Article

Quantification of Accelerometer Derived Impacts Associated With Competitive Games in NCAA Division I College Football Players

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Abstract

The aims of the present study were to 1) examine positional impact profiles of NCAA division I college football players using global positioning system (GPS) and integrated accelerometry (IA) technology, and 2) determine if positional differences in impact profiles during competition exist within offensive and defensive teams. Thirty-three NCAA Division I Football Bowl Subdivision players were monitored using GPS and IA (GPSports, Canberra, Australia) during 12 regular season games throughout the 2014 season. Individual player datasets (n = 294) were divided into offensive and defensive teams, and positional sub-groups. The intensity, number, and distribution of impact forces experienced by players during competition were recorded. Positional differences were found for the distribution of impacts within offensive and defensive teams. Wide receivers (WR) sustained more very light and light to moderate (5-6.5 G force) impacts than other position groups, while the running backs (RB) were involved in more severe (>10 G force) impacts than all offensive position groups, with the exception of the quarterbacks (QB) (p<0.05). The defensive back (DB) and linebacker (LB) groups were subject to more very light (5.0-6.0 G force) impacts, and the defensive tackle (DT) group sustained more heavy and very heavy (7.1-10 G force) impacts than other defensive positions (p<0.05). Data from the present study provide novel quantification of positional impact profiles related to the physical demands of college football games and highlight the need for position-specific monitoring and training in the preparation for the impact loads experienced during NCAA Division I football competition.

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... Monitoring collisions that contact sports players have to endure may help to mitigate the risk of injury. As with in-game workload monitoring, learning more about in-game collision loads can aid coaches in designing more specialized training and recovery strategies to better prepare their players (Wellman et al 2017). ...
... When monitoring collision events using accelerometers, the collision intensity is determined by the acceleration of the player due to the collision (Gabbett et al 2014, Wellman et al 2017, Naughton et al 2020. In most studies, different ranges of acceleration are categorized into three severity levels, mild, moderate, and heavy (Gabbett et al 2014, Wellman et al 2017, Naughton et al 2020. ...
... When monitoring collision events using accelerometers, the collision intensity is determined by the acceleration of the player due to the collision (Gabbett et al 2014, Wellman et al 2017, Naughton et al 2020. In most studies, different ranges of acceleration are categorized into three severity levels, mild, moderate, and heavy (Gabbett et al 2014, Wellman et al 2017, Naughton et al 2020. However, the acceleration ranges used for each severity level vary across different studies, which makes it difficult to meaningfully compare their outputs (Naughton et al 2020). ...
Article
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Participation in sports has become an essential part of healthy living in today's world. However, injuries can often occur during sports participation. With advancements in sensor technology and data analytics, many sports have turned to technology-aided, data-driven, on-field monitoring techniques to help prevent injuries and plan better player management. This review searched three databases, Web of Science, IEEE, and PubMed, for peer-reviewed articles on on-field data monitoring techniques that are aimed at improving the health and well-being of team-sports athletes. It was found that most on-field data monitoring methods can be categorized as either player workload tracking or physical impact monitoring. Many studies covered during this review attempted to establish correlations between captured physical and physiological data, as well as injury risk. In these studies, workloads are frequently tracked to optimize training and prevent overtraining in addition to overuse injuries, while impacts are most often tracked to detect and investigate traumatic injuries. This review found that current sports monitoring practices often suffer from a lack of standard metrics and definitions. Furthermore, existing data-analysis models are created on data that are limited in both size and diversity. These issues need to be addressed to create ecologically valid approaches in the future.
... To illustrate, the running back (RB) and wide receiver (WR) typically perform more noncontact running and cutting actions and cover greater high-speed distance than other positions (22). Offensive linemen (OL) and defensive linemen (DL) are typically more engaged in movements such as blocking or tackling (8,22,25). Defensive backs (DB), linebackers (LB), and tight ends (TE) execute a combination of high-speed running, and blocking and tackling movements (22). Those positions are also known for their hybrid nature. ...
... Previous studies have revealed positional differences in practices and games; for instance, nonlinemen (e.g., WR, RB, DB, and quarterbacks [QB]) perform greater amounts of running movements compared with linemen (e.g., OL, DL, and TE) during the preseason period (8). Moreover, WR, DB, and LB experience more light-intensity impacts (5.0-6.0 g force) compared with other offensive and defensive positions during collegiate American football games (25). An evaluation of practice demands of National Football League (NFL) players revealed that variations in training intensity between positional groups can also be influenced by the periodization of training (22). ...
... During those plays, an RB often collided with linemen near the line of scrimmage demanding higher IMA efforts from the RB, which was exerted by quick changes of direction, a change in speed, or collisions with other players. Similar results were seen from impact profiles of RBs, revealing that RBs were exposed to the greatest number of severe impacts during games compared with other position groups (25). Those findings suggested that during indy drills, RB must develop skills to cope with a high degree of contact and high-speed running demands. ...
Article
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Quantifying player training loads allows football coaching staff to make informed adjustments to the volume and intensity of training. Physical workload intensity in American football practices have not been extensively quantified. The current study examined physical workload intensities across positions in American collegiate football during training. Data from player tracking technology (Catapult Vector) were collected from 72 American football players (National Collegiate Athletic Association Division I) during in-season practices. Players were involved in individualized skill (indy), team playbook (team), and special team (ST) drills during practice and analyzed for their specialist offensive or defensive role (e.g., linebacker or wide receiver). Player running (i.e., high-speed running and sprint) and accelerations (i.e., high-intensity PlayerLoad and high-intensity inertial movement analysis) per minute were of interest. Drill type and practice day had significant effects on all workload intensity metrics (p < 0.01), but not position. Greater running intensities were seen in ST drills compared with other drill types. Tuesday practice sessions had greater overall intensities compared with other days. Interaction effect of position and drill type was significant (p < 0.001) for all intensity metrics, indicating that position groups exhibited unique workload responses to the drill types. Drill type and practice day interaction effect was significant for all intensity metrics (p < 0.01). The findings may be informative for coaches to tailor physical workloads of practice drills for positional roles in preparation for games and practices. Player tracking technology can add value for strength and conditioning coaches to adjust training programs based on position-specific on-field demands of players.
... Currently, peak and accumulated workload during team sports have been registered through inertial devices composed of tri-axial accelerometers at the scapulae level using an anatomically adjusted harness (Casamichana et al., 2013;Dalen et al., 2016;Gibson et al., 2016;Ritchie et al., 2016;Scanlan et al., 2014;Wellman et al., 2016;Wik et al., 2017). Then, a brief review of the peak and accumulated variables from accelerometry, as well as the specific location during monitoring is performed for practical applications in team sports. ...
... Arbitrary units (Gabbett, 2015;McLellan and Lovell, 2012;Suárez-Arrones et al., 2012), soccer (Abade et al., 2014) and American football (Wellman et al., 2016). Among sports modalities, the differentiating factor has been the impact/collision threshold (in g-force) selected for their detection. ...
... Among sports modalities, the differentiating factor has been the impact/collision threshold (in g-force) selected for their detection. In this sense, the detection threshold in rugby or American football has been set at 10 G (Gabbett et al., 2010;Suárez-Arrones et al., 2012;Wellman et al., 2016). Instead, the detection threshold set in soccer was 5 G. On the other hand, if it compares the number of impacts/ collisions suffered between sport modalities, soccer received a smaller number of >5 G impacts (490±309.5 to 613.1±329.4) ...
... 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). ...
... Moreover, WR, DB and LB performed significantly greater high-intensity locomotor activities (high-intensity running, sprint distance, and high-intensity accelerations and decelerations) than all other positions. In a second study (63), the authors examined the positional impact profiles (intensity, number, and distribution of impact forces) and their results demonstrated different distribution of force impacts between the positions, with RB experiencing the greatest number of severe (above 10G force) impacts during games compared to the other offensive positions, with the exception of the quarterbacks. To further highlight these positional differences, Sanders et al. (52) quantified average and maximal total distance and high-speed distance throughout a competitive season to get a better understanding of maximal or near maximal in-game distance workloads and thus improve conditioning protocols and periodization practices. ...
... In fact, McCunn, Fullagar, Williams, & Halseth (42) speculated that WR might be more vulnerable to the physical effects of game-related fatigue because they cover more total, HSR and sprint distances than all other offensive positions. Data from the present study reflect those positional differences between RB and WR, although RB will experience more severe collisions during games (63). However, no available injury data from this study can confirm or refute these speculations. ...
Article
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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.
... Autores Sistema de Clasificación de los impactos Rugby (Venter et al., 2011) De 5 a 6g De 6.5 a 7g De 7 a 8g De 8 a 10g Mayor de 10g -Impacto suave, fuerte aceleración/desaceleración cambio de dirección -Impacto Moderado a fuerte -Impacto Fuerte -Impacto Muy fuerte -Impacto severo (Colisión) Rugby (Owen et al., 2015) Fútbol Americano (Wellman et al., 2017) Suave: 5,00 -5,99 Bajo-Moderado: 6,00 -6,49 Moderado-Fuerte: 6,50-6,99 Fuerte: 7,00-7,99 Muy Fuerte: 8,00-9,99 Severo: ≥10.0 -Fuerte aceleración/desaceleración cambio de dirección -Colisión menor con el oponente o contra el suelo. ...
... Además siguiendo las propuestas en otras disciplinas como el rugby o el fútbol (Cunniffe et al., 2009;Wellman et al., 2017) y en balonmano playa (Zapardiel & Asín-Izquierdo, 2020) se estudian las exigencias de los diferentes puestos específicos del balonmano playa en competición. ...
... La clasificación propuesta por Wellman et al., (2017) desestima los impactos de baja intensidad y evalúa los impactos en caídas-contactos-cambios bruscos de dirección, situando esta clasificación entre 5 y 15 g. No obstante los datos estudiados en la presente tesis doctoral se basan en la clasificación propuesta por utilizada para el rugby diferenciando cinco zonas de 5,5 g a >10 g, con una pequeña diferencia dada las características del balonmano playa y sus consecuentes diferencias con el rugby (donde el contacto está permitido). ...
Thesis
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This doctoral thesis deals with the kinematic, kinetic and physiological demands of beach handball in the absolute category of women in competition. The aim is to determine and compare in official and unofficial matches and to check that the physical tests of resistance, jumping and sprinting capacity are related to these demands. The competition is analyzed on the basis of the variables of distance, speed, acceleration and deceleration, sprint and impact and by heart rate. These variables have been related to two qualitative variables such as the type of match (official - unofficial) and the specific positions that the players perform in competition. In addition, the game time has been subdivided into 5-minute periods. From the analysis of the obtained data, it is extracted that the average distance is 368,5±142,3 m in official matches and 257,1±100,4 m in non-official matches (CD: 29%, ES: 0,980). 80% of the distance covered is divided between zone 2 (10-29% Vmax) with 47% and zone 4 (50-79% Vmax) with 34%. The maximum speed achieved in official matches is 15.4±1.6 km.h-1 and in non-official matches 13.2±2.1 km·h-1 (CD: 14.2%; ES: 1.037). The highest number of impacts is recorded in intensities of (1.5 to 5.5 g), being 22% higher in official matches than in non-official ones. It can be seen that 29% of the playing time is spent on acceleration and deceleration, with the maximum acceleration being 3.99 m·s-2, covering distances of 5,65,3 m. Reporting significant differences (p<0.01) between the number of accelerations recorded in official and unofficial matches (CD:7.4%; ES:0.241). High intensity actions (>2.75 m·s-2) reported an average of 13.7±8.9 in official matches with a repetition rate of 65.4%. The FCmax in official matches was 182.0±11.0 (ppm) between 3.9-6% higher than in non-official matches. The areas where the heart rates were concentrated in greater percentage were in zone 1 (0-60% FCmax) and zone 4 (80-90% FCmax). The qualitative variable on the specific positions determines significant differences in the variables of distance and speed. The defense post is the one that covers the most distance and the specialist post the one that covers the least distance. The qualitative variable where the playing time was divided into five-minute intervals determined that it is at the beginning of the second set that all the variables are superior compared to the rest of the time intervals. Likewise, the physical tests administered determine that the variables distance covered, maximum acceleration, number of sprints and distance in sprints are related to the results obtained in the jumping, speed and resistance tests administered. It is concluded that beach handball is an intermittent discipline where distances, speed and accelerations are related to the specific positions held. The impacts that the player suffers in competition are the product of falls-landings and the conditional performance of this discipline is determined by the capacity of jumping-sprints that the player can develop.
... Currently, peak and accumulated workload during team sports have been registered through inertial devices composed of tri-axial accelerometers at the scapulae level using an anatomically adjusted harness (Casamichana et al., 2013;Dalen et al., 2016;Gibson et al., 2016;Ritchie et al., 2016;Scanlan et al., 2014;Wellman et al., 2016;Wik et al., 2017). Then, a brief review of the peak and accumulated variables from accelerometry, as well as the specific location during monitoring is performed for practical applications in team sports. ...
... Arbitrary units (Gabbett, 2015;Suárez-Arrones et al., 2012), soccer (Abade et al., 2014) and American football (Wellman et al., 2016). Among sports modalities, the differentiating factor has been the impact/collision threshold (in g-force) selected for their detection. ...
... Among sports modalities, the differentiating factor has been the impact/collision threshold (in g-force) selected for their detection. In this sense, the detection threshold in rugby or American football has been set at 10 G Suárez-Arrones et al., 2012;Wellman et al., 2016). Instead, the detection threshold set in soccer was 5 G. On the other hand, if it compares the number of impacts/ collisions suffered between sport modalities, soccer received a smaller number of >5 G impacts (490±309.5 to 613.1±329.4) ...
Book
The use of technology within sport is well established, most professional sport teams engage with the use of Electronic Performance and Tracking Systems. This book is the first to offer a dep and structured examination of these technologies and how they are used in a team sport setting. The Use of Applied Technology in Team Sport describes and assists researchers, academics and professionals with understanding the methodology around applied technology in sport examining; what systems track players performance, who are the manufacturers that provide these systems. This new volume goes on to describe how to apply the systems and highlights the ways of reporting analysis information and helps the reader to know and understand the future avenues of research and development. The Use of Applied Technology in Team Sport is considered an essential guide for researchers, academics and students as well as professionals working in the areas of Applied Sport Science, Coaching, and subjects relating to Physiology, Biomechanics, Sports Engineering, Sports Technology and Performance Analysis in Sport.
... Another interesting variable to quantify during training sessions is body impact, which could provide relevant information regarding the mechanical stresses arising from the kinetic demands of all forces imposed on players during acceleration/deceleration, related changes of direction and impacts from both the player-toplayer collision and contact with the ground (Cummins et al., 2013;McLean et al., 2010;Vanrenterghem et al., 2017). In fact, body impacts have been demonstrated to be a useful variable to assess match-related fatigue (Russell et al., 2016), to understand training and match loads rather than other external loads (Abade et al., 2014;Arruda et al., 2015), to predict the training load measured by the rating of perceived moderate exertion (Gaudino et al., 2015), to provide specific soccer position profiles (Wellman et al., 2016) and to quantify the external load during sided soccer games. Thus, using body impacts as an external load variable would be interesting for coaches in order to widely understand the physical demands of the different soccer sided games. ...
... The software displayed the total impact counts from collisions, the intensity, as well as the time during the game or training drill where the impact occurred. A scaling system between 5-10+g for grading the impacts (I) was used: I5-6g: light impact, hard acceleration/deceleration/change of direction; I6-6.5g: light to moderate impact (player collision, contact with the ground); I6.5-7g: moderate to heavy impact; I7-8g: heavy impact; I8-10g: very heavy impact (scrum engagement); and I10+g: severe impact/tackle/collision. Impacts above 10g were used to report on the number of severe impacts that the players received during games (Wellman et al., 2016). The equipment presented good levels of validity and reliability in linear, circular and zig-zag courses (Bastida- Castillo et al., 2018;Muñoz-Lopez et al., 2017). ...
... Despite the scarce literature focused on body impacts in soccer, it seems that the quantification of this variable could be interesting in order to implement appropriate training strategies (Abade et al., 2014;Arruda et al., 2015). To date, although some authors have reported information about the number and intensities of body impacts during official soccer games (Russell et al., 2016;Wellman et al., 2016), only one study has provided data during training drills (Castillo, Raya-Gonzalez, Clemente et al., 2019). In line with this investigation, the results of our study showed that greater body impacts were registered in LSGs compared to SSGs. ...
Article
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The aim of this study was to compare external training loads between small-sided games (SSGs) and large-sided games (LSGs) in soccer players. Twenty outfield soccer players (14.8 ± 0.6 years old) who competed in the Spanish U16 Provincial Division and belonged to the same team participated in the study. The soccer sided games were played at different individual interaction space (IIS) per player (i.e., SSG = 100 m 2 and LSG = 200 m 2) and were disputed in the same format (five-aside plus goalkeepers) on two different pitch sizes (i.e., 38 x 26 vs. 53 x 37 m) defending an official soccer-goal. The sided games' duration was 4 bouts of 6 min with 2 min rest intervals between bouts. The results of this study showed no meaningful differences in the total distance and intensity of accelerations and decelerations between SSGs and LSGs except for the lower distance covered at medium intensity (2.5-4 m·s-2) observed during LSGs (-10.2%; ES (effect size):-0.51). Players registered greater sprints, maximum velocity (Velmax) and body impacts at different intensities (i.e., I5-6g, I6-6.5g, I6.5-7g, I7-8g, I8-10g,) in LSGs in comparison to SSGs. These findings suggest that an increase in the pitch size (i.e., IIS per player) can induce higher external loads for soccer players.
... In most of the analyzed studies, the inertial devices composed of tri-axial accelerometers for external workload monitoring in invasion team sports have been placed on the scapulae using an anatomically adjusted harness [8,17,26,69,93,98,99], except in a few studies where the companies recommend the location on the center of mass [24-26, 29] or the sternum [41]. ...
... Currently, from the raw data obtained by the accelerometer, the analysis of external workload is carried out from two main variables: impacts as a function of intensity ranges and PL TM in its different variants (2D, x-axis, y-axis, z-axis, slow). Workload quantification about the intensity of impacts has been used predominantly in rugby [92,[100][101][102][103], soccer [42] and American football [99]. In rugby and American football the detection threshold is 10G [91,92,99,103]. ...
... Workload quantification about the intensity of impacts has been used predominantly in rugby [92,[100][101][102][103], soccer [42] and American football [99]. In rugby and American football the detection threshold is 10G [91,92,99,103]. In soccer, the detection threshold is 5G, and the number of impacts ranges from 490±309.5 to 613.1±329.4 number of impacts [42]. ...
Article
Full-text available
Accelerometry is a recent method used to quantify workload in team sports. A rapidly increasing number of studies supports the practical implementation of accelerometry monitoring to regulate and optimize training schemes. Therefore, the purposes of this study were: (1) to reflect the current state of knowledge about accelerometry as a method of work-load monitoring in invasion team sports according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines, and (2) to conclude recommendations for application and scientific investigations. The Web of Science, PubMed and Scopus databases were searched for relevant published studies according to the following keywords: "accelerometry" or "accelerometer" or "microtechnology" or "inertial devices", and "load" or "workload", and "sport". Of the 1383 studies initially identified, 118 were selected for a full review. The main results indicate that the most frequent findings were (i) devices' body location: scapulae; (b) devices brand: Catapult Sports; (iii) variables: PlayerLoad TM and its variations; (iv) sports: rugby, Australian football, soccer and basketball ; (v) sex: male; (vi) competition level: professional and elite; and (vii) context: separate training or competition. A great number of variables and devices from various companies make the comparability between findings difficult; unification is required. Although the most common location is at scapulae because of its optimal signal reception for time-motion analysis, new methods for multi-location skills and locomotion assessment without losing tracking accuracy should be developed.
... Distance covered while accelerating (Acc) and decelerating (Dec) was taken as a key outcome measure, with further distance measures derived for different intensity categories: low-intensity acceleration (LAcc; 1-2.5 m·s −2 ), medium-intensity acceleration (MAcc; 2.5-4 m·s −2 ), high-intensity acceleration (HAcc; > 4 m·s −2 ), low-intensity deceleration (LDec; −1/-2.5 m·s −2 ), medium-intensity deceleration (MDec; −2.5/-4 m·s −2 ), and high-intensity deceleration (HDec; < −4 m·s −2 ). In addition, the GPS devices were coupled with a 100 Hz triaxial accelerometer that allowed for the estimation of body impact data provided in "g" force (Wellman, Coad, Goulet, Coffey, & McLellan, 2016). An impact is counted by the system if the force applied is more than five g force units (5 g). ...
... Previous authors have reported body impacts to represent not only the physical contact but also the high number of impacts during soccer small-sided games practice in youth players (Abade, Gonçalves, Leite, & Sampaio, 2014). The software displays the total impact counts from collisions, the intensity and the point in the game or training drill where the impact occurred (Wellman et al., 2016). Data were collected during what were considered to be good weather and satellite conditions for GPS (number of satellites = 10.1 ± 0.2). ...
... In addition, greater body impacts are registered as the size of the playing area increases. This finding is a great novelty in the training process because no scientific study has addressed body impact during training drills, and only data on official matches has been reported (Wellman et al., 2016). Future works could investigate match-related fatigue caused by body impacts, in order to implement training programmes to ensure soccer players can cope with the high body impact demands. ...
Article
The aims of this study are 1) to compare sided games’ (SGs) external responses encountered by players according to pitch size and to 2) examine the relationships between sprint performance and SGs’ external physical responses. Twenty soccer players under 15 years of age (U-15) participated in this study. Each player performed a sprinting test (10 m and 30 m sprints) and played a SG on two different pitch sizes (small at 100 [SSG] and large at 200 [LSG] m2 per player). Higher external responses (p < 0.01, ES = -6.41–1.22) were found in LSG in comparison to SSG, except to distance accelerating and decelerating (p > 0.05, ES = -0.26–0.27). Players who were faster over 10 and 30 m covered higher distances cruising and sprinting (r = -0.47/-0.66;  0.23/ 0.30, respectively, p < 0.05), performed a greater number of sprints, achieved higher maximum velocity (Velmax) during LSG and covered a greater distance at high-intensity accelerating (r = -0.50/-0.70; 0.21/0.29, respectively, p < 0.05) during SSG and LSG. LSG demanded a higher external load in comparison with SSG. In addition, the improved sprint capacity could allow players to perform greater running activities and short-term actions at high-intensities during SG.
... The modern-day game of American football (AmF) is primarily comprised of repeated high-intensity bouts involving change of direction, acceleration, deceleration and sprinting, followed by longer periods of low-intensity rest, recovery and tactical play [1][2][3]. Athletes also experience high contact loads through tackling and blocking [2], with the resultant collision loads greatly differing depending on positional requirements [2,3]. For ease of clarification, collisions are defined as direct contact with another player in the instance of tackling or blocking. ...
... The modern-day game of American football (AmF) is primarily comprised of repeated high-intensity bouts involving change of direction, acceleration, deceleration and sprinting, followed by longer periods of low-intensity rest, recovery and tactical play [1][2][3]. Athletes also experience high contact loads through tackling and blocking [2], with the resultant collision loads greatly differing depending on positional requirements [2,3]. For ease of clarification, collisions are defined as direct contact with another player in the instance of tackling or blocking. ...
... The modern-day game of American football (AmF) is primarily comprised of repeated high-intensity bouts involving change of direction, acceleration, deceleration and sprinting, followed by longer periods of low-intensity rest, recovery and tactical play [1][2][3]. Athletes also experience high contact loads through tackling and blocking [2], with the resultant collision loads greatly differing depending on positional requirements [2,3]. For ease of clarification, collisions are defined as direct contact with another player in the instance of tackling or blocking. ...
Article
Full-text available
The sport of American football (AmF) exposes athletes to high velocity movements and frequent collisions during competition and training placing them at a susceptible risk of contact and non-contact injury. Due to the combative nature of the game the majority of injuries are caused by player contact, however a significant amount are also non-contact soft tissue injuries. Literature suggests that this mechanism of injury can be prevented through workload monitoring and management. The recent introduction of microtechnology into AmF allows practitioners and coaches to quantify external workload of training and competition to further understand the demands of the sport. Significant workload differences exist between positions during training and competition; couple this with large differences in anthropometric and physical characteristics between and within positions suggest that the training response and physiological adaptations will be highly individual. Effective athlete monitoring and management allows practitioners and coaches to identify how athletes are coping with the prescribed training load and subsequently if they are prepared for competition. Several evidence based principles exist that can be adapted and applied to AmF which could decrease the risk of injury and optimise athletic performance.
... Actualmente, a partir de los datos brutos obtenidos por el acelerómetro, el análisis de la carga de trabajo externa se lleva a cabo a partir de dos variables principales: los impactos en función de los rangos de intensidad y PL TM en sus diferentes variantes (2D, eje x, eje y, z-eje, lento). La cuantificación de la carga de trabajo sobre la intensidad de los impactos se ha utilizado predominantemente en el rugby (Gabbett, 2013(Gabbett, , 2015Gabbett & Seibold, 2013;McLellan & Lovell, 2012;Suárez-Arrones et al., 2012), fútbol (Abade, Gonçalves, Leite & Sampaio, 2014) y fútbol americano (Wellman et al., 2017). En rugby y fútbol americano el umbral de detección de las colisiones/impactos es de 10g (Gabbett, 2013;Gabbett et al., 2010;Suárez-Arrones et al., 2012;Wellman et al., 2017 (Gabbett, 2015). ...
... La cuantificación de la carga de trabajo sobre la intensidad de los impactos se ha utilizado predominantemente en el rugby (Gabbett, 2013(Gabbett, , 2015Gabbett & Seibold, 2013;McLellan & Lovell, 2012;Suárez-Arrones et al., 2012), fútbol (Abade, Gonçalves, Leite & Sampaio, 2014) y fútbol americano (Wellman et al., 2017). En rugby y fútbol americano el umbral de detección de las colisiones/impactos es de 10g (Gabbett, 2013;Gabbett et al., 2010;Suárez-Arrones et al., 2012;Wellman et al., 2017 (Gabbett, 2015). Estos datos confirman que cada deporte tiene demandas específicas con respecto a la carga de trabajo externa, siendo los rangos como consecuencia de las diferentes posiciones de juego. ...
Thesis
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La acelerometría es un método de cuantificación de la carga externa que está teniendo una aplicación exponencial gracias a su integración en dispositivos electrónicos para el análisis del rendimiento en deportes colectivos. La carga externa ha sido comúnmente cuantificada a través del desplazamiento (distancia y velocidad), no teniendo en cuenta su efecto a nivel neuromuscular. Por ello, el objetivo principal de la presente Tesis Doctoral es el análisis de la carga externa que soportan múltiples ubicaciones anatómicas de forma simultánea en los desplazamientos deportivos, específicamente en baloncesto. Para ello, se realiza una revisión sistemática detectando que diferentes aspectos técnicos requieren una evaluación previa al registro así como que los acelerómetros miden la aceleración del segmento al que están unidos. Para subsanar ambos aspectos, se realiza un análisis de la precisión y fiabilidad del sensor, se identifican los índices de carga y frecuencia de muestreo adecuados, así como se diseña y valida un protocolo de registro multi-ubicación y una batería de evaluaciones que representa los desplazamientos más comunes en los deportes de invasión. Finalmente, se realiza la evaluación multi-ubicación de la carga externa en test de laboratorio y test de campo para evaluar el efecto de la velocidad, sexo y tipo de desplazamiento, así como establecer perfiles de rendimiento individual. A partir de estos resultados, los entrenadores podrán identificar la carga externa específica de cada estructura musculoesquelética para diseñar programas individualizados de acondicionamiento físico, prevención de lesiones y recuperación adaptados a los grupos musculares con mayor carga externa. Accelerometry is a method for quantifying external load that is having an exponential application thanks to its integration in electronic performance and tracking systems in team sports. External load has been commonly quantified through displacement (distance and speed), not considering its effect at the neuromuscular level. Therefore, the main objective of this Doctoral Thesis is the analysis of the external load supported by multiple anatomical locations simultaneously in sports movements, specifically in basketball. To do this, a systematic review is carried out, detecting those different technical aspects that require an evaluation prior to registration, as well as that the accelerometers measure the acceleration of the segment to which they are attached. To correct both aspects, an analysis of the precision and reliability of the sensor was performed, the appropriate load index and sampling frequency were identified, as well as a multi-location registration protocol and a battery of evaluations that represent the most common displacements in invasion sports were designed and validated. Finally, the multi-location evaluation of the external load was performed in laboratory and field tests to evaluate the effect of speed, sex and type of movement, as well as to establish individual performance profiles. From these results, trainers will be able to identify the specific external load of each musculoskeletal structure to design individualized programs for physical conditioning, injury prevention and recovery adapted to the muscle groups with the highest external load.
... 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. ...
Article
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.
... American football is a crash-based sport including intense physical collisions, and characterized by intermittent short duration maximum high intensity activities separated by short rest times between games. It requires physical performance characteristics such power, strength, speed, acceleration, deceleration [2][3][4][5][6], and also skills such as catching, throwing, backpedalling, stealing, blocking, backpedalling, and back-pedaling, and sudden multi-directional running in-match performance [7]. The game is played by 11 players on each team. ...
... 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. ...
Article
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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.
... 14 However, variable workload periods have not been compared when calculating EWMA's and it is unclear if one model would be appropriate for all sports. American football for example has a unique playing structure (separate offensive and defensive 'teams') and playing season (16)(17) weeks inclusive of pre-season) that is substantially shorter than other contact sports (Rugby League and Australian football) where ACWR spikes have been associated with elevated injury risks. 6,11,12 Furthermore, there is variation in the number of injuries observed across positional groups in NCAA football 5 and it is known that injury risk is greater in more senior players. ...
... highly variable relative to positional demands, 17,18 ACWR-injury risks in American football have yet to be determined. This investigation will therefore examine workload injury risk relationships in NCAA football. ...
Article
Objectives: To determine injury risk-workload associations in collegiate American Football. Design: Retrospective analysis. Methods: Workload and injury data was recorded from 52 players during a full NCAA football season. Acute, chronic, and a range of acute:chronic workload ratios (ACWR: 7:14, 7:21 and 7:28 day) calculated using rolling and exponentially weighted moving averages (EWMA) were plotted against non-contact injuries (regardless of time lost or not) sustained within 3- and 7-days. Injury risks were also determined relative to position and experience. Results: 105 non-contact injuries (18 game- and 87 training-related) were observed with almost 40% sustained during the pre-season. 7-21 day EWMA ACWR's with a 3-day injury lag were most closely associated with injury (R2=0.54). Relative injury risks were >3× greater with high compared to moderate and low ratios and magnified when combined with low 21-day chronic workloads (injury probability=92.1%). Injury risks were similar across positions. 'Juniors' presented likely and possibly increased overall injury risk compared to 'Freshman' (RR: 1.94, CI 1.07-3.52) and 'Seniors' (RR: 1.7, CI 0.92-3.14), yet no specific ACWR - experience or - position interactions were identified. Conclusions: High injury rates during college football pre-season training may be associated with high acute loads. In-season injury risks were greatest with high ACWR and evident even when including (more common and less serious) non-time loss injuries. Substantially increased injury risks when low 21-day chronic workloads and concurrently high EWMA ACWR highlights the importance of load management for individuals with chronic game- (non-involved on game day) and or training (following injury) absences.
... Scientific studies on collegiate AF have grown exponentially since the first paper in 1969, leading to various avenues of scientific development in key areas from this time to the present day. These include injury prevention 3,4 , concussion 5 , return to play injury characteristics 6,7 , analysis of strength and conditioning [8][9][10][11] , overall health 12 and wellbeing and most recently the objective quantification of training and games [13][14][15] . ...
... G force) impacts, and defensive tackles (interior DL) reported significantly more heavy and very heavy (7.1-10 G force) impacts than other defensive positions 13 . These studies further our understanding of the demands imposed on players, which may form the basis for the design of position-specific monitoring and training in the preparation for the external load and impact forces performed in games. ...
Article
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Whilst there are various avenues for performance improvement within collegiate American football (AF), there is no comprehensive evaluation of the collective array of resources around performance, physical conditioning and injury and training/game characteristics to guide future research and inform practitioners. Accordingly, the aim of the present review was to provide a current examination of these areas within collegiate AF. Recent studies show that there is a wide range of body compositions and strength characteristics between players, which appear to be influenced by playing position, level of play, training history/programming and time of season. Collectively, game demands may require a combination of upper and lower body strength and power production, rapid acceleration (positive and negative), change of direction, high-running speed, high intensity and repetitive collisions and muscular strength endurance. These may be affected by the timing of, and between, plays and/or coaching style. AF players appear to possess limited nutrition and hydration practices, which may be disadvantageous to performance. AF injuries appear due to a multitude of factors: strength, movement quality, and previous injury whilst there is also potential for extrinsic factors such as playing surface type, travel, time of season, playing position and training load. Future proof of concept studies are required to determine the quantification of game demands with regards to game style, type of opposition and key performance indicators. Moreover, more research is required to understand the efficacy of recovery and nutrition interventions. Finally, the assessment of the relationship between external/internal load constructs and injury risk is warranted.
... The evident unpredictability of loads associated with decelerating rapidly also have hugely important implications for the management of load throughout the season, and return to sports participation programmes following injury (Verstegen et al., 2012;Wellman, Coad, Goulet, et al., 2017). ...
Thesis
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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.
... In college football, defensive backs displayed higher acceleration and deceleration values than other position groups. As a unit, defensive players experienced great acceleration-deceleration values (Wellman et al., 2017). Our prediction model found one acceleration factor and one deceleration factor as indicators of elevated CLEI risk. ...
Article
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Clinical prediction models are useful in addressing several orthopedic conditions with various cohorts. American football provides a good population for attempting to predict injuries due to their relatively high injury rate. Physical performance can be assessed a variety of ways using an assortment of different tests to assess a diverse set of metrics, which may include reaction time, speed, acceleration, and deceleration. Asymmetry, the difference between right and left performance has been identified as a possible risk factor for injury. The purpose of this study was to determine the whole-body reactive agility metrics that would identify Division I football players who were at elevated risk for core, and lower extremity injuries (CLEI). This cohort study utilized 177 Division I football players with a total of 57 CLEI suffered who were baseline tested prior to the season. Single-task and dual-task whole-body reactive agility movements in lateral and diagonal direction reacting to virtual reality targets were analyzed separately. Receiver operator characteristic (ROC) analyses narrowed the 34 original predictor variables to five variables. Logistic regression analysis determined the three strongest predictors of CLEI for this cohort to be: lateral agility acceleration asymmetry, lateral flanker deceleration asymmetry, and diagonal agility reaction time average. Univariable analysis found odds ratios to range from 1.98 to 2.75 for these predictors of CLEI. ROC analysis had an area under the curve of 0.702 for any combination of two or more risk factors produced an odds ratio of 5.5 for risk of CLEI. These results suggest an asymmetry of 8-15% on two of the identified metrics or a slowed reaction time of ≥0.787 s places someone at increased risk of injury. Sixty-three percent (36/57) of the players who sustained an injury had ≥2 positive predictors In spite of the recognized limitation, these finding support the belief that whole-body reactive agility performance can identify Division I football players who are at elevated risk for CLEI.
... In many published studies of workload monitoring, there is no mention of how missing workload data were handled, particularly for youth sports (Windt et al., 2018). In other studies, missing data were ignored or excluded from the analysis (Black et al., 2018;Curtis et al., 2018;DeWitt et al., 2018;Martín-García et al., 2018;Rago et al., 2019;Smpokos et al., 2018a;Smpokos et al., 2018b;Vahia et al., 2019;Wellman et al., 2017;Whitehead et al., 2019). While excluding incomplete cases is a simple way to handle missing data, complete case analyses can lead to biased estimates and large standard errors (Gelman and Hill, 2006;Van Buuren, 2018). ...
Article
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Missing data can influence calculations of accumulated athlete workload. The objectives were to identify the best single imputation methods and examine workload trends using multiple imputation. External (jumps per hour) and internal (rating of perceived exertion; RPE) workload were recorded for 93 (45 females, 48 males) high school basketball players throughout a season. Recorded data were simulated as missing and imputed using ten imputation methods based on the context of the individual, team and session. Both single imputation and machine learning methods were used to impute the simulated missing data. The difference between the imputed data and the actual workload values was computed as root mean squared error (RMSE). A generalized estimating equation determined the effect of imputation method on RMSE. Multiple imputation of the original dataset, with all known and actual missing workload data, was used to examine trends in longitudinal workload data. Following multiple imputation, a Pearson correlation evaluated the longitudinal association between jump count and sRPE over the season. A single imputation method based on the specific context of the session for which data are missing (team mean) was only outperformed by methods that combine information about the session and the individual (machine learning models). There was a significant and strong association between jump count and sRPE in the original data and imputed datasets using multiple imputation. The amount and nature of the missing data should be considered when choosing a method for single imputation of workload data in youth basketball. Multiple imputation using several predictor variables in a regression model can be used for analyses where workload is accumulated across an entire season.
... 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. ...
Article
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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.
... Practitioners should select specific exercises for offensive linesmen that target the development of the neuromuscular capabilities required to produce and attenuate the high forces associated with decelerating rapidly, whilst also ensuring a high level of perceptual-cognitive training that will harness the ability to skilfully apply braking forces during emergent and unpredictable situations. The evident unpredictability of loads associated with decelerating rapidly also have hugely important implications for the management of load throughout the season, and return to sports participation programmes following injury [103,104]. Similar to the high-intensity category, soccer demonstrated the highest (SMD = − 3.19) frequency of very high intensity decelerations compared to accelerations. The SMD ranged from very large (− 2.40 to − 2.79) in defenders (n = 24 vs. 7) and attackers (n = 16 vs. ...
Article
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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.
... Thus, in a collision dominant sport evidence suggest that collegiate AF players will also be required to run at high speeds with appropriate body mass to be competitive during collisions, and thus developing greater momentum characteristics will be a favourable quality amongst players involved in a greater amount of collisions During collisions AF players may experience impact forces (G) surpassing 10 G (73). Wellman et al. (73) quantified total impacts and G across 12 Division I games, reporting that the greatest number of collisions (>10 G) were experienced by the quarterback (13.6 ± 5.9) and running backs (12.3 ± 5.0) on the offensive team, while on the defensive team it was the defensive ends (13.2 ± 6.9) and linebackers (12.7 ± 7.4). Although total impacts for forces greater than >10 G were highest among those four positions, the wide receivers experienced the greatest number of recorded impacts (4,093 ± 791.6) across 12 Division I games. ...
Article
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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.
... Wearable microsensors are attractive to coaches because the physical demands of competition or training can be quantified with minimal burden to the athlete. Though training load monitoring is becoming more popular in American football (35)(36)(37), its use in conjunction with recovery status indicators among football players has not been well studied. This research is needed because external training load ...
Article
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The purpose of this study was to determine if recovery of cardiac-autonomic activity to baseline occurs between consecutive-day training sessions among positional groups of a collegiate football team during Spring camp. A secondary aim was to evaluate relationships between chronic (i.e., 4-week) HRV and training load parameters. Baseline HRV (lnRMSSD_BL) was compared with HRV following ~20 h of recovery prior to next-day training (lnRMSSDpost20) among positional groups comprised of SKILL (n = 11), MID-SKILL (n = 9) and LINEMEN (n = 5) with a linear mixed model and effect sizes (ES). Pearson and partial correlations were used to quantify relationships between chronic mean and coefficient of variation (CV) of lnRMSSD (lnRMSSD_chronic and lnRMSSDcv, respectively) with the mean and CV of PlayerLoad (PL_chronic and PL_cv, respectively). A position × time interaction was observed for lnRMSSD (p = 0.01). lnRMSSD_BL was higher than lnRMSSDpost20 for LINEMEN (p <0.01; ES = Large) while differences for SKILL and MID-SKILL were not statistically different (p >0.05). Players with greater body mass experienced larger reductions in lnRMSSD (r = -0.62, p <0.01). Longitudinally, lnRMSSDcv was significantly related to body mass (r = 0.48) and PL_chronic (r = -0.60). After adjusting for body mass, lnRMSSDcv and PL_chronic remained significantly related (r = -0.43). The ~20 h recovery time between training sessions on consecutive days may not be adequate for restoration of cardiac-parasympathetic activity to baseline among LINEMEN. Players with a lower chronic training load throughout camp experienced greater fluctuation in lnRMSSD (i.e., lnRMSSDcv) and vice-versa. Thus, a capacity for greater chronic workloads may be protective against perturbations in cardiac-autonomic homeostasis among American college football players.
... Recent studies (16,39,48) have added to our knowledge of player movement characteristics during National Collegiate Athletic Association (NCAA) Division I football competition providing an increased understanding of the positional movement profiles, including the quantification of sprint distances and high-intensity accelerations and decelerations, in addition to a basic understanding of exercise to rest ratios. An additional investigation (49) of NCAA Division I college football has revealed the frequency and intensity of impacts and rapid changes in direction and provided a quantification of the position-specific number and intensity of impacts per game. The movement patterns of NCAA Division I football players during competition using global positioning systems (GPS) technology have been reported (48); however, limited data (8) exist describing the movement profiles experienced by players during preseason training camp, that are synonymous with college football competition. ...
Article
The aims of the present study were to examine the movement demands of pre-season practice in National Collegiate Athletic Association (NCAA) division I college football players using portable global positioning system (GPS) technology and to assess perceived wellness associated with pre-season practice to determine if GPS-derived variables from the preceding day influence perceived wellness the following day. Twenty-nine players were monitored using GPS receivers (Catapult Innovations, Melbourne, Australia) during 20 pre-season practices. Individual observations (n=550) were divided into offensive and defensive position groups. Movement variables including low-, medium-, high-intensity, and sprint distance, player load, and acceleration and deceleration distance were assessed. Perceived wellness ratings (n=469) were examined using a questionnaire which assessed fatigue, soreness, sleep quality, sleep quantity, stress, and mood. A one-way ANOVA for positional movement demands, and multi-level regressions for wellness measures were used, followed by post-hoc testing to evaluate the relational significance between categorical outcomes of perceived wellness scores and movement variables. Results demonstrated significantly (p<0.05) greater total, high-intensity, and sprint distance, along with greater acceleration and deceleration distances for the DB and WR position groups compared to their respective offensive and defensive counterparts. Significant (p<0.05) differences in movement variables were demonstrated for individuals who responded more or less favorably on each of the six factors of perceived wellness. Data from the present study provide novel quantification of the position-specific physical demands and perceived wellness associated with college football pre-season practice. Results support the use of position-specific training and individual monitoring of college football players.
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Wearable technologies are often indicated as tools that can enable the in-field collection of quantitative biomechanical data, unobtrusively, for extended periods of time, and with few spatial limitations. Despite many claims about their potential for impact in the area of injury prevention and management, there seems to be little attention to grounding this potential in biomechanical research linking quantities from wearables to musculoskeletal injuries, and to assessing the readiness of these biomechanical approaches for being implemented in real practice. We performed a systematic scoping review to characterise and critically analyse the state of the art of research using wearable technologies to study musculoskeletal injuries in sport from a biomechanical perspective. A total of 4952 articles were retrieved from the Web of Science, Scopus, and PubMed databases; 165 were included. Multiple study features—such as research design, scope, experimental settings, and applied context—were summarised and assessed. We also proposed an injury-research readiness classification tool to gauge the maturity of biomechanical approaches using wearables. Five main conclusions emerged from this review, which we used as a springboard to propose guidelines and good practices for future research and dissemination in the field.
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Thesis
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.
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