while considering moderator variables (i.e., football code, sex, age, playing standard, phase of season).
Results
121 studies met the inclusion criteria, totalling 3419 athletes. Significant improvements (small-large) were found between pre- and post-training in short-sprint performance for the combined, secondary, tertiary and combined-specific training methods. No significant effect was found for primary or sport only training. No individual mode was found to be the most effective. Between-subgroup analysis identified that football code, age, playing standard and phase of season all moderated the overall magnitude of training effects.
Conclusions
This review provides the largest systematic review and meta-analysis of short-sprint performance development methods and the only one to assess football code athletes exclusively. Practitioners can apply combined, secondary and tertiary training methods to improve short-sprint performance within football code athletes. The application of sport only and primary methods does not appear to improve short-sprint performance. Regardless of the population characteristics, short-sprint performance can be enhanced by increasing either or both the magnitude and the orientation of force an athlete can generate in the sprinting action.
... Over time, a variety of systems and methods have been utilised in the TMA of athletes from a broad range of team field sports, including football (i.e., soccer) (21)(22)(23)(24), Australian football (25)(26)(27)(28)(29), American football (30)(31)(32), Gaelic football (33)(34)(35), cricket (36)(37)(38), field hockey (39)(40)(41)(42)(43), rugby union (44)(45)(46)(47), and rugby league (8,9,11,20,48). Initially, TMA of team field sports was a tedious task, involving direct observation of live match-play coupled with pen and paper notational analysis (25,49). ...
A variety of time-motion analysis methodologies have assisted practitioners objectively quantify the physical demands of both rugby league match-play and training. This narrative review focuses on both the evolution of time-motion analysis and its role in team field sports, as well as summarise and compare rugby league match-play and training data. Four
electronic databases (CINAHL, Medline, Scopus, and SPORTDiscus) were searched from the earliest record to December 2019. 124 studies met the eligibility criteria and reported on the use of time-motion analysis in team field sports, in particularly, throughout rugby league match-play and training at an elite, semi-elite, amateur, and junior playing standard. This review demonstrated that training drills utilised to prepare rugby league athletes for the physical demands of match-play may not meet or exceed required demands. For instance, skill-based and speed and agility/repeated high intensity effort drills often fail to elicit match-play thresholds for physical demands such as absolute distance, speed, high-, very-high-speed, and sprint activity, as well as collisions and impacts. The strength and conditioning coach as well as sport scientist can utilise the data and findings presented within this review to increase the specificity of subsequent training methodologies. That is, if the aim of the training session is to replicate and/or overload match-play intensities, conventional training methodologies such as traditional conditioning drills and small-sided games are a more appropriate stimulus.
... In team sports that involve collisions, such as (a) rugby union (11,40,50), (b) rugby league (12,21,34), and (c) Australian Football (5,6,9,59), wearable microtechnologies have become an integral part of sport performance analysis (5). As stated previously, only a few studies are currently available in the literature documenting their use in American football (47,(52)(53)(54)(55) and one in Canadian football (8). Obstacles remain in the implementation and use of wearable microtechnology. ...
Coaches are encouraged to quantify and monitor the training loads (TL) of athletes in order to optimize performance
while also minimising the risk of injury by making proper adjustments to training when deemed necessary. This case
study documents the process of monitoring the TL of Canadian university student-athletes during the 2017 season and
assesses its application from a coach and athletic performance perspective. Session-RPE TL and acute:chronic
workload ratios (ACWR) were collected daily. Weekly meetings with the coaches allowed the graphical presentation of
the data and discussions about how these were situated in the context of the team’s activities. An increase in TL was
observed during the first three weeks of the season as a consequence of training camp (average weekly TL of 3001,
2939 and 2877 arbitrary units (AU) on offense, defence and special teams respectively during that period), resulting in
an increase in fatigue and potential injury risk (ACWR of 1.86, 1.9, 1.39; 1.67, 1.71, 1.38; and 1.76, 1.80, 1.38). Such
practice goes against what is considered ‘best practice’ when it comes to developing the competition schedule in
university football. TL and ACWR progressively decreased over the following weeks of the regular season (average
weekly TL of 1775, 1550 and 1426 AU for the last three weeks of the season) to promote recovery while potentially
maintaining the physiological adaptations obtained from training. From a coaching perspective, having access to TL
data can help coaches engage in a reflective process about their practice and their experience. This can allow coaches
to contextualise their decisions, provide support or the opportunity to question their coaching practice and thus better
support experiential learning.
... GNSS-based methods require the attachment of a device to the body to track the player. These methods are frequently used in sports where games are played in large outdoor fields such as American football (19) and soccer. (20) Catapult PLAYERTEK (21) can analyze players' mileage, play area, and accuracy of formation from the data obtained by tracking their location information in the game, and it can also be used for tactics. ...
In the field of sports, there are increasing opportunities to use inertial measurement units (IMUs) to enhance the training process and improve the performance of athletes. We focus on kendo, a traditional martial art using shinai (bamboo swords) in Japan, and propose methods for detecting and recognizing strike activities using IMUs towards realizing a kendo skill improvement support system. We used a sensor data set of strike activities obtained from 14 participants (seven kendo-experienced and seven inexperienced persons). We attached four IMUs to the participants’ right wrist, waist, and shinai (tsuba and saki-gawa). First, to detect the strike activity, we calculated the dynamic time warping (DTW) distance between the training data and the time series data, and detected the strike activity sections. The proposed method detected strike activities with a high accuracy of 95.0%. Next, to recognize the strike activity, we recognized five types (Center-Men, Right-Men, Left-Men, Dō, and Kote). In the person-dependent (PD) case, we achieved an accuracy of 89.5% using data of the right wrist. In the person-independent (PI) case, we achieved an accuracy of 54.9% using IMUs attached to the three positions. These results clarified the points to be improved in the proposed method to realize the support system.
... Thus, many investigations have analyzed the capacity of these systems to evaluate conditional variables in training sessions to improve performance or avoid injuries [14,15]. In addition, recent studies are quantifying these variables in match situations [13,16,17] but, to date, we have no knowledge of studies that have compared VID and GPS data in official matches. ...
The aim of this study was to compare the agreement of the movement demands data during a soccer match (total distance, distance per minute, average speed, maximum speed and distance covered in different speed sectors) between an optical tracking system (Mediacoach System) and a GPS device (Wimu Pro). Participants were twenty-six male professional soccer players (age: 21.65 ± 2.03 years; height: 180.00 ± 7.47 cm; weight: 73.81 ± 5.65 kg) from FC Barcelona B, of whom were recorded a total of 759 measurements during 38 official matches in the Spanish second division. The Mediacoach System and the Wimu Pro were compared using the standardized mean bias, standard error of estimate, intraclass correlation coefficients (ICC), coefficient of variation (%), and the regression equation to estimate data for each variable. In terms of agreement between systems, the magnitude of the ICC was almost perfect (> 0.90-1.00) for all variables analyzed. The coefficient of the variations between devices was close to zero (< 5%) for total distance, distance per minute, average speed, maximum speed, and walking and jogging, and between 9% and 15% for running, intense running, and sprinting at low and at high intensities. It can be observed that, compared to Wimu Pro the Mediacoach System slightly overestimated all the variables analyzed except for average speed, maximum speed, and walking variables. In conclusion, both systems can be used, and the information they provide in the analyzed variables can be interchanged, with the benefits implied for practitioners and researchers.
... 29 In another study, GPS sensors and related analytics were used by National Collegiate Athletic Association (NCAA) Division I Football athletes to record workload, velocity, distance, and acceleration during both practices and games. 48,50 The studies found significant variation in movement profiles among collegiate football players and the authors identified the need for position-specific and game-specific physical conditioning strategies to maximize player performance, limit the effects of fatigue, and minimize the onset of injuries. The combination of the internal and external workloads of the athlete determine the training outcome. ...
The convergence of semiconductor technology, physiology, and predictive health analytics from wearable devices has advanced its clinical and translational utility for sports. The detection and subsequent application of metrics pertinent to and indicative of the physical performance, physiological status, biochemical composition, and mental alertness of the athlete has been shown to reduce the risk of injuries and improve performance and has enabled the development of athlete-centered protocols and treatment plans by team physicians and trainers. Our discussions in this review include commercially available devices, as well as those described in scientific literature to provide an understanding of wearable sensors for sports medicine. The primary objective of this paper is to provide a comprehensive review of the applications of wearable technology for assessing the biomechanical and physiological parameters of the athlete. A secondary objective of this paper is to identify collaborative research opportunities among academic research groups, sports medicine health clinics, and sports team performance programs to further the utility of this technology to assist in the return-to-play for athletes across various sporting domains. A companion paper discusses the use of wearables to monitor the biochemical profile and mental acuity of the athlete.
On behalf of the Strength and Conditioning Society (SCS) and the Nucleus of High Performance in Sport (NAR), we are pleased to present the abstracts of the SCS 5th Annual Conference, which, for the first time, took place outside of Europe. The event was held at NAR’s state-of-the-art facilities in São Paulo, Brazil, on 3–5 November 2022, and comprised several invited sessions from international and national speakers on a variety of topics related to strength and conditioning practices and their application to health, injury prevention and sports performance. These included strength training in high-performance sports and older adults, sleep and recovery in elite athletes, performance optimization of the female athlete, high-intensity interval training, velocity-based resistance training, and running and cycling biomechanics, among others. The Conference also included different practical workshops conducted by renowned academics and practitioners on post-competition recovery strategies, plyometric training, hamstring strain injuries in soccer, and resisted sprint training. Finally, the event disseminated up-to-date strength and conditioning research by providing practitioners and researchers with the opportunity to present their most recent findings. In this regard, all abstracts of the communications presented at the SCS 5th Annual Conference can be found in this Conference Report.
Purpose:
To assess objective strain and subjective muscle soreness in "Bigs" (offensive and defensive line), "Combos" (tight ends, quarterbacks, line backers, and running backs), and "Skills" (wide receivers and defensive backs) in American college football players during off-season, fall camp, and in-season phases.
Methods:
Twenty-three male players were assessed once weekly (3-wk off-season, 4-wk fall camp, and 3-wk in-season) for hydroperoxides (free oxygen radical test [FORT]), antioxidant capacity (free oxygen radical defense test [FORD]), oxidative stress index (OSI), countermovement-jump flight time, Reactive Strength Index (RSI) modified, and subjective soreness. Linear mixed models analyzed the effect of a 2-within-subject-SD change between predictor and dependent variables.
Results:
Compared to fall camp and in-season phases, off-season FORT (P ≤ .001 and <.001), FORD (P ≤ .001 and <.001), OSI (P ≤ .001 and <.001), flight time (P ≤ .001 and <.001), RSI modified (P ≤ .001 and <.001), and soreness (P ≤ .001 and <.001) were higher for "Bigs," whereas FORT (P ≤ .001 and <.001) and OSI (P = .02 and <.001) were lower for "Combos." FORT was higher for "Bigs" compared to "Combos" in all phases (P ≤ .001, .02, and .01). FORD was higher for "Skills" compared with "Bigs" in off-season (P = .02) and "Combos" in-season (P = .01). OSI was higher for "Bigs" compared with "Combos" (P ≤ .001) and "Skills" (P = .01) during off-season and to "Combos" in-season (P ≤ .001). Flight time was higher for "Skills" in fall camp compared with "Bigs" (P = .04) and to "Combos" in-season (P = .01). RSI modified was higher for "Skills" during off-season compared with "Bigs" (P = .02) and "Combos" during fall camp (P = .03), and in-season (P = .03).
Conclusion:
Off-season American college football training resulted in higher objective strain and subjective muscle soreness in "Bigs" compared with fall camp and during in-season compared with "Combos" and "Skills" players.
Objectives:
The primary aim was to establish normative values of isometric plantarflexor muscle strength in professional male rugby union players and compare forwards with backs. The secondary aims were to examine how individual playing position or age influences isometric plantarflexor strength.
Design:
Cross-sectional.
Setting:
Testing at professional rugby clubs.
Participants:
355 players (201 forwards and 154 backs) from 9 clubs in the English Premiership club competition.
Main outcome measures:
Maximal unilateral isometric plantarflexion strength was measured, using a Fysiometer C-Station, in a seated position with a flexed knee and in maximal available dorsiflexion. Values are reported normalised to body mass and specific to playing position.
Results:
Mean combined limb isometric plantarflexion strength for the group was 193.1 kg (SD 32) or 1.86 xBW. (SD 0.31). Forwards were significantly weaker than backs (forwards = 1.75xBW (SD 0.26), backs = 2.00xBW (SD 0.28) (p=<0.0001)). Age category revealed no influence on plantarflexor strength.
Conclusion:
This study presents normative isometric plantarflexion strength values for professional male rugby union players. Forwards are typically relatively weaker than backs.
Head impacts and physical exertion are ubiquitous in American football, but the relationship between these factors is poorly understood across a competitive season or even within an individual session. Gameplay characteristics, including player position and session type, may contribute to these relationships but have not been prospectively examined. The current study aimed to determine if an association exists between head impact biomechanics and physical load metrics. We prospectively studied college football players during the 2017–2021 football seasons across representative playing positions (15 offensive and defensive linemen, 11 linebackers and tight ends, and 15 defensive backs, running backs, and receivers). Participants wore halters embedded with Catapult Vector GPS monitoring systems to quantify player load and participant helmets were equipped with the Head Impact Telemetry System to quantify head impact biomechanics and repetitive head impact exposure (RHIE). Generalized linear models and linear regression models were employed to analyze in-session and season-long outcomes, while addressing factors such as player position and session type on our data. Player load was associated with RHIE (p < 0.001). Season-long player load predicted season-long RHIE (R2 = 0.31; p < 0.001). Position group affected in-session player load (p = 0.025). Both player load and RHIE were greater in games than in practices (p < 0.001), and position group did not affect RHIE (p = 0.343). Physical load burden was associated with RHIE within sessions and across an entire season. Session type affected both RHIE and player load, while position group only affected player load. Our data point to tracking physical load burden as a potential proxy for monitoring anticipated RHIE during the season.
The application of acceleration and deceleration data as a measure of an athlete's physical performance is common practice in team sports. Acceleration and deceleration are monitored with athlete tracking technologies during training and games to quantify training load, prevent injury and enhance performance. However, inconsistencies exist throughout the literature in the reported methodological procedures used to quantify acceleration and deceleration. The object of this review was to systematically map and provide a summary of the methodological procedures being used on acceleration and deceleration data obtained from athlete tracking technologies in team sports and describe the applications of the data. Systematic searches of multiple databases were undertaken. To be included, studies must have investigated full body acceleration and/or deceleration data of athlete tracking technologies. The search identified 276 eligible studies. Most studies (60%) did not provide information on how the data was derived and what sequence of steps were taken to clean the data. Acceleration and deceleration data were commonly applied to quantify and describe movement demands using effort metrics. This scoping review identified research gaps in the methodological procedures and deriving and cleaning techniques that warrant future research focussing on their effect on acceleration and deceleration data.
Davis, JK, Wolfe, AS, Basham, SA, Freese, EC, and De Chavez, PJD. Neuromuscular, endocrine, and perceptual recovery after a youth American football game. J Strength Cond Res 35(5): 1317-1325, 2021-American football is a high-intensity intermittent sport consisting of various movements and repeated collisions which highlights the importance of adequate recovery from a game to prepare for the next competition. Therefore, the purpose of this study was to determine the time course of recovery markers after a youth American football game. Thirteen male American football youth players were monitored for 7 days after a single football game. Baseline measures were taken 28 hours pregame for lower-body neuromuscular function by countermovement jumps (CMJs) to determine peak power (PP), jump height (JH), flight time (FT), and takeoff velocity (TOV). Saliva was analyzed for cortisol, testosterone, and C-reactive protein (CRP). Perceptual recovery was assessed by the modified profile of mood states (POMS), perceived recovery status (PRS), and a daily wellness questionnaire. These measures were repeated immediately postgame (30 minutes) and at 20, 44, 68, 92, 116, and 140 hours postgame. Compared with baseline values, there was a significant decrease (p < 0.05) in CMJ PP, JH, and TOV up to 68 hours postgame and FT 44 hours postgame. No significant difference existed among time points for salivary testosterone and CRP. Cortisol levels significantly increased postgame compared with baseline (p < 0.05). Total mood disturbance, assessed by POMS, and daily wellness markers for energy were significantly decreased (p < 0.05), whereas daily wellness markers for soreness were significantly increased (p < 0.05) immediately after the game. Players exhibited a significant decrease in PRS up to 44 hours postgame (p < 0.05), similar to the decrease in neuromuscular function. Neuromuscular function and PRS are impaired for up to 44-68 h postgame.
Sprinting and speed is a fundamental skill and physical attribute crucial in seam bowlers and batters within cricket. The aim of this study was to assess differences in mechanical properties during sprinting between youth and senior international cricketers and between seam bowlers and batters. Retrospective 40 m sprint times and anthropometric measures of 56 international cricketers (19 senior seam bowlers, 7 under-19 seam bowlers, 16 senior batters, 14 under-19 batters) were used to calculate the theoretical maximal force (F 0 ), theoretical maximal velocity (V (0) ), theoretical maximal power (P max ), slope of the force-velocity relationship (F-V slope), maximal ratio of horizontal-to-resultant force (RF max ), decrease in the ratio of horizontal-to-resultant force (DRF) and optimum velocity (V opt ). There were no significant (P > 0.05) differences in sprint times nor sprint mechanical profile variables between position or age. However, there was a moderately greater F 0 (N/Kg) (ES = 0.78; 90% CI 0.19–1.34) and RF max (ES = 0.75; 90% CI 0.11–1.35) in senior seam bowlers when compared to batters. Furthermore, FV Slope (ES = 0.79; 90% CI 0.15–1.40) and DRF (ES = 0.75; 90% CI 0.11–1.35) were moderately greater in senior compared to under-19 batters. When expressed relative to body mass, it appears that senior international seam bowlers show trends towards a more force biased profile during sprinting when compared to batters. These findings will help coaches to optimise physical preparation strategies in youth and senior international cricketers.
Zabriskie, HA, Dobrosielski, DA, Leppert, KM, Droege, AJ, Knuth, ND, and Lisman, PJ. Positional analysis of body composition using dual-energy X-ray absorptiometry in National Collegiate Athletic Association Division I football and men's lacrosse. J Strength Cond Res XX(X): 000-000, 2020-Despite the widespread use of dual-energy X-ray absorptiometry (DXA), few studies have examined differences in body composition between positions within sports and none have reported DXA-derived body composition reference values for men's lacrosse. The purpose of this study was to examine differences in measures of total and regional body composition and bone mineral density (BMD) using DXA across sport positions in a large cohort of National Collegiate Athletic Association Division I male lacrosse and football players. A total of 294 male athletes (football, n = 196; lacrosse, n = 98) underwent DXA. One-way analysis of variance or Kruskal-Wallis tests were used to examine whether body composition variables differed by sports position. In football, position was a significant determinant for every compositional variable in football athletes (all, p < 0.05; effect size range = 0.24-0.79). Offensive linemen had the highest total body fat percentage (30.1 ± 2.9%), followed by fullbacks (26.7 ± 3.3%) and defensive linemen (24.6 ± 5.7%); wide receivers had the lowest (14.5 ± 2.1%). For total body BMD, defensive linemen had the highest (1.70 ± 0.09 g·cm), followed by linebackers (1.67 ± 0.09 g·cm) and offensive linemen (1.65 ± 0.09 g·cm); kickers had the lowest (1.45 ± 0.11 g·cm) BMD. In lacrosse, no differences were found between positions for any total or regional body composition and BMD measure (all, p > 0.05). Our data confirm that total and regional measures of body composition and BMD vary across positions in football but not in men's lacrosse. Unlike football, similarities in body composition among lacrosse players may indicate that the uniformity of training demands or preferred player attributes in team selection outweigh the unique positional demands in gameplay.
Kildow, AR, Wright, G, Reh, RM, Jaime, S, and Doberstein, S. Can monitoring training load deter performance drop-off during off-season training in Division III American football players? J Strength Cond Res XX(X): 000-000, 2019-The primary aim of this observational investigation was to monitor performance of Division III American football players during off-season training while the secondary aim was to investigate differences in training adaptations between linemen and nonline players. Twenty-three subjects from the university's football team were recruited from an Exercise Science 100 conditioning class to participate in a 15-week off-season training program. Phase I consisted of concurrent strength and speed/endurance training (3-4 d·wk) for 7 weeks. Phase II consisted of strength training and spring football practice (3-4 d·wk) for 4 weeks. Countermovement jump, estimated one repetition maximum (1RM) bench press and back squat, 505 change of direction (COD), repeated 30-yard anaerobic sprint test (RAST), and body mass were all measured Pre, Mid, and Post training program. Two-way analysis of variance with repeated measures revealed no significant interaction between linemen and nonline players for all performance variables (p > 0.05). Over the course of the study, RSAT % decrement, 505 COD times, and estimated 1RM performance for bench and squat significantly improved (p ≤ 0.05). No significant changes were detected in CMJ, RSAT best time, or body mass. Results indicate that linemen and non-line players did not respond significantly different to the present training program. The 15-week training program produced improvements in COD skill, speed, anaerobic capacity, and muscular strength. Furthermore, all performance changes were maintained through the end of the study. Data from this study indicate that monitoring training load can give feedback to help augment performance and prevent performance decrements during the off-season.
Planifier et réguler quotidiennement l’entrainement sont deux opérations importantes
du savoir pratique des entraineurs. Dans la pratique du sport de manière compétitive,
l’atteinte d’une performance optimale requiert l’intégration, l’optimisation et la
synchronisation de nombreux éléments qui composent la performance sportive.
L’entraineur sportif agit comme le « chef de projet performance » autour de qui
s’articule le processus d’entrainement d’athlètes dans des sports individuels et dans
des sports collectifs. Pour prendre en compte la variabilité des réponses
interindividuelles des athlètes, il est recommandé que l’entraineur entreprenne une
démarche de régulation de l’entrainement en quantifiant notamment la charge
d’entrainement, un construit qui comprend, entre autres, les stimuli d’entrainement
(charge externe) et la réponse de l’organisme à ces dits stimuli (charge interne). Les
outils à la disposition de l’entraineur se regroupent en trois principales catégories,
chacune possédant ses avantages et ses limites. L’intérêt et la pertinence de ce projet
doctoral résident toutefois dans l’utilisation de la part de l’entraineur de ces données
de la charge d’entrainement afin de faciliter la pratique réflexive. En récoltant a priori
les données de la charge d’entrainement auprès d’étudiants-athlètes en football
universitaire québécois, il sera possible d’étudier le processus réflexif et décisionnel
de l’entraineur au cours de ses actions de programmation et de régulation des activités
technico-tactiques et à la suite des matchs pendant une saison de compétition. Grâce à
des techniques fortement influencées par la recherche dans le domaine de l’éducation,
cette recherche s’intéresse non seulement aux actions des entraineurs, mais également
à leurs réflexions. Ainsi, les techniques du rappel stimulé, de la réflexion partagée et
de la verbalisation concourante, triangulées avec des d’autres données obtenues via
l’utilisation de cartes réflexives et d’observations sur le terrain, permettront de
recueillir, au cours d’entretiens semi-dirigés, de l’information de nature qualitative
qui facilitera la compréhension d’un phénomène d’intérêt, soit le processus
dynamique, interactionniste et complexe qu’est le coaching sportif dans le contexte
d’un sport d’équipe, soit le football universitaire québécois. Les résultats témoignent
de l’utilité d’un outil subjectif de quantification de la charge d’entrainement pour
gérer de nouvelles « informations émergentes » et susciter des réflexions diverses de
la part des participants-entraineurs. Cette étude démontre que l’utilisation d’une
méthode subjective de quantification de la charge d’entrainement permet de récolter
de manière systématique des informations pertinentes sur le dosage et la réponse de
l’organisme aux diverses activités d’entrainement de la part des étudiants-athlètes,
permettant ensuite aux entraineurs sportifs de démontrer des caractéristiques d’une
pratique réflexive contextualisée aux exigences particulières du contexte du football
universitaire.
Advances in sports performance analysis technologies such
as portable global positioning system (GPS) and integrated
accelerometry have enabled investigators to accurately quantify
the demands of competitive match-play in contact sports such as
Rugby Union - The aim of the present study was i) to examine the
physiological demands of competitive Super 15 Rugby match-play
using portable Global Positioning Systems (GPS) and integrated
accelerometry to monitor the demands of match-play and ii) examine
positional comparisons to determine if a player’s physiological
requirements are influenced by their playing position during Super
15 Rugby competition. Five elite male Rugby Union players were
monitored during eleven regular season competition matches using
portable GPS and integrated accelerometry. There was a significant
(p>0.05) difference in the total and relative distance travelled and
between backs and forwards during match-play. Backs achieved
greater maximum running speed, completed a greater number
of sprints, had greater time between sprints, and covered more
distance sprinting than forwards. Forwards experienced significantly
(p>0.05) more total impacts than backs during match-play while the
number of impacts recorded in zone 4 (7.1-8.0 G), zone 5 (8.1-10.0
G) and zone 6 (≥ 10.1 G) were significantly (p>0.05) greater for
forwards than backs. The present study provides insight into the
variation in positional demands between forwards and backs and
the intense physical nature of Super 15 Rugby Union match-play.
These data may assist coaching and performance staff to develop
and implement individualised and position specific training regimes
to optimise on-field performance.
Rugby league is a team sport in which players engage in repeated high-intensity exercise involving frequent collisions. Recent research, much of which has involved global positioning system (GPS) technology, has provided coaches and sport scientists with a deeper understanding of match demands, particularly at the elite level. This has allowed for the development of training programmes that prepare players for the most intense contact and running demands likely to be experienced in competition. At the elite level, rugby league players have well-developed aerobic and anaerobic endurance, muscular strength and power, reactive agility, and speed. Upper- and lower-body strength and aerobic power are associated with a broad range of technical and sport-specific skills, in addition to a lower risk of injury. Significant muscle damage (as estimated from creatine kinase concentrations) and fatigue occurs as a result of match-play; while muscle function and perceptual fatigue generally return to baseline 48 h following competition, increases in plasma concentrations of creatine kinase can last for up to 5 days post-match. Well-developed physical qualities may minimise post-match fatigue and facilitate recovery. Ultimately, the literature highlights that players require a broad range of physical and technical skills developed through specific training. This review evaluates the demands of the modern game, drawing on research that has used GPS technology. These findings highlight that preparing players based on the average demands of competition is likely to leave them underprepared for the most demanding passages of play. As such, coaches should incorporate drills that replicate the most intense repeated high-intensity demands of competition in order to prepare players for the worst-case scenarios expected during match-play.
The purpose of this study was to assess the validity and inter-unit reliability of 10 Hz (Catapult) and 15 Hz (GPSports) GPS units and investigate the differences between these units as measures of team sport athlete movement demands. A team sport simulation circuit was completed by eight trained male participants. The movement demands examined included: total distance covered (TD), average peak speed and the distance covered, time spent and number of efforts performed low speed running (0.00-13.99 km·h), high speed running (14.00-19.99 km·h) and very-high speed running (>20.00 km·h). The degree of difference between the 10 Hz and 15 Hz GPS units, as well as validity was assessed using a paired samples t-test. Pearson's correlations were also used for validity assessment. Inter-unit reliability was established using percentage typical error of measurement and intra-class correlations. The findings revealed that 10 Hz GPS units were a valid (p>0.05) and reliable (%TEM=1.3%) measure of TD. In contrast, the 15 Hz GPS units exhibited lower validity for TD and average peak speed. Further, as the speed of movement increased the level of error for the 10 Hz and 15 Hz GPS units increased (%TEM=0.8-19.9). The findings from this study suggest that comparisons should not be undertaken between 10 Hz and 15 Hz GPS units. In general, the 10 Hz GPS units measured movement demands with greater validity and inter-unit reliability than the 15 Hz units, however both 10 Hz and 15 Hz units provided improved measures of movement demands in comparison to 1 Hz and 5 Hz GPS units.
Rugby sevens is a rapidly growing sport. Match analysis is increasingly being used by sport scientists and coaches to improve the understanding of the physical demands of this sport. This study investigated the physical and physiological demands of elite men's rugby sevens, with special reference to the temporal patterns of fatigue during match-play. Nine players, four backs and five forwards (age 25.1±3.1 yrs) participated during two "Roma 7" international tournaments (2010 and 2011). All players were professional level in the highest Italian rugby union, and five of these players also competed at the international level. During the matches (n=15) players were filmed in order to assess game performance. Global positioning system (GPS), heart rate (HR), and blood lactate (BLa) concentration data were measured and analyzed. The mean total distance covered throughout matches was 1221±118m (first half = 643±70m and second half = 578±77m; with a decrease of 11.2%, p>0.05, Effect Size = 0.29). Players achieved 88.3±4.2% and 87.7±3.4% of HR max during the first and second half, respectively. The BLa for the first and second half was 3.9±0.9 mmol·L and 11.2±1.4 mmol·L, respectively. The decreases in performance occurred consistently in the final 3 minutes of the matches (-40.5% in distance covered per minute). The difference found in relation to the playing position, although not statistically significant (p=0.11), showed a large ES (η=0.20), suggesting possible practical implications. These results demonstrate that rugby sevens is a demanding sport that places stress on both the anaerobic glycolytic and aerobic oxidative energy systems. Strength and conditioning programs designed to train these energy pathways may prevent fatigue-induced reductions in physical performance.
Time-motion data was used to classify a selection of training drills. Ten midfielders (age=23.8±1.8yr; height=183.9±3.8cm; mass=83.2±5.0 kg) from an Australian Football League team participated in 17 training drills and four quarters of an official competitive match. Heart rate and time-motion data were collected using Global Positioning and Heart Rate Systems. Cluster analysis of mean distance travelled in the seven velocity zones identified three clusters: 1) game-specific conditioning; 2) skill refining/moderate intensity dominant; and 3) skill refining/low intensity dominant. Differences between the three clusters in distance travelled at the speed zones were confirmed using one-way ANOVA. Differences between clusters were also assessed for number of efforts in velocity zones and percentage time in heart rate zones. When compared to drills with a focus on skill refining or performed on a reduced playing area, drills utilising the entire playing field better replicated the movement characteristics of competitive game play.
Abstract The purpose of this investigation was to quantify the movement characteristics of elite rugby union players during competitive play and identify whether position-related differences exist. Ninety-eight elite players from eight English Premiership Clubs were tracked using global positioning systems (GPS) during 44 competitive matches throughout the 2010/2011 season. Player positions were defined as: (1) Backs or Forwards; (2) Front, Second and Back Rows, Scrum Half, Inside and Outside Backs; (3) 15 individual positions (numbers 1-15). Analysis revealed the game is predominantly played at low speeds with little distance covered 'sprinting' by either the Backs (50 ± 76 m) or the Forwards (37 ± 64 m). The Backs travelled greater (P < 0.05) absolute and relative distances than the Forwards. The Scrum Half covered the greatest total distance during a match (7098 ± 778 m) and the Front Row the least (5158 ± 200 m). The Back Row covered the greatest distances at 'sprinting' speeds, particularly the number 8 position (77 m). These findings reflect notable differences in the movement characteristics displayed by elite rugby union players in specific positional roles, and reinforce the contemporary view that training programmes for such players ought to be structured with this in mind.
To investigate the physical demands of professional rugby league match-play using microtechnology, and to compare these demands with typical training activities used to prepare players for competition.
Prospective cohort study.
Thirty elite rugby league players participated in this study. Seven hundred and eighty-six. training data sets and 104 data sets from National Rugby League matches were collected over one playing season. Movement was recorded using a commercially available microtechnology unit (minimaxX, Catapult Innovations), which provided information on speeds, distances, accelerations, physical collisions and repeated high-intensity efforts.
Mean distances covered during match-play by the hit-up forwards, wide-running forwards, adjustables, and outside backs were 3,569 m, 5,561 m, 6,411 m, and 6,819 m, respectively. Hit-up forwards and wide-running forwards were engaged in a greater number of moderate and heavy collisions than the adjustables and outside backs, and more repeated high-intensity effort bouts per minute of play (1 bout every 4.8-6.3 min). The physical demands of traditional conditioning, repeated high-intensity effort exercise, and skill training activities were all lower than the physical demands of competition.
These results demonstrate that absolute distances covered during professional rugby league matches are greater for outside backs, while the collision and repeated high-intensity effort demands are higher for hit-up forwards and wide-running forwards. The specific physical demands of competitive play, especially those demands associated with collisions and repeated high-intensity efforts, were not well matched by those observed in traditional conditioning, repeated high-intensity effort exercise, and skills training activities. Further research is required to investigate whether modifications need to be made to these training activities to better prepare players for the demands of National Rugby League competition.
The validity and reliability of three commercial global positioning system (GPS) units (MinimaxX, Catapult, Australia; SPI-10, SPI-Pro, GPSports, Australia) were quantified.
Twenty trials of cricket-specific locomotion patterns and distances (walking 8800 m, jogging 2400 m, running 1200 m, striding 600 m, sprinting 20- to 40-m intervals, and run-a-three) were compared against criterion measures (400-m athletic track, electronic timing). Validity was quantified with the standard error of the estimate (SEE) and reliability estimated using typical error expressed as a coefficient of variation.
The validity (mean +/- 90% confidence limits) for locomotion patterns walking to striding ranged from 0.4 +/- 0.1 to 3.8 +/- 1.4%, whereas for sprinting distances over 20 to 40 m including run-a-three (approx. 50 m) the SEE ranged from 2.6 +/- 1.0 to 23.8 +/- 8.8%. The reliability (expressed as mean [90% confidence limits]) of estimating distance traveled by walking to striding ranged from 0.3 (0.2 to 0.4) to 2.9% (2.3 to 4.0). Similarly, mean reliability of estimating different sprinting distances over 20 to 40 m ranged from 2.0 (1.6 to 2.8) to 30.0% (23.2 to 43.3).
The accuracy and bias was dependent on the GPS brand employed. Commercially available GPS units have acceptable validity and reliability for estimating longer distances (600-8800 m) in walking to striding, but require further development for shorter cricket-specific sprinting distances.
Global positioning system (GPS) monitoring of movement patterns is widespread in elite football including the Australian Football League (AFL). However documented analysis of this activity is lacking. We quantified the movement patterns of AFL football and differences between nomadic (midfield), forward and defender playing positions, and determined whether the physical demands have increased over a four season period. Selected premiership games were monitored during the 2005 (n=80 game files), 2006 (n=244), 2007 (n=632) and 2008 (n=793) AFL seasons. Players were fitted with a shoulder harness containing a GPS unit. GPS data were downloaded after games and the following measures extracted: total distance (km), time in various speed zones, maximum speed, number of surges, accelerations, longest continuous efforts and a derived exertion index representing playing intensity. In 2008 nomadic players covered per game 3.4% more total distance (km), had 4.8% less playing time (min), a 17% higher exertion index (per min), and 23% more time running >18kmh(-1) than forwards and defenders (all p<0.05). Physical demands were substantially higher in the 2008 season compared with 2005: an 8.4% increase in mean speed, a 14% increase in intensity (exertion index) and a 9.0% decrease in playing time (all p<0.05). Nomadic players in AFL work substantially harder than forwards and defenders in covering more ground and at higher running intensities. Increases in the physical demands of AFL football were evident between 2005 and 2008. The increasing speed of the game has implications for game authorities, players and coaching staff.
Sports scientists require a thorough understanding of the energy demands of sports and physical activities so that optimal training strategies and game simulations can be constructed. A range of techniques has been used to both directly assess and estimate the physiological and biochemical changes during competition. A fundamental approach to understanding the contribution of the energy systems in physical activity has involved the use of time-motion studies. A number of tools have been used from simple pen and paper methods, the use of video recordings, to sophisticated electronic tracking devices. Depending on the sport, there may be difficulties in using electronic tracking devices because of concerns of player safety. This paper assesses two methods currently used to measure player movement patterns during competition: (1) global positioning technology (GPS) and (2) a computer-based tracking (CBT) system that relies on a calibrated miniaturised playing field and mechanical movements of the tracker. A range of ways was used to determine the validity and reliability of these methods for tracking Australian footballers for distance covered during games. Comparisons were also made between these methods. The results indicate distances measured using CBT overestimated the actual values (measured with a calibrated trundle wheel) by an average of about 5.8%. The GPS system overestimated the actual values by about 4.8%. Distances measured using CBT in experienced hands were as accurate as the GPS technology. Both systems showed relatively small errors in true distances.
Objectives:
To examine the influence of quarter outcome and the margin of the score differential on both the physical activity profile and skill performance of players during professional Australian Football matches.
Design:
Prospective, longitudinal.
Methods:
Physical activity profiles were assessed via microtechnology (Global Positioning System and accelerometer) from 40 professional AF players from the same team during 15 Australian Football League games. Skill performance measures (involvement and effectiveness) and player rank scores (Champion Data(©) Rank) were provided by a commercial statistical provider. The physical performance variables, skill involvements and individual player performance scores were expressed relative to playing time for each quarter. The influence of the quarter result (i.e. win vs. loss) and score margin (i.e. small: <9 points, moderate: 10-18 points, and large: >19 points) on activity profile and skill involvements and skill efficiency performance of players were examined.
Results:
Skill involvements (total disposals/min, long kicks/min, marks/min, running bounces/min and player rank/min) were greater in quarters won (all p<0.01). In contrast, the players high speed running distance per minute (>14.5 km h(-1), HSR/min), sprints/min and peak speed were higher in losing quarters (all p<0.01). Smaller score margins were associated with increased physical activity (m/min, HSR/min, and body load/min, all p<0.05) and decreased skill efficiency (handball clangers/min and player rank/min, all p<0.05).
Conclusions:
Professional AF players are likely to have an increased physical activity profile and decreased skill involvement and proficiency when their team is less successful.
The purpose of this study was to quantify the movement demands of all nine individual playing positions in professional rugby league. The movement demands of 135 professional rugby league players were recorded during 28 National Rugby League games in 2011, using a non-differential 5 Hz global positioning system. The mean total distances covered in a game for fullback, wing, centre, five-eight and halfback, hooker, lock, back row and prop players were 7760, 7457, 7301, 8402, 8500, 6988, 5481, 6936, and 4597 m, respectively. The average frequency of high-intensity runs per match was 42, 35, 34, 86, 120, 74, 52, 26 and 18 for fullback, wing, centre, five-eight and halfback, hooker, lock, back row and prop players, respectively. The average distance travelled greater than 18 km.h for fullback were 17 ± 2 m, wing 18 ± 2 m, centre 18 ± 3 m, five-eight 16 ± 3 m and halfback 17 ± 4 m. The average distance and range travelled greater than 18 km.h for hooker were 14 ± 3 m, lock 16 ± 2 m, back row 18 ± 3 m, prop 16 ± 2 m. The use of GPS has demonstrated plausibility to eliminate the use of grouping of positions in rugby league and for coaches to make specific training protocols for each position. Given the differences in movement demands of all nine positions in rugby league, some positions would lack specificity to their positional requirements if using collective grouping for planning of training regimes.
The aim of the present study was to examine positional differences in physical performance measures of professional, semi-professional and junior elite Rugby League match-play using portable Global Positioning Systems (GPS). Twelve professional, twelve semi-professional and eighteen junior elite male Rugby League players were monitored during five regular season competition matches using portable GPS software. The mean total distance travelled during professional (8371 ± 897 m) and semi-professional (7277 ± 734 m) match-play was significantly (p< 0.05) greater than elite junior (4646 ± 978 m) match-play. Position specific total distance travelled and distance travelled per minute of playing time were significantly (p< 0.05) less for junior elite backs (5768 ± 765 m; 74 ± 11 m·min) and forwards (4774 ± 564 m; 82 ± 5 m·min) in comparison to professional (backs 8158 ± 673 m; 101 ± 8 m·min, forwards 8442 ± 812 m; 98 ± 12 m·min) and semi-professional (backs 7505 ± 765 m; 94 ± 8 m·min, forwards 6701 ± 678 m; 89 ± 8 m·min) match-play. Maximum running speed, maximum sprints and total sprint distance travelled by professional players were all significantly (p< 0.05) greater than junior elite player but not semi-professional players during match-play. Professional backs and forwards performed significantly (p< 0.05) more maximum sprints and travelled greater total distance during match-play in comparison to semi-professional and junior elite players. The present findings demonstrate minimal differences in the physical performance measures of professional and semi-professional Rugby League match-play. The position specific performance characteristics of junior elite match-play indicate current junior elite player development pathways may not provide adequate preparation for players transitioning into professional competition.
To describe the external load of Australian football matches and training using accelerometers.
Nineteen elite and 21 subelite Australian footballers wore accelerometers during matches and training. Accelerometer data were expressed in 2 ways: from all 3 axes (player load; PL) and from all axes when velocity was below 2 m/s (PLSLOW). Differences were determined between 4 playing positions (midfielders, nomadics, deeps, and ruckmen), 2 playing levels (elite and subelite), and matches and training using percentage change and effect size with 90% confidence intervals.
In the elite group, midfielders recorded higher PL than nomadics and deeps did (8.8%, 0.59 ± 0.24; 34.2%, 1.83 ± 0.39 respectively), and ruckmen were higher than deeps (37.2%, 1.27 ± 0.51). Elite midfielders, nomadics, and ruckmen recorded higher PLSLOW than deeps (13.5%, 0.65 ± 0.37; 11.7%, 0.55 ± 0.36; and 19.5%, 0.83 ± 0.50, respectively). Subelite midfielders were higher than nomadics, deeps, and ruckmen (14.0%, 1.08 ± 0.30; 31.7%, 2.61 ± 0.42; and 19.9%, 0.81 ± 0.55, respectively), and nomadics and ruckmen were higher than deeps for PL (20.6%, 1.45 ± 0.38; and 17.4%, 0.57 ± 0.55, respectively). Elite midfielders, nomadics, and ruckmen recorded higher PL (7.8%, 0.59 ± 0.29; 12.9%, 0.89 ± 0.25; and 18.0%, 0.67 ± 0.59, respectively) and PLSLOW (9.4%, 0.52 ± 0.30; 11.3%, 0.68 ± 0.25; and 14.1%, 0.84 ± 0.61, respectively) than subelite players. Small-sided games recorded the highest PL and PLSLOW and were the only training drill to equal or exceed the load from matches across positions and playing levels.
PL differed between positions, with midfielders the highest, and between playing levels, with elite higher. Differences between matches and training were also evident, with PL from small-sided games equivalent to or higher than matches.
The purpose of this study was to investigate the relationship between the prematch and short-term postmatch neuromuscular responses to the intensity, number, and distribution of impacts associated with collisions during elite Rugby League match play. Twenty-two elite male Rugby League players were monitored during 8 regular season competition matches using portable global positioning system (GPS) technology. The intensity, number, and distribution of impact forces experienced by players during match play were recorded using integrated accelerometry. Peak rate of force development (PRFD), peak power (PP), and peak force (PF) were measured during a countermovement jump on a force plate 24 hours prematch, 30 minutes prematch, 30 minutes postmatch and then at 24-hour intervals for a period of 5 days postmatch. The change in the dependent variables at each sample collection time was compared with that at 24 hours prematch and 30-minute prematch measures. There were significant (p < 0.05) decreases in PRFD and PP up to 24 hours postmatch with PF significantly (p < 0.05) being decreased 30 minutes postmatch. Significant (p < 0.05) correlations were found between the total number of impacts and PRFD and PP 30 minutes postmatch. Impact zones 4 (7.1-8.0 G), 5 (>8.1-10.0 G), and 6 (>10.1 G) were significantly (p < 0.05) correlated to PRFD and PP 30 minutes postmatch with the number of zone 5 and 6 impacts significantly (p < 0.05) correlated to PRFD and PP 24 hours postmatch. Elite Rugby League match play resulted in significant neuromuscular fatigue and was highly dependent on the number of heavy collisions >7.1G. Results demonstrate that neuromuscular function is compromised for up to 48 hours postmatch indicating that at least 2 days of modified activity is required to achieve full neuromuscular recovery after elite Rugby League match play. Position-specific demands on energy systems and the influence of repeated blunt force trauma during collisions during elite Rugby League match play should be considered when planning postmatch recovery protocols and training activities to optimize subsequent performance.
The current use of tracking technology in the form of global positioning systems (GPS) allows for a greater analysis of locomotor activities occurring in games and a larger volume of games when compared to TMA. Therefore the aim of this study is to be the first to analyse the physiological demands of forwards and backs throughout the entirety of an Australian professional rugby league season. The movement patterns of 185 players from a professional rugby league club were recorded during 28 National Rugby League (NRL) games played in Australia during the 2010 season. Players were clustered into two positional groups; backs and forwards. Maximum match-play time recorded was 99 minutes and 50 seconds in a semi-final game recorded for both a forward and back.The mean total distances covered in a game for forwards and backs were 5964 ± 696 m and 7628 ± 744 m respectively (p < 0.05). The maximum distance recorded by a forward was 10511m and 10359m for a back. The average number of occurrences in high-intensity running (> 18 km/h) was 23 ± 4 and for forwards and significantly higher backs with 35 ± 8 (p < 0.05). The maximum work rate in a 10-minute block of match-play was 115 m and 120 m per minute of play for forwards and backs respectively. Understanding the physiological demands of a sport is important for coaches to deliver athletes optimal training programs that elicit appropriate and specific physiological adaptation. The differences in locomotor activities, which occur between positions, need to be accounted for when developing training programs.
The purpose of this research was to investigate the validity and the reliability of 5-Hz MinimaxX global positioning system (GPS) units measuring athlete movement demands. A team sport simulation circuit (files collected from each unit = 12) and flying 50-m sprints (files collected from each unit = 34) were undertaken, during which the total distance covered; peak speed; player load; the distance covered; time spent and number of efforts performed walking, jogging, running, high-speed running, and sprinting were examined. Movement demands were also separately categorized into low-intensity activity, high-intensity running, and very high-intensity running. The results revealed that GPS was a valid and reliable measure of total distance covered (p > 0.05, percentage typical error of measurement [%TEM] < 5%) and peak speed (p > 0.05, %TEM 5-10%). Further, GPS was found to be a reliable measure of player load (%TEM 4.9%) and the distance covered, time spent, and number of efforts performed at certain velocity zones (%TEM <5% to >10%). The level of GPS error was found to increase along with the velocity of exercise. The findings demonstrated that GPS is capable of measuring movement demands performed at velocities <20 km·h(-1), whereas more caution is to be exercised when analyzing movement demands collected by using GPS velocities >20 km·h(-1).
The purpose of this study was to investigate positional relationships between sprint and jump abilities and body mass in elite college American football players (n = 1,136). Data from the annual National Football League combine over the years 2005-2009 were examined. The measures included for examination were the 9.1-, 18.3-, 36.6-, and flying 18.3-m sprints and the vertical and horizontal jumps. Pearson's correlation coefficients (r) were calculated to determine the relationships between the tests, and coefficients of determination (r2) were used to determine common variance. With the exception of the relationship between the 9.1-m and the flying 18.3-m sprints, the relationships between all sprints are very strong. Vertical jump ability is more strongly associated with maximum speed, as compared with acceleration. Horizontal jump ability is similarly associated with maximum speed and acceleration. The 9.1-, 18.3-, and flying 18.3-m sprints and the jump tests would appear to measure independent skills. Stationary start sprints up to 36.6 m appear to be heavily influenced by acceleration and may thus measure similar characteristics. The flying 18.3-m sprint is recommended as a measure of maximum speed. Body mass was most strongly associated with performance in the lineman group. When body mass was controlled for, correlations weakened across all the groups. The role of body mass remains unclear. Regardless of sport, the present research supports the notion that the relationships between various sprint and jump abilities warrant positional consideration. Coaches and practitioners will be able to use the findings of this research to better test and monitor athletes requiring different skills.
The purpose of this study was to determine if there is an association between variables that describe movements in an Australian Rules football (ARF) game with muscle damage. Fourteen elite junior ARF players were monitored with a global positioning system (GPS) during a match, and muscle damage was estimated by determining creatine kinase (CK) 24 hours postmatch. The players were median split based on CK levels, into a high and low CK group, and the groups were compared with independent t-tests. The primary finding was that the group that experienced greater muscle damage (high CK group) generally covered significantly (p < 0.05) greater distances. This was the case for running speeds between 4 and 7 m·s(-1) and, with the exception of high acceleration, all intensities of acceleration and deceleration. The high, as compared with the low, CK group also produced a significantly greater (42%) "player load." All of these significant differences were accompanied by large effect sizes. Group-specific Pearson (r) correlations between CK level and GPS variables suggest that a certain volume of movement is required before the elicitation of a positive relationship beyond trivial or small. Correlations between CK and running speeds >4 m·s(-1) and moderate-high acceleration and deceleration were negative in the low CK (lesser volumes) group. With the exception of low-intensity acceleration/deceleration, the same relationships were positive and generally of a moderate-to-large magnitude in the high CK (greater volumes) group. It may be that a certain volume of movement is required for that movement to be strongly associated with CK levels. It was concluded that selected GPS variables obtained from ARF games can be used as indicators of muscle damage, and this information may be used to individualize recovery strategies after games.
In this study, we assessed the validity and reliability of 5 and 10 Hz global positioning systems (GPS) for measuring instantaneous velocity during acceleration, deceleration, and constant velocity while straight-line running. Three participants performed 80 running trials while wearing two GPS units each (5 Hz, V2.0 and 10 Hz, V4.0; MinimaxX, Catapult Innovations, Scoresby, VIC, Australia). The criterion measure used to assess GPS validity was instantaneous velocity recorded using a tripod-mounted laser. Validity was established using the standard error of the estimate (± 90% confidence limits). Reliability was determined using typical error (± 90% confidence limits, expressed as coefficient of variation) and Pearson's correlation. The 10 Hz GPS devices were two to three times more accurate than the 5 Hz devices when compared with a criterion value for instantaneous velocity during tasks completed at a range of velocities (coefficient of variation 3.1-11.3%). Similarly, the 10 Hz GPS units were up to six-fold more reliable for measuring instantaneous velocity than the 5 Hz units (coefficient of variation 1.9-6.0%). Newer GPS may provide an acceptable tool for the measurement of constant velocity, acceleration, and deceleration during straight-line running and have sufficient sensitivity for detecting changes in performance in team sport. However, researchers must account for the inherent match-to-match variation reported when using these devices.
The purpose of this study was to examine the differences in physical performance and game-specific skill demands between 5 positional groups in a professional rugby league team. Positional groups consisted of the backs (n = 8), forwards (n = 8), fullback (n = 7), hooker (n = 8), and service players (n = 8). Time-motion analysis was used to determine physical performance measures (exercise intensity, distance travelled, time, frequency, and speed measures) and game-specific skill measures (ball carries, supports, ball touches, play the balls, and tackling indices) per minute of playing time. The main finding was that the fullback completed more very high-intensity running (VHIR) because of more support runs when compared to all other positional groups (p = 0.017). THe VHIR (p = 0.004) and sprinting indices (p < 0.002) were also greater in the second half of a match for the fullback than in any other positional group. The hooker spent more time jogging than the backs and forwards (p < 0.001) and touched the ball on more occasions than any other positional group (p < 0.001). The backs spent more time walking than the forwards, hooker, and service players (p < 0.001). The forwards, hooker, and service players completed more tackles per minute during a match than the backs and fullback (p < 0.001). The fullback and forwards also ran the ball on more occasions than the backs, hooker, and service players did (p < 0.001). These results show that positional roles play an important part in determining the amount of physical and game-specific skill involvement during match play.
The purpose of this study was to evaluate physical demands of football players during preseason practices in the heat. Furthermore, we sought to compare how physical demands differ between positions and playing status. Male National Collegiate Athletic Association Division 1 football players (n = 49) participated in 9 practice sessions (142 ± 16 minutes per session; wet bulb globe temperature (WBGT) 28.75 ± 2.11°C) over 8 days. Heart rate (HR) and global positioning system data were recorded throughout the entirety of each practice to determine the distance covered (DC), velocity (V), maximal HR (HRmax), and average HR (HRavg). The subjects were divided into 2 groups: linemen (L) (N = 25; age: 22 ± 1 years, weight: 126 ± 16 kg, height: 190 ± 4 cm,) vs. nonlinemen (NL) (N = 24; age: 21 ± 1 years, weight: 91 ± 11 kg, height: 183 ± 8 cm) and starters (S) (N = 17; age: 21 ± 1 years, weight: 118 ± 21 kg, height: 190 ± 7 cm) vs. nonstarters (NS) (N = 32; age: 20 ± 1 years, weight: 105 ± 22 kg, height: 185 ± 7 cm) for statistical analysis. The DC (3,532 ± 943 vs. 2,573 ± 489 m; p = 0.001) and HRmax (201 ± 9 vs. 194 ± 11 b·min(-1); p = 0.025) were significantly greater in NL compared with that in L. In addition, NL spent more time (p < 0.0001) and covered more distance (p = 0.002) at higher velocities than L did. Differences between S vs. NS were observed (p = 0.008, p = 0.031), with S obtaining higher velocities than NS did. Given the demands of their playing positions, NL were required to cover more distance at higher velocities, resulting in a greater HRmax than that of L. Therefore, it appears that L engage in more isometric work than NL do. In addition, the players exposed to similar practice demands provide similar work output during preseason practice sessions regardless of their playing status.
Interest in the quantification of physical activity is on the rise. Triaxial accelerometry has frequently been used; however, research on the reliability of these devices is limited. We examine the interunit and intraunit reliability of 22 RT3 triaxial accelerometers using a performance-documented laboratory agitator.
The RT3 units were tested while moving in 2 directions (antero-posterior, medio-lateral) and speeds (150 and 275 RPM) on a shaker with simultaneous documented performance output for three 24-hour periods.
Minimal shaker variance was recorded for all trials (coefficients of variation [CVs] < 0.52%). Our data demonstrate good reliability within RT3s (CVs < 1.81%) but poor reliability among the 22 units (CVs range = 9.5% to 34.7%).
In longitudinal studies, each subject should use the same RT3 unit at each assessment. The use of multiple RT3 units in cross-sectional studies is not recommended because data interpretation would be compromised by the high between-unit variability.