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Internal and External Training Load: 15 Years On
Abstract
Exercise is a stressor that induces various psychophysiological responses, which mediate cellular adaptations in many organ systems. To maximize this adaptive response, coaches and scientists need to control the stress applied to the athlete at the individual level. To achieve this, precise control and manipulation of the training load are required. In 2003, the authors introduced a theoretical framework to define and conceptualize the measurable constructs of the training process. They described training load as having 2 measurable components: internal and external load. The aim of this commentary is to extend, clarify, and refine both the theoretical framework and the definitions of internal and external training load to avoid misinterpretation of this concept.
... Time-motion analysis and physiological monitoring have frequently been used to analyse the movement patterns and workloads imposed by the match play and training sessions in soccer [1]. According to previous literature, the workload can be differentiated into internal and external loads [2]. In that sense, Global Positioning System (GPS) technology is commonly used to monitor and record external load in professional soccer [3]. ...
... central defenders (2), fullbacks (2), midfielders (4), and forwards (2). ...
... central defenders (2), fullbacks (2), midfielders (4), and forwards (2). ...
... illness prevention [1][2][3][4][5]. Training and competition load of athletes can be defined as input variable that coaches intending to elicit certain training induced adaptations (as this term including competitions) in their athletes usually try to manipulate [6]. ...
... Training and competition load of athletes can be defined as input variable that coaches intending to elicit certain training induced adaptations (as this term including competitions) in their athletes usually try to manipulate [6]. Measures of training or competition load can be categorized as either external or internal, depending on whether they refer to measurable aspects occurring externally or internally to the athlete [2,4,5]. External loads (EL) are objective measures of the work performed by an athlete during training or competition. ...
... External loads (EL) are objective measures of the work performed by an athlete during training or competition. In contrast, internal loads (IL) refer to the relative biological (both physiological and psychological) stressors imposed on the athlete during training or competition [2,4]. ...
Despite load monitoring being considered an integral part of targeted performance management, including injury and illness prevention, there is currently no consensus of an effective monitoring system in professional soccer. Thus, the aims were to apply an integrative load monitoring approach, previously established in rink-hockey, in professional soccer; extend this approach with further data (Short Recovery and Stress Scale); assess this (extended) approach, thereby further evaluating the relationship between the used external load (EL) measures (total distance, distance above 55% and 70% of individual maximal speed, number of accelerations and decelerations > 4 m/s2, total loading) and the internal load (IL) measure session rate of perceived exertion training load (sRPE-TL) as well as between the used EL measures and sRPE. This retrospective observational cohort study analyzed data from a Swiss team collected over a 14 week-period during the 2021/22 season. Based on our findings, the integrative approach tested proved to be an applicable load monitoring tool in professional soccer, placing players on a fitness-fatigue continuum throughout the different microcycle sessions without using tests, thus providing relevant information to individually tailor training programs. sRPE-TL (ρ [95% CI] = .55 [.51 to .59] to .87 [.85 to .88]; all p < .001) better reflected the EL experienced by players than sRPE (ρ [95% CI] = .45 [.40 to .50] to .71 [.69 to .75]; all p < .001) supporting the definition of sRPE-TL as a measure of IL. However, for even stronger relevance of the tested tool, further research is warranted, especially to ascertain its sensitivity and determine an optimal selection of EL and IL measures. In sum, the present data clearly demonstrate the importance of load management taking place at an individual level, even within team structures, thereby analyzing a set of both EL and IL measures.
... TL, in the framework of sport training, has been defined "as a higher-order construct reflecting the amount of physical training that is actually performed and experienced by the athletes" (56). In general, it is scheduled to induce the desired training responses that are supposed to be related to performance (32,46). Two subdimensions called IL and external (training) load (EL) (46,54) characterized the TL. ...
... In general, it is scheduled to induce the desired training responses that are supposed to be related to performance (32,46). Two subdimensions called IL and external (training) load (EL) (46,54) characterized the TL. Commonly, training prescription refers only to the EL (32,46) and, in particular, to total distance, range of speed covered, accelerations, and metabolic power (78). ...
... Two subdimensions called IL and external (training) load (EL) (46,54) characterized the TL. Commonly, training prescription refers only to the EL (32,46) and, in particular, to total distance, range of speed covered, accelerations, and metabolic power (78). External load stimuli induces internal responses on psychological, physiological, biochemical, metabolic, and biomechanical domains (54,55,78,81). ...
Pillitteri, G, Clemente, FM, Petrucci, M, Rossi, A, Bellafiore, M, Bianco, A, Palma, A, and Battaglia, G. Toward a new conceptual approach to "intensity" in soccer player's monitoring: A narrative review. J Strength Cond Res 37(9): 1896-1911, 2023-In the last decade, monitoring physiological and match-related demands in soccer has become an increasingly common practice in sports sciences. One of the great challenges during monitoring process is the identification of key indicators that permit to generalize evidence and sustain decision-making process during training prescription. Actually, one of the major debates in the scientific community and among practitioners is the identification of the "intensity" concept. Defining a given training session or exercise based on "intensity" is difficult due to the fact that a huge amount of indicators are available (related both to the performed activities and to the athletes' psychophysiological responses). These indicators can lead to specific outcomes with different interpretations. The current narrative review aims to discuss the different measures approaches used in soccer to describe the intensity for both internal and external demands. In addition, a second purpose of this review is to propose general recommendations for combining intensity indicators with the aim of defining an overall intensity score of a training session or drill.
... The TL informs coaches of the physical and psychological stressors imposed on athletes during training and is categorised into two theoretical constructs: internal and external [1]. The internal TL captures the individual response to a given training stimulus and consists of objective physiological measures such as the heart rate (HR) or subjective psychophysiological methods such as the session rating of perceived exertion (sRPE) [2]. In contrast, the external load is the physical work completed by the individual. ...
... VO 2max both in the composite data set and at the individual level for all participants. These findings align with the previous literature, suggesting that both HR and RPE are reliable indicators of intensity and load in the context of load monitoring [2,34,35]. It is important to emphasise that the load monitoring approaches employed in this study captured distinct parameters of the load from the participants, as exemplified through the varying degrees of correlation with % . ...
... VO 2max for the grouped data. This highlights the different parameters that internal and external player monitoring systems capture during exercise [2,25,36]. The type of treadmill running test used in the present study may have negatively influenced the relationship between PL and % . ...
The purpose of this study was two-fold: (1) to determine the sensitivity of the sEMG shorts-derived training load (sEMG-TL) during different running speeds; and (2) to investigate the relationship between the oxygen consumption, heart rate (HR), rating of perceived exertion (RPE), accelerometry-based PlayerLoadTM (PL), and sEMG-TL during a running maximum oxygen uptake (V˙O2max) test. The study investigated ten healthy participants. On day one, participants performed a three-speed treadmill test at 8, 10, and 12 km·h−1 for 2 min at each speed. On day two, participants performed a V˙O2max test. Analysis of variance found significant differences in sEMG-TL at all three speeds (p < 0.05). A significantly weak positive relationship between sEMG-TL and %V˙O2max (r = 0.31, p < 0.05) was established, while significantly strong relationships for 8 out of 10 participants at the individual level (r = 0.72–0.97, p < 0.05) were found. Meanwhile, the accelerometry PL was not significantly related to %V˙O2max (p > 0.05) and only demonstrated significant correlations in 3 out of 10 participants at the individual level. Therefore, the sEMG shorts-derived training load was sensitive in detecting a work rate difference of at least 2 km·h−1. sEMG-TL may be an acceptable metric for the measurement of internal loads and could potentially be used as a surrogate for oxygen consumption.
... Monitoring load is often grouped into two categories: (i) internal load and (ii) external load. 17 The external load is related to the physical, locomotor, and/ or mechanical demands (e.g. distance covered at different speed thresholds, accelerations, and decelerations) that a given training drill imposes on the player. ...
... distance covered at different speed thresholds, accelerations, and decelerations) that a given training drill imposes on the player. 17 The internal load represents the psychophysiological responses (e.g. heart rate, rate of perceived exertion) associated with the corresponding external load. ...
... heart rate, rate of perceived exertion) associated with the corresponding external load. 17 Although related, the magnitude of the relationship between external and internal load measures is variabledependent and mode training-dependent. For example, the rate of perceived effort multiplied by the session time (sRPE) or training impulse calculated using heart rate commonly shows a strong association with total distance or frequency of accelerations, although not with sprinting or high-speed running distances. ...
Acute: chronic workload ratio (ACWR) and training monotony have been criticized as injury risk predictors. Therefore, the use of intensity measures should be oriented to understand the variations of intensity across the season. The aim of this systematic review is to summarize the main evidence about the ACWR and training monotony variations over the season in professional soccer players. The search was made in PubMed, SPORTDiscus, and FECYT according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. From the 225 studies initially identified, 27 were fully reviewed, and their outcome measures were extracted and analyzed. Existing literature revealed a variety of designs, ACWR and training monotony ranges, variables assessed and durations of the studies. Overall, the range values for ACWR were 0.4–3.39 AU, while those focused on monotony were 0.49–5.7 AU. Regarding ACWR, the ratios located around 0.85-1.25 could predict lower risk values and ratios around ≥ 1.50 could predict higher risk values. On the contrary, with respect to training monotony, the ratios are approximately between 0.5 to 2.00 (low values in the preseason and low competition weeks and high values when soccer players are in highly scheduled competition weeks). Nevertheless, ACWR and training monotony methods should be addressed and considered based on their real value before using this indicator to reduce injury risk. In fact, the data did not conclusively define injured and non-injured players. For this reason, utilizing standardized approaches will allow for more precise conclusions about professional soccer players.
... The choice of intensity is a critical factor in determining the results of training processes, ranging from simple to complex, easy to difficult, and low to high load. Furthermore, the RPE is used to complement the control and prescription of the intensity, determining the internal load of the exercise [75]. When eccentric exercise is related to concentric 1RM (sub-maximal, maximal, and supra-maximal), the intensity should range between 75 and 140%, and the rest between series should range from 45 to 240 s [27]. ...
... This complexity is closely related to eccentric exercise intensity, where the easiest or least complex exercises should start any eccentric training program. In addition, it integrates all previously described training load components (i.e., intensity, volume, rest, preparation, order, and technical execution), which could directly impact the subject's internal load [75]. The number of joints involved also aligns with exercise complexity. ...
... eccentric training program. In addition, it integrates all previously described training load components (i.e., intensity, volume, rest, preparation, order, and technical execution), which could directly impact the subject's internal load [75]. The number of joints involved also aligns with exercise complexity. ...
Eccentric resistance training that focuses on the lengthening phase of muscle actions has gained attention for its potential to enhance muscle strength, power, and performance (among others). This review presents a methodological proposal for classifying eccentric exercises based on complexity, objectives, methods, and intensity. We discuss the rationale and physiological implications of eccentric training, considering its benefits and risks. The proposed classification system considers exercise complexity and categorizing exercises by technical requirements and joint involvement, accommodating various skill levels. Additionally, training objectives are addressed, including (i) Sports Rehabilitation and Return To Sport, (ii) Muscle Development, (iii) Injury Prevention, (iv) Special Populations, and (v) Sporting Performance, proposing exercise selection with desired outcomes. The review also highlights various eccentric training methods, such as tempo, isoinertial, plyometrics, and moderate eccentric load, each with different benefits. The classification system also integrates intensity levels, allowing for progressive overload and individualized adjustments. This methodological proposal provides a framework for organizing eccentric resistance training programs, facilitating exercise selection, program design, and progression. Furthermore, it assists trainers, coaches, and professionals in optimizing eccentric training’s benefits, promoting advancements in research and practical application. In conclusion, this methodological proposal offers a systematic approach for classifying eccentric exercises based on complexity, objectives, methods, and intensity. It enhances exercise selection, program design, and progression in eccentric resistance training according to training objectives and desired outcomes.
... Control of fatigue in athletes is very important in terms of achieving optimum performance (Ament & Verkerke, 2009;Bourdon et al., 2017;Kellmann et al., 2018). In order to control fatigue in athletes and to continue their training in the desired dose-response range, the monitoring of loads created by the training on the athletes is of great importance (Impellizzeri et al., 2019;Jones et al., 2017). Along with the monitoring of training loads, it is critical to monitor the daily well-being status of the athletes (Bourdon et al., 2017;Eckard et al., 2018). ...
... All the stress factors that occur in athletes kept in balance to prevent the athletes from being exposed to insufficient training and protect them from injuries (Bourdon et al., 2017;Eckard et al., 2018;Jones et al., 2017). The methods used to measure training load are large-scale, and these methods differ according to the demands of the trainers (Bourdon et al., 2017;Eckard et al., 2018;Impellizzeri et al., 2019). A common method of assessing internal load in team sports is by collecting each athlete's rating of perceived exertion, which a then multiplied by session duration to represent the internal load (session rating of perceived exertion, sRPE) (Foster, 1998;Foster et al., 2001;Herman et al., 2006). ...
... In many sports branches, a great number of studies have been conducted on various subjects related to the training load, neuromuscular fatigue, and well-being of athletes (Bourdon et al., 2017;Clemente et al., 2017Clemente et al., , 2019Clemente et al., , 2020Eckard et al., 2018;Govus et al., 2018;Hills & Rogerson, 2018;Impellizzeri et al., 2019;Jones et al., 2017;Nilsson et al., 2002;Nobari et al., 2020;Sawczuk et al., 2018aSawczuk et al., , 2018bSlimani et al., 2017). However, although wrestling has been among the main branches of the Olympics for many years, research regarding the training load, neuromuscular fatigue, and well-being status of wrestlers in the related literature is relatively limited. ...
Purpose: This study investigated acute workload (wAW), chronic workload (wCW), acute: chronic workload ratio (wACWR), training monotony (wTM), perceived load training strain indicators (wTS), and countermove- ment jump (CMJ) as indicators of wellness in one season and defined weekly variations. In addition, we analyzed the relationships between training load measurements and weekly reports. Methods: 16 elite young wrestlers were monitored daily with individual observations for 46 consecutive weeks throughout the season. Training load was obtained using the session rating of perceived effort. wSleep, wStress, wFatigue & wMuscle Soreness well-being were monitored daily using the Hooper index. Results: As a result of the analysis, it was found that there is a moderate relationship (r = 0.51, p = .003) between ACWR and w mean load (A.U.) and a high relationship (r = 0.81, p < .001) between monotony and strain. Conclusion: All variables other than ACWR, w mean load, strain, and monotony presented small and statistically insignificant relationships. These results provide coaches and practitioners with new insights into perceived loads and health changes during a season at the elite youth level.
... TL measures were described in the literature as external and internal TL measures [18], even though they are currently questioned [19]. External TL corresponds to the physical work required in a training session. ...
... External TL corresponds to the physical work required in a training session. On the other hand, the internal TL is the psychophysiological response to the physical work [18]. Commonly, running athletes measure their TL based on the distance covered (e.g., external TL). ...
... These can be noted in our study, since W-DIST presented lower correlations between W-RPE or W-TRIMP (external TL compared to internal TL), compared to the correlation between W-RPE and W-TRIMP (two measures of internal TL). However, even presenting differences, internal and external TL measures are coupled to each other [4,18], explaining the large correlation between W-DIST and W-RPE or W-TRIMP. ...
The development of the rating of perceived exertion (RPE) enables the easy assessment of runners’ training strain as well as training load (TL). However, the long-term and retrospective validity of TL assessment using RPE scales still needs further investigation. Therefore, this study examined the validity of weekly and monthly ratings of perceived exertion (W-RPE, M-RPE) in assessing TL in runners. Healthy adult runners (n=53) rated perceived exertion using the modified category-ratio 10 (CR-10) scale for each week of a four-week period, as well as for the month, considering the four-week period. CR-10 for the week and the month were multiplied by the total training time of the week and month, respectively, to assess the W-RPE and M-RPE. Training impulse (TRIMP) was used as the criterion measure. The results indicated that the W-RPE and M-RPE may be used for monitoring TL during prolonged periods, presenting a very large correlations with the criterion measure.
... Knowing what soccer players physically need to be prepared for requires a solid understanding of the sport-specific demands (6)(7)(8)(9). Measures of load, both in training and matches, can be categorized as either external or internal, depending on whether they refer to measurable aspects occurring externally or internally to the athlete (10)(11)(12). ...
... External loads are objective measures of the work performed by an athlete. In contrast, internal loads refer to the relative biological (both physiological and psychological) stressors imposed on the athlete (10,11). Nowadays, there are a number of methods for measuring training and match loads (10,(12)(13)(14). ...
... In order to optimally develop the physical capabilities of soccer players, training stimuli need to be applied individually even within a team environment (10,(13)(14)(15)(16). To individually tailor training programs, maximizing positive physiological adaptation and simultaneously preventing injury and illness, careful load monitoring is required (10)(11)(12)(13)17). Within load monitoring, employing an integrated load monitoring approach (i.e., rigorous and consistent, combining both external and internal loads) seems crucial (10)(11)(12)(13)15). ...
Careful load management is needed to optimize the physical capacity, a key performance component, of soccer players. The training load of soccer players is often expressed as a percentage of match load. However, no study has yet evaluated how training match load ratios are affected by using either a player-specific or position-specific reference for match load. Therefore, this study aimed to compare training match load ratios of professional soccer players per day of a microcycle with match load being player-specific and position-specific, respectively. Additionally, the load that players typically experience per day of a microcycle and its variation should be analyzed. Therefore, a retrospective observational cohort study was conducted over a 14-month period, analyzing 11 external load measures during sessions of 20 players belonging to a team competing in the highest Swiss league. Within a microcycle, typical full matches presented a unique load for players, and they experienced higher training loads on days with a greater temporal distance to a match. Load variation proved to be highly associated with the day in a microcycle and the load measure. Substantial differences in typical load were evident in (i) trainings between players, (ii) matches both between players and positions, and (iii) training match load ratios when using player-specific or position-specific match references. The importance of individual load management in professional soccer was reaffirmed. When consulting training match load ratios for that purpose, one should be aware of the aim, select appropriate reference values depending on it, and interpret the ratios accurately to finally draw adequate conclusions.
... Ultimately, it is the internal load that determines the training response or training effect. Additionally, this response is influenced by an individual's characteristics such as age, weight, and nutrition, alongside external factors such as the training environment (Jeffries et al., 2021, Impellizzeri et al., 2019) Jeffries et al. (2021 proposed that positive and negative training effects could be categorised via performance measures, physiological measures, subjective measures or other measures. ...
... Whilst this route of investigation is common, it has been suggested that current practices relating load monitoring with injury are lacking in substantial evidence, possibly due to the shortcomings of available univariate load metrics (Kalkhoven et al., 2021) Load and the subsequent adaptations generated, can be characterised as being either physiological or biomechanical (Vanrenterghem et al., 2017). Features of training load describing the magnitude and amount of the physical work are considered the external load (Impellizzeri et al., 2019, Vanrenterghem et al., 2017, whereas, features describing the resultant physiological and biomechanical response are characterised as the internal load (Impellizzeri et al., 2019, Vanrenterghem et al., 2017. Generally, practitioners monitor prescribed physical work, which is represented by external load, alongside the players response which is characterised as the internal load (Vanrenterghem et al., 2017, Impellizzeri et al., 2019. ...
... Whilst this route of investigation is common, it has been suggested that current practices relating load monitoring with injury are lacking in substantial evidence, possibly due to the shortcomings of available univariate load metrics (Kalkhoven et al., 2021) Load and the subsequent adaptations generated, can be characterised as being either physiological or biomechanical (Vanrenterghem et al., 2017). Features of training load describing the magnitude and amount of the physical work are considered the external load (Impellizzeri et al., 2019, Vanrenterghem et al., 2017, whereas, features describing the resultant physiological and biomechanical response are characterised as the internal load (Impellizzeri et al., 2019, Vanrenterghem et al., 2017. Generally, practitioners monitor prescribed physical work, which is represented by external load, alongside the players response which is characterised as the internal load (Vanrenterghem et al., 2017, Impellizzeri et al., 2019. ...
... Workloads have been recently highlighted as an important factor in the injury aetiology model (Windt et al., 2017). Workload monitoring and management is a topic that has gained interest, to examine the relationship between fitness, fatigue and injury (Impellizzeri et al., 2019). Most authors investigated the relationship between injury risk/odds and internal workload using cumulative loads and derived metrics as the ACWR Soligard et al., 2016). ...
... In football, the internal load is usually used for the on-field training session, but it can also be reported regarding gym sessions, both independently or/and in conjunction (Bourdon et al., 2017;Impellizzeri et al., 2019;Lockie et al., 2012). ...
Purpose: (A) To characterize the epidemiology of injury at an elite youth football academy. (B) To investigate the differences between injured and non-injured elite youth footballers in musculoskeletal screening and workload variables, for lower extremity non-contact soft tissue injuries; and for groin located and muscular type injuries. Methods: (A) Prospective analysis of time-loss injuries from one hundred eighty-four elite youth male football players (age: 16.2±2.2 yrs) in a Portuguese academy (U14-U23) during the 2019-2020 season. Injury frequency, burden, incidence, and patterns were calculated. (B) A match-paired case approach was used to investigate differences between injured (n= 56) and non-injured (n= 56) groups for preseason musculoskeletal screening variables (passive knee fall out (PKFO), adductor squeeze (ASQZ), adductor squeeze bodyweight ratio (ASQZ/BWratio), dorsiflexion lunge test (DLT); single-leg countermovement jump (SL-CMJ)) and workload variables before injury (Cumulative sum; monotony; strain; acute: chronic workload ratio (ACWR); week to week change) using internal load (sRPE). Groin located injuries (n=14 vs n=14) and muscular injuries (n= 27 vs n=27) were also investigated. Results: (A) A total of 129 time-loss injuries were observed. Injuries were more frequent in training but had a higher incidence and burden rate in match context. Overall incidence was 2.7 per 1000 hours, and burden rate 59.3 days lost per 1000 hours. The thigh was the most frequent location. Quadriceps was the most injured muscle group, mainly by sprinting and shooting mechanisms. Moderate injuries were more frequent, with a mean of 21.9±28 days lost to injury. Under 17 was the most affected team, with the highest-burden cross-product. (B) ASQZ/BWratio was higher in non-injured players compared with injured players for lower body non-contact (0.64±0.11 vs 0.59±0.11; p=0.025) and groin injuries (0.64±0.08 vs 0.54±0.11; p=0.007). No other workload and musculoskeletal variable had significant differences between groups. Conclusions: Characteristics of injury incidence, burden, and patterns differ among squads in elite youth football. Non-contact injuries in pre-adolescent players remain frequent, representing a threat to the young football player's safe development. ASQZ/BWratio could be used to identify risk of injury for lower body non-contact and groin injuries. More data is necessary to clarify which musculoskeletal and workload factors are relevant to youth football injury occurrence.
... De manière similaire, les termes de CE externe et interne sont largement utilisés dans la littérature, il semble pourtant que les mesures actuelles de CE externe ne présentent pas le caractère multidimensionnel du concept de CE. En effet, les données de CE externe concernent principalement le volume d'exercice et ne sont pas combinées aux autres variables [22]. Les volumes réalisés dans des plages d'intensité sont également utilisés pour exprimer la CE externe, mais dans ce cas, ils ne quantifient pas la dose F. Desgorces, A. Sedeaud, J.-F. ...
... Les mesures de CE interne sont souvent associées aux méthodes de quantifications basées sur des paramètres physiologiques (ex., fréquence cardiaque). Cela amène quelques auteurs à considérer que la CE interne prend en compte la réponse individuelle à l'exercice [22]. Il semble pourtant que les mesures physiologiques sont utilisées par les méthodes de quantification de la CE en tant qu'indicateurs d'intensité et non comme réponse de l'organisme. ...
... Physiological demands were considered as any heart rate (HR) and derived calculations (eg, mean HR, peak HR, HR percentages, and zones) as well as blood lactate or other biochemical internal response parameters. [17][18][19] Perceptual demands referred to ratings of perceived exertion (RPE) and derived calculations (session RPE load). [17][18][19][20] Technical-tactical demands were intended as relevant notational analysis variables used in basketball, such as shooting statistics (ie, field goals, free throws, percentages, and efficiency indicators), passes and assists, rebounds, turnovers, and tactical indicators such as count, frequency, types, and effectiveness of ball possessions and tactical actions (ie, ball screens, number of players involved, and court location of plays). ...
... [17][18][19] Perceptual demands referred to ratings of perceived exertion (RPE) and derived calculations (session RPE load). [17][18][19][20] Technical-tactical demands were intended as relevant notational analysis variables used in basketball, such as shooting statistics (ie, field goals, free throws, percentages, and efficiency indicators), passes and assists, rebounds, turnovers, and tactical indicators such as count, frequency, types, and effectiveness of ball possessions and tactical actions (ie, ball screens, number of players involved, and court location of plays). 21 Variables were coded according to players' sex (male or female) and, when applicable, competition phase (qualification rounds or final rounds, including quarter-finals, semifinals, and final games), and winning and losing teams (KPIs). ...
Purpose: To systematically review the physical, physiological, perceptual, and technical–tactical demands of official 3 × 3
basketball games.
Methods: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines were followed. Three electronic databases (PubMed, Scopus, and Web of Science) were systematically searched to identify studies assessing physical, physiological, perceptual, and technical–tactical demands of 3 × 3 games. Data were also coded according to player’s sex and tournament phases. Quality assessment of the included studies was performed using a modified Downs and
Black checklist.
Results: Thirteen articles were finally included, with a mean quality of 8.6 (1.1) out of 11. 3 × 3 basketball games have an intermittent profile (1:1 work–rest ratio), with a duration of ∼15 minutes, and are characterized by short (6–8 s) ball possessions, and considerable physical (17–33 accelerations, 24–44 decelerations, 62–94 changes of directions, and 17–24 jumps per game) and physiological (lactate: ∼6.2 mmol·L−1) demands. Overall, the game performance profile is similar in males and
females, with minor changes happening across tournament phases. Several key technical–tactical indicators were identified as discriminating winning and losing teams, such as better shooting and defensive efficiency, low number of turnovers, and implementing tactical actions involving more players, passing first, and ending possessions with shots from outside of the arch from the top of the key. Conclusions: 3 × 3 basketball is an intermittent, physically demanding sport characterized by quick plays and specific tactical constraints. This review provides information which should be considered by performance staff to improve training prescription, game tactical plans, and for better player selection and talent identification.
... TL can describe the physiological response to exercise (ie, internal TL) or the physical work that is performed (ie, external TL). 25 There are many ways to measure internal and external TLs. Recall and schedules/timetables can be used to assess training volume, journals and questionnaires can be used to assess self-reported ratings of perceived exertion (RPE), and wearable technology such WHAT IS ALREADY KNOWN ON THIS TOPIC ⇒ Training load tells us how much and how hard a dancer is working. ...
... Tools used to capture TL in dance TL helps dance science practitioners understand how much (ie, volume and frequency) and/or how hard (ie, intensity) dancers are working over a defined period of time across different session types. 25 In this review, the most commonly used tools to capture TL were hours of dance, heart rate and portable metabolic systems. While video analysis was first used in dance in 2009, no studies using this tool have been conducted since 2011 to quantify TL. ...
Dance is a popular physical activity. Increased dance training has been associated with an increased risk of injury. Given the established association between training load (TL) and injury in sport, knowledge of how TL is currently being measured in dance is critical. The objective of this study is to summarise published literature examining TL monitoring in dance settings. Six prominent databases (CINAHL, EMBASE, Medline, ProQuest, Scopus, SportDiscus) were searched and nine dance-specific journals were handsearched up to May 2022. Selected studies met inclusion criteria, where original TL data were collected from at least one dancer in a class, rehearsal and/or performance. Studies were excluded if TL was not captured in a dance class, rehearsal or performance. Two reviewers independently assessed each record for inclusion at title, abstract and full-text screening stages. Study quality was assessed using Joanna Briggs Institute Critical Appraisal Tool checklists for each study design. The 199 included studies reported on female dancers (61%), ballet genre (55%) and the professional level (31%). Dance hours were the most common tool used to measure TL (90%), followed by heart rate (20%), and portable metabolic systems (9%). The most common metric for each tool was mean weekly hours (n=381; median=9.5 hours, range=0.2–48.7 hours), mean heart rate (n=143) and mean oxygen consumption (n=93). Further research on TL is needed in dance, including a consensus on what tools and metrics are best suited for TL monitoring in dance.
... These parameters are very important to assess acute (A) and chronic (C) training overload and their relationship (A/C ratio), as they are strongly related to work production capacity, as well as the relative risk of injuries triggered by the training session (25). ...
... The main internal load control parameters used due to their low cost and easy access are subjective rate of perceived exertion (RPE), LOAD (RPE x time), visual analogue scale (VAS) for muscle pain, blood lactate concentration (BLC), training impulse (TRIMP) and the profile of the autonomic nervous system, determined by heart rate variability (HRV) (25). ...
The aim of the present study was to evaluate the effects of acute β-alanine supplementation on the rate of perceived exertion, training impulse and heart rate variability during high intensity functional training. Twelve trained men (age: 22.0 ± 5.0 years old; body mass index: 23.6 ± 4.2 Kg/m2; fat mass: 9.8 ± 2.3; VO2max: 54.0 ± 4.5 mL/kg/min) participated in the present study. At the first visit to the training center, they performed a cardiopulmonary exercise test in the rowing ergometer to determine the maximum oxygen consumption. At the two subsequent visits, participants were randomized as-signed to the following conditions: a) placebo supplementation and b) 6.4g of β-alanine supple-mentation. The training protocol adopted was to execute the maximal number of repetitions of 5 pull-ups, 10 push-ups, and 15 squats per round in 20 minutes. Simultaneously, the following training load parameters were measured and then also compared during the two experimental conditions: session load (SL), training impulse (TRIMP), blood lactate concentration (BLC) and heart rate variability (HRV). β-alanine supplementation increased performance (p <0.05) and reduced BLC (p <0.05). Additionally, the internal training load parameters showed strong correlations with performance after β-alanine supplementation (SL: r=0.80, p <0.01; TRIMP: r=0.80, p <0.01; and HRV: r=0.79, p <0.01). Therefore, β-alanine supplementation may increase performance in high intensity functional fitness training.
... The primary goal of athlete monitoring systems is to monitor training load and the athletes' responses to training and competition stress to inform decision making on recovery and availability for subsequent training and competition (Bourdon et al., 2017). Importantly, an intricate understanding of the stress on athletes is fundamental to the subtle manipulation of training load to maximise favourable and functional adaptations to maximise performance (Impellizzeri et al., 2019). ...
... Often the difficulties with monitoring team sport athletes in particular, is the individual variability between athletes in their response to modifiable (health, sleep and training status) and non-modifiable (genetics, weather, and pressure and expectation from media and supporters) factors (Impellizzeri et al., 2019). Indeed, the prescription of the identical training load for one athlete may evoke a completely different internal, psychophysiological response in other athletes from the same team (Bouchard et al., 2011;Mann et al., 2014;Smith, 2003). ...
This systematic review and meta-analysis evaluated the validity of tests / markers of athletic readiness to predict physical performance in elite team and individual sport athletes. Ovid MEDLINE, Embase, Emcare, Scopus and SPORT Discus databases were searched from inception until 15 March 2023. Included articles examined physiological and psychological tests / markers of athletic readiness prior to a physical performance measure. 165 studies were included in the systematic review and 27 studies included in the meta-analysis. 20 markers / tests of athletic readiness were identified, of which five were meta-analysed. Countermovement jump (CMJ) jump height had a large correlation with improved 10m sprint speed / time (r = 0.69; p = .00), but not maximal velocity (r = 0.46; p = .57). Non-significant correlations were observed for peak power (r = 0.13; p = .87) and jump height (r = 0.70; p = .17) from squat jump, and 10m sprint speed / time. CMJ jump height (r = 0.38; p = .41) and salivary cortisol (r = -0.01; p = .99) did not correlate with total distance. Sub-maximal exercise heart rate (r = -0.65; p = .47) and heart rate variability (r = 0.66; p = .31) did not correlate with Yo-Yo Intermittent Recovery Test 1 performance. No correlation was observed between blood C-reactive protein and competition load (r = 0.33; p = .89). CMJ jump height can predict sprint and acceleration qualities in elite athletes. The validity of the other readiness tests / markers meta-analysed warrants further investigation.
... Some technological limitations (e.g., the use of portable thoracic bands especially during official matches) or some contextual limitations (e.g., athletes buy-in to collect rate of perceived exertion after each drill, etc.) negatively affected the use of internal load assessment tools in present study. However, coupling external load with internal load metrics may warrant a better understanding of drills demands (Impellizzeri et al., 2019). Second, individualizing the speed thresholds using physiological individual profile and/or individual maximal sprinting speed (Hunter et al., 2015) may help to further improve the understanding of the locomotor and physiological demands imposed on each player during different drills (Impellizzeri et al., 2019). ...
... However, coupling external load with internal load metrics may warrant a better understanding of drills demands (Impellizzeri et al., 2019). Second, individualizing the speed thresholds using physiological individual profile and/or individual maximal sprinting speed (Hunter et al., 2015) may help to further improve the understanding of the locomotor and physiological demands imposed on each player during different drills (Impellizzeri et al., 2019). Thirdly, several formats of ball drills differing for number of players, pitch sizes, rules modifications, etc. may lead to different results due to the typical highvariability in the locomotor demands during soccer-specific drills (Ade et al., 2014;Clemente, Praca, et al., 2019;Los Arcos et al., 2014;Riboli, Dellal, et al., 2022;Younesi et al., 2021); moreover, we highlight that this is a team-study and the current results could be also possibly affected by the variability due to athletes' characteristics, coaches' style of play, etc. Lastly, future studies may investigate how replicating or surpassing locomotor peak demands in specific drill formats may influence the peak locomotor demands during match-play. ...
To compare the locomotor demands of several ball/running drills with the official match peak, locomotor demands determined across different time-windows of the same duration in top-class male soccer players (n = 40). Total distance (TD), high-speed running (HSR, 15-20 km⋅h −1), very high-speed running (VHSR, 20-24 km⋅h −1), sprint and acceleration+deceleration (Acc+Dec >±3 m⋅s −2) distances were measured during training and official matches. A total of 9372 individual observations were classified as technical-tactical drills, small-sided games (SSGs), super-SSGs (pitch-area >340 m 2 ·player), SSGs with rules modifications (SSG modified), individual positional drills or running drills. The relative (m·min −1) TD, HSR, VHSR, sprint and Acc+Dec were compared with the peak locomotor demands determined during official matches across different time-windows (1, 2, 3, 4 and 5-min). Individual position-specific drill, super-SSGs, SSG modified and running drills showed similar (P > 0.05) or higher (P < 0.05; ES:1.17/4.61) than match TD, HSR and VHSR, while sprint and Acc+Dec were lower (P < 0.05). Conversely, technical-tactical drills and SSGs showed lower (P < 0.05; ES:-1.00/-3.45) TD, HSR, VHSR, sprint and Acc+Dec than official match peak demands. Locomotor loads during technical-tactical drills and SSGs were lower than peak demands, particularly for VHSR and sprint. Since training intensity is a key factor for high-performance development , these results may help to prepare top-class players for the official match peak demands. ARTICLE HISTORY
... Despite the extensive research related to training load evaluation methods, a gold standard has not yet come out, since discrepancies between different types of sports and evaluation contexts have been observed, making difficult the standardization of measures (Impellizzeri et al., 2019). In the last decade, training load and recovery assessment has been promoted using subjective methods like questionnaires and scales that measure the perception of well-being, stress, and recovery (Heidari et al., 2019). ...
Objectives. – The aim of the study was to analyze the behavior of the modified total quality recovery (TQR) scale during four microcycles of accumulation in volleyball players and its relationship with physiological markers as heart rate variability (HRV) and training impulse (TRIMP), as well as load perception by the session rating of perceived exertion (s-RPE), and perceived recovery-stress state using the RESTQ-Sport questionnaire. Equipment and methods. – Seven female players of a national volleyball team (age: 24.26 ± 3.37 years; weight: 71.63 ± 6.84 kg; height: 176.97 ± 8.04 cm; % fat: 32.64 ± 1.57%) were evaluated during a pre-competitive camp. HRV, TRIMP, TQR scale, and the s-RPE were assessed daily. While the RESTQ-Sport was applied at the beginning and at the end of the concentration camp. The Spearman correlation for all variables, as well as Friedman Test for HRV, TRIMP, TQR and S-RPE and Wilcoxon test for RESTQ-Sport were performed. Furthermore, the smallest worthwhile change (SWC) was applied to identify the magnitudes of change in the intra-subject data. Results. – The TQR scale showed significant correlations (p < .05) with HRV parameters (LnrMSSD and Stress Score), S-RPE and RESTQ-Sport dimensions. Conclusion. – The TQR scale shows to be sensitivity to microcycles of accumulation in female volleyball players. In addition, the study proves the TQR concurrent validity by correlating with different physiological and psychological parameters for monitoring load and recovery. Keywords: assessment; recovery; sports performance; volleyball; internal training load
... 2 To effectively measure the impact of training models on injury and illness incidence, data collection of both health-and performance-related variables must be integrated into all aspects of training and competition. 3 At present, the goal of monitoring training response is to allow iterative adjustment of training plans to optimize team gains, prevent inappropriate overload, 4 optimize recovery, 5 minimize load-related risk factors, and reduce injury rates. 6 Basketball is a strength-speed sport in which constant changes of direction and accelerations and decelerations predominate, 7 and these actions take place intermittently during high-intensity periods. ...
... The results obtained in the CG can be attributed to the coach's meticulously designed training program, which involved the thoughtful selection and utilization of specific methods and techniques, along with effective management of the training load. Continuous assessment of individual participant responses (internal load) in each session played a crucial role in achieving this balance [36,37]. Notably, improvements were observed in both the countermovement jump (CMJ) and CMJ with free arms (CMJ-FA), with minimal differences that did not achieve statistical significance (p > 0.05). ...
Countermovement jumping (CMJ) and free-arm countermovement jumping (CMJFA) express the explosive-elastic force of the lower limbs. Strategies to enhance performance in both types of jumping can be categorized into cognitive and ecological-dynamic approaches. However, the effectiveness of these approaches in improving CMJ and CMJFA remains incompletely understood. This study aims to investigate the impact of training protocols based on the two approaches to improving CMJ. Thirty-six subjects with an average age of 26 years were selected and divided into two groups: the ecological-dynamic group (EDG) and the cognitive group (CG). For 12 weeks, both groups followed separate protocols of three weekly one-hour sessions. EDG group followed a protocol focused on circle time. The CG group followed an instructor-led training protocol. Incoming and outgoing flight heights were measured. Pre and post-intervention differences within and between groups were assessed using t-tests for dependent and independent samples, respectively (p ≤ 0.05). CG demonstrated a 12.2% increase in CMJ and a 7.8% improvement in CMJFA, while EDG showed a 10.2% increase in CMJ and 19.5% progress in CMJFA. No statistically significant differences (p > 0.05) were observed between the groups in the improvement of CMJ; statistically significant differences (p < 0.05) were found in the improvement of CMJFA in favor of EDG.
... A number of different monitoring tools exist to follow the progression of individuals with different fitness levels and objectives, including the measurement of both external and internal loads. 1 In simple terms, external load is observable exercise behavior, which can be measured with standard units, such as kilograms, meters, seconds, velocity/speed, and power. Within an individual, they might be thought of as index training sessions, which are intended to demonstrate improvement over time. ...
Purpose:
Monitoring is a fundamental part of the training process to guarantee that the programmed training loads are executed by athletes and result in the intended adaptations and enhanced performance. A number of monitoring tools have emerged during the last century in sport. These tools capture different facets (eg, psychophysiological, physical, biomechanical) of acute training bouts and chronic adaptations while presenting specific advantages and limitations. Therefore, there is a need to identify what tools are more efficient in each sport context for better monitoring of training process.
Methods and results:
We present and discuss the fine-tuning approach for training monitoring, which consists of identifying and combining the best monitoring tools with experts' knowledge in different sport settings, designed to improve (1) the control of actual training loads and (2) understanding of athletes' training adaptations. Instead of using single-tool approaches or merely subjective decision making, the identification of the best combination of monitoring tools to assist experts' decisions in each specific context (ie, triangulation) is necessary to better understand the link between acute and chronic adaptations and their impact on health and performance. Future studies should elaborate on the identification of the best combination of monitoring tools for each specific sport setting.
Conclusion:
The fine-tuning monitoring approach requires the simultaneous use of several valid and practical tools, instead of a single tool, to improve the effectiveness of monitoring practices when added to experts' knowledge.
... Por otra parte, el jugador de baloncesto debe tomar decisiones tácticas, aplicando su capacidad técnica de forma intensa y en el menor período temporal (Esper, 2020). Con el propósito último de desarrollar en el comportamiento motriz del deportista estas capacidades, es necesario llevar a cabo una correcta y planificada preparación física que controle la carga de los entrenamientos y de los partidos en función de la necesidad que el preparador físico establezca en cada microciclo (Bingqiu & Chenggong, 2022;Impellizzeri et al., 2019). De esta forma, se evitará el sobreentrenamiento de los deportistas, previniendo las posibles lesiones que puedan aparecer por el exceso de carga (Aoki et al., 2017). ...
El objetivo principal de esta investigación fue analizar el efecto de una intervención en preparación física específica para jugadores sub18 de baloncesto durante un período de ocho semanas. La muestra utilizada fue de 23 jugadores de baloncesto con una edad de 16.30 (± .470) años. Más allá, se dividió la muestra en grupo experimental y control, realizándose un pretest y un postest para medir las capacidades de salto, velocidad, agilidad, dorsiflexión y fuerza de tren superior entre todos los jugadores. Igualmente, se realizó un análisis estadístico atendiendo a las variables: grupo, edad del jugador, demarcación del jugador y minutos jugados por partido. Por otra parte, el grupo experimental fue expuesto a una intervención física acorde a las demandas físicas del baloncesto, repartida en tres sesiones semanales de 40 minutos, haciendo un total de 24 sesiones. Dicha intervención se basó en ejercicios pliométricos, ejercicios de fuerza con peso libre, ejercicios de movilidad y ejercicios de coordinación y velocidad. Los principales resultados obtenidos mostraron mayores mejoras del grupo experimental en fuerza del tren superior y en dorsiflexión, al igual que ligeras mejoras en el resto de los test realizados, atendiendo a la comparación con el grupo control. A modo de conclusión, un programa de preparación física que responda a las necesidades físicas del baloncesto repercute en una mejora de las capacidades analizadas, siendo especialmente necesario una planificación más extensa para obtener mayores mejoras en estas capacidades físicas. Palabras Clave: Baloncesto; Capacidades físicas; Rendimiento deportivo; Condición física; Deportes de equipo. Abstract. The main objective of this research was to analyse the effect of a specific physical preparation intervention for U18 basketball players over a period of eight weeks. The sample used was 23 basketball players with an age of 16.30 (± .470) years. Further, the sample was divided into experimental and control groups, and a pretest and a posttest were performed to measure jumping, speed, agility, dorsiflexion and upper body strength among all players. Likewise, a statistical analysis was carried out according to the following variables: group, age of the player, player demarcation and minutes played per match. On the other hand, the experimental group was exposed to a physical intervention according to the physical demands of basketball, distributed in three weekly sessions of 40 minutes, making a total of 24 sessions. This intervention was based on plyometric exercises, strength exercises with free weights, mobility exercises and coordination and speed exercises. The main results obtained showed greater improvements in the experimental group in upper body strength and dorsiflexion, as well as slight improvements in the rest of the tests performed, compared to the control group. In conclusion, a physical preparation programme that responds to the physical needs of basketball has an impact on the improvement of the skills analysed, being especially necessary a more extensive planning to obtain greater improvements in these physical skills. Keywords: Basketball; Physical capacities; Sports performance; Physical condition; Team sports.
... External load is associated with mechanical/locomotor demands, usually collected by global positioning systems, global navigation satellite systems, local positioning systems, and inertial measurement units that belong to micro-electro-mechanical systems (which provide a combination of 3D accelerometers, 3D gyroscopes, and 3D magnetometers). Despite different technologies, they provide external load measures, such as distances covered at various running speeds, accelerations, decelerations, player load, and others [2][3][4][5]. ...
Load monitoring consists of training/match demand quantification as well as wellness and readiness to maximize the likelihood of optimal athletic performance [...]
... 15 Specific to athletic performance, physiological sexbased differences have been noted metabolically 9 and in response to fatigue. 3 Individuals respond to training differently, so applying practices and systems to female athletes that have only been studied in males is inherently problematic. ...
The purpose of this study was to describe the in-season variations of acute:chronic workload ratio (ACWR) of distance, high intensity distance (HID), sprints, accelerations, and decelerations between player positions of a Division I collegiate women’s lacrosse team. Data were collected via wearable microtechnology across a total of 17 games and 64 training sessions on a total of 15 participants (attackers n=5, midfielders n=5, defenders n=5). ACWRs were calculated weekly by dividing the workload from the past seven days by the workload from the past 28 days for each metric. Two repeated measures analyses of variance (RM-ANOVA) were used to compare positional differences and weekly changes in all five metrics for 1) ACWR and 2) weekly training totals. There were several differences in weekly totals and ACWRs across all five metrics evaluated (p<.05), but no positional differences were noted. Apart from the early training weeks, ACWR primarily stayed within the optimal window of 0.8-1.5 to maximize performance and reduce injury risk. These data indicate that there is variation in weekly totals for the main five metrics studied that cause “spikes” and “valleys” in workload. However, the athletes had built enough of a base in their chronic workload that it did not affect their ACWR to move outside of the optimal window. Using this information, coaches and team physicians can more effectively program training not only to optimize performance, but also to limit injuries, fatigue, and lack of fitness.
... EL monitoring is the main method used within professional and amateur sporting organizations, as measuring devices do not require specialized equipment that may be unattainable to said organizations. Accumulating TL affect's individuals uniquely as an internal physiological response will vary based on the same external stimuli (Impellizzeri et al., 2019). ...
BACKGROUND: During a professional soccer season, training load (TL) will fluctuate due to the need to prepare for the next competition. Based on the technical staff’s daily and weekly evaluation, TL will be adjusted as they prepare the team and maximize individual performance and achieve a favorable result. Therefore, the programming of each match week (MW) TL may promote a favorable result. PURPOSE: The purpose of this study was to examine variation in daily GPS-derived TL variables based on match result using the Match Day Minus (MD-) system. This study provides descriptive TL data yet to be reported in this novel population. METHODS: Twenty-four male United Soccer League One (USL1) players were monitored through the full competitive in-season macrocycle. Using GPS units, metrics of interest were identified to best provide a full picture of training load. Duration (D), Total Distance (DT), High Metabolic Load Distance (HMLD), Total Loading (LT), Number of Accelerations (#A), and Number of Decelerations (#D), collectively make up weekly TL. The MD- system was used to categorize each training day. One-Way ANOVA was used for each MD- to compare results, with a Bonferroni Correction. RESULTS: D, DT, HMLD, and LT were the metrics of interest that had the largest effect throughout the MW. CONCLUSION: Based on the results of this study, weekly TL has been shown to influence match results in American professional soccer. Special consideration should be given to the metrics of interest during the MW in preparation for weekly competition.
... EL monitoring is the main method used within professional and amateur sporting organizations, as measuring devices do not require specialized equipment that may be unattainable to said organizations. Accumulating TL affect's individuals uniquely as an internal physiological response will vary based on the same external stimuli (Impellizzeri et al., 2019). ...
... An adequate training dose is essential for the development of physical fitness and sporting skills (technical, tactical and psychological) 14 . An inadequate training load may under prepare the athlete for performance 15,16 , whereas, a greater training load with insufficient recovery may cause overtraining, overuse injury or burnout 17 . It should be noted, however, that the causal effects between training load and injuries are complex and poorly understood [18][19][20] . ...
The management of training load in youth team-sport athletes is important. There is, however, a lack of research on practitioners’ perceptions and understandings of managing training load during this period and what this means in terms of maturational status and injury risk. This study aimed to investigate academy football practitioners’ perceptions and understanding of training load, maturation and injury risk in young male footballers. Coaches, sports scientists, medical staff and key stakeholders from a professional football club academy in England participated in focus groups investigating their understanding and perceptions of training load, maturation and injury risk. A qualitative descriptive methodology utilising framework analysis was used to capture and better understand participants’ views. Findings revealed that practitioners consider managing training load during adolescence to be comprised of, and mediated by, three key elements: club philosophy, factors inside the club's control (periodisation strategy; staff member practice), and factors outside the club's control (life load; growth and maturation). This study is an important addition to the current literature on managing injuries through the growth spurt by investigating how different stakeholders perceive training load, maturation and potential strategies to mitigate risk.
... The monitoring of many indicators has been realized by using flexible, wearable sensors. According to a recent systematic review of wearable sensors for sports, these can be categorized as follows: (1) kinematical indicators, including posture, motion, force, and acceleration; (2) physiological indicators, including vital signs (e.g., breath, pulse, ECG, heart beating, blood pressure, temperature, SpO2, etc.) and metabolites during and after exercises (e.g., glucose, pH, electrolytes, lactic acid, etc.) [5] .In the current study we aimed to analyse the performance of young basketball players on four consecutive trial matches using Kinexon perform mobile system [9]. ...
... Irrespective of how it is quantified, coaches prescribe training according to external load to the desired psychophysiological response. It is this response that corresponds to the internal training load (Impellizzeri et al. 2019). There exists a vacuum in research that analyses the relationship between the external load prescribed by the coach/es and that perceived by the athletes (post-session) in a professional senior's team. ...
The shift from a conventional approach to a more game-based and tacticalapproach when coaching football has placed an increased emphasis on the monitoringof training sessions and has consequently influenced, to a considerable extent, the furtherdevelopments of tools and technology. With the growth of this field of practice, it becameapparent that there is a gap in scientific understanding of the relationship between thecoachs predicted and players perceived training load. The training load that is predictedand perceived by football coaches and players respectively was compared in twenty-twotraining sessions with a semi-professional football team participating in the Maltese PremierLeague during the 2019/20 season. This was done through the session ratings of perceivedexertion (Session RPE) and global positioning system (GPS). The participants consistedof twenty-one players and their coaches (coach and physical trainer). Athletes respondedto the scale of perceived exertion using the BORG scale (scores from 0 to 10) after thetraining sessions, while the coaches completed the scale pre-session (predicted load) andpost session (estimated load). Apart from that, the players were monitored with a PlayertekGPS (10hz) throughout all training sessions. These methods were used to collect both theinternal load (Session RPE) and external load (GPS). There was little disagreement betweenthe predicted and estimated training load (coaches) and that perceived by the playersas high correlations were established. Findings suggest that the coaches predicted andestimated loads strongly correlate with the load as perceived by the football players duringan ongoing season between December 2019 and February 2020. A strong correlation alsoexists between the coaches predicted and estimated loads and the GPS load.
... Las áreas de histéresis de la TEP, la FC y la O 2 Hb muscular variaron en gran medida a lo largo de las series, tal y como muestra su elevada dispersión estadística. Estas observaciones respaldan resultados previos que estudiaron la TEP y la FC (Montull et al., 2020) y las relaciones no proporcionales observadas entre cargas internas y externas (Impellizzeri et al., 2019). ...
... Also, Bermejo et al. (2022) demonstrated that the increase in cortisol levels caused by acute exercise impairs memory and learning ability. The exertion level may differ between stroke and non-disabled individuals, even with the same workload (intensity and duration), because stroke-related psychophysiological characteristics may influence the internal training load (the individual's ability to accept physiological stress) (Impellizzeri et al. 2019). In this way, physical fatigue in the BEFORE group may have a detrimental effect on implicit motor learning specific to stroke individuals, given their low load acceptability compared to neurotypical individuals. ...
The acute impact of cardiovascular exercise on implicit motor learning of stroke survivors is still unknown. We investigated the
effects of cardiovascular exercise on implicit motor learning of mild-moderately impaired chronic stroke survivors and neurotypical
adults. We addressed whether exercise priming effects are time-dependent (e.g., exercise before or after practice) in the encoding
(acquisition) and recall (retention) phases. Forty-five stroke survivors and 45 age-matched neurotypical adults were randomized
into three sub-groups: BEFORE (exercise, then motor practice), AFTER (motor practice, then exercise), and No-EX (motor
practice alone). All sub-groups practiced a serial reaction time task (five repeated and two pseudorandom sequences per day) on
three consecutive days, followed 7 days later by a retention test (one repeated sequence). Exercise was performed on a stationary
bike, (one 20-min bout per day) at 50% to 70% heart rate reserve. Implicit motor learning was measured as a difference score
(repeated—pseudorandom sequence response time) during practice (acquisition) and recall (delayed retention). Separate analyses
were performed on the stroke and neurotypical groups using linear mixed-effects models (participant ID was a random effect).
There was no exercise-induced benefit on implicit motor learning for any sub-group. However, exercise performed before practice
impaired encoding in neurotypical adults and attenuated retention performance of stroke survivors. There is no benefit to implicit
motor learning of moderately intense cardiovascular exercise for stroke survivors or age-matched neurotypical adults, regardless
of timing. Practice under a high arousal state and exercise-induced fatigue may have attenuated offline learning in stroke survivors.
... Training load is generally classified into two components; internal and external [12]. Internal TL (e.g., heart rate response to training), reflects the psychophysiological response to exercise, whilst external TL (e.g., total distance covered), refers to the physical work ...
... 9 Understanding how an additional stressor to exercise can alter the internal-external load relationship (e.g., heart rate achieved in reference with work done) is important for optimizing exercise prescription. 10 For instance, environmental manipulations (i.e., acute exposure to systemic hypoxia 11 or heat stress 12 ) may be a viable option for individuals with compromised load capacity in their lower extremities to train at higher intensities without having to perform excessive mechanical work. This promising approach represents a potential therapeutic solution for those with acute (e.g., athletes recovering from an injury) or chronic dysfunction (e.g., patients suffering from musculoskeletal disorders) who may be unable to fully load their locomotor system. ...
Objectives:
To quantify the acute effects of graded blood flow restriction on the interaction between changes in mechanical output, muscle oxygenation trends and perceptual responses to heart rate clamped cycling.
Design:
Repeated measures.
Methods:
Twenty-five adults (21 men) performed six, 6-min cycling bouts (24 min of recovery) at a clamped heart rate corresponding to their first ventilatory threshold at 0 % (unrestricted), 15 %, 30 %, 45 %, 60 % and 75 % of arterial occlusion pressure with the cuffs inflated bilaterally from the fourth to the sixth minute. Power output, arterial oxygen saturation (pulse oximetry) and vastus lateralis muscle oxygenation (near-infrared spectroscopy) were monitored during the final 3 min of pedalling, whilst perceptual responses (modified Borg CR10 scales) were obtained immediately after exercise.
Results:
Compared to unrestricted cycling, average power output for minutes 4-6 decreased exponentially for cuff pressures ranging 45-75 % of arterial occlusion pressure (P < 0.001). Peripheral oxygen saturation averaged ∼96 % across all cuff pressures (P = 0.318). Deoxyhemoglobin changes were larger at 45-75 % versus 0 % of arterial occlusion pressure (P < 0.05), whereas higher total haemoglobin values occurred at 60-75 % of arterial occlusion pressure (P < 0.05). Sense of effort, ratings of perceived exertion, pain from cuff pressure, and limb discomfort were exaggerated at 60-75 % versus 0 % of arterial occlusion pressure (P < 0.001).
Conclusions:
Blood flow restriction of at least 45 % of arterial occlusion pressure is required to reduce mechanical output during heart rate clamped cycling at the first ventilatory threshold. Whilst power decreases non-linearly above this pressure threshold, higher occlusion levels ranging 60-75 % of arterial occlusion pressure also accentuate muscle deoxygenation and exercise-related sensations.
... Athlete monitoring examines the physiological stress placed on the body due to physical activity, also known as training load [1]. Training load can be measured internally, reflected as a psychophysiological response to physical activity, or externally, reflected as the physical work performed by the body [2]. Tracking training load variables through the use of global positioning systems (GPSs) has become a common practice in collegiate soccer [3][4][5], with research being increasingly conducted on female collegiate soccer athletes in recent years [4,[6][7][8][9]. ...
The purpose of this study was to estimate the workloads accumulated by collegiate female soccer players during a competitive season and to compare the workloads of starters and substitutes. Data from 19 college soccer players (height: 1.58 ± 0.06 m; body mass: 61.57 ± 6.88 kg) were extracted from global positioning system (GPS)/heart rate (HR) monitoring sensors to quantify workload throughout the 2019 competitive season. Total distance, distance covered in four speed zones, accelerations, and time spent in five HR zones were examined as accumulated values for training sessions, matches, and the entire season. Repeated-measures ANOVA and Student’s t tests were used to determine the level of differences between starter and substitute workloads. Seasonal accumulated total distance (p < 0.001), sprints (≥19.00 km/h; p < 0.001), and high-speed distance (≥15.00 km/h; p = 0.005) were significantly greater for starters than substitutes. Accumulated training load (p = 0.08) and training load per minute played in matches (p = 0.08) did not differ between starters and substitutes. Substitutes had similar accumulated workload profiles during training sessions but differed in matches from starters. Coaches and practitioners should pursue strategies to monitor the differences in workload between starters and substitutes.
The present study was designed to investigate two aspects. Firstly, analysis of variations in acute load, chronic load, acute-chronic load ratio, monotony, and training strain during the preseason (PS), first and second half of the season (1st HS, 2nd HS). Secondly, comparing these indicators of training load in players' positions. Twenty-two elite soccer players from the Premier League of Iran (age: 27.2 4.5 years, professional experience: 6.2 4.3 years) were involved in this study. Players were monitored daily for 45 weeks through an 18 Hz global positioning system (GPS), to gather data on distance running (total running), distance running at 14 km/h (moderate intensity running), and distance running at a speed above 19.8 km/h (high-intensity running). One-way analysis of variance, followed by Tukey HSD post hoc test to analyze data. The pre-season has a significantly higher amount of acute load, chronic load, monotony and training strain, total running, and moderate-intensity running than the first half ( p < 0.05) and the second half ( p < 0.05). When comparing these training load indicators for high-intensity running, a significant difference was only observed between the PS and the 2nd HS (p 0.05, moderate ES). Also, no significant differences were observed between positions in total running and moderate intensity running. However, training load indices based on high-intensity running between positions showed external defenders vs center backs ( p < 0.05), midfielders ( p < 0.05) and strikers ( p < 0.05) were significantly different. Furthermore, wingers had a significant difference in high-intensity running compared to central defenders ( p < 0.05) and midfielders ( p < 0.05). To conclude, this study demonstrated that acute load, chronic load, monotony, and training strain were more prevalent in the pre-season and slowly decreased during the season. External defenders and wingers experienced more acute load, chronic load, monotony, and training strain for high-intensity running during the season compared to other positions. Therefore, the results indicate that pre-season had a higher physical load than competition season, and players' positions experienced varying physical loads.
Since the analysis of most demanding scenarios (MDS) in basketball has improved the practical knowledge about match demands and possible impacts for the training process, it seems important to summarize the scientific evidence providing useful information and future directions related to MDS. This review assesses the results reflected in the available literature about the MDS in basketball, synthesizing and discussing data from scientific papers, and then providing relevant insights about terminology, sex and sample size, competition category, workload variables recorded, technology used, method of calculation, time windows analyzed, and activities evaluated related to MDS. Therefore, the present narrative review would be of practical use for coaches, scientists, athletes as well as strength and conditioning trainers exploring the current trends and future directions related to MDS in basketball.
Professional soccer is a physically demanding sport that requires players to be highly trained. Advances using GPS allow the tracking of external workloads for individual players in practice and competition, however, there is a lack of evidence on how these measures impact match results. Therefore, we analyzed external workloads by player position and determined if they vary depending on the result of competitive matches. External workloads were analyzed in professional soccer players (n = 25) across 28 competitive games. One-way ANOVA determined if workloads varied by position (striker - ST, wide midfielder - WM, central midfielder - CM, wide defender - WD, central defender - CD) or across games won (n = 8), lost (n = 13) or tied (n = 7). Repeated-measures ANOVA assessed differences in workloads specific to each position in each of the result categories. Statistical significance was set at p < 0.05. Across all games, more high-speed and very-high speed running was done by ST and WD compared to CD (p < 0.001) and CM (p < 0.001 - 0.02). Whole-team data showed no differences in any external workload variable with respect to match result (p > 0.05), however, in games won ST did more very high-speed running than in losing games (p = 0.03) and defending players did more high and very high-speed running in games tied vs. those won or lost (p < 0.05). Whole-team external workloads do not vary depending on the match result; however, high speed running may be a differentiating factor at the positional level. Coaches should consider position-specific analysis when examining player workloads.
Purpose:
Quantifying training intensity provides a comprehensive understanding of the training stimulus. Recent technological advances may have improved the feasibility of using heart-rate (HR) monitoring in swimming. However, the implementation of HR monitoring is yet to be assessed longitudinally in the daily training environment of swimmers. This study aimed to assess the implementation of HR by comparing the training-intensity distribution from an external measure, planned volume at set intensities (PVSI), with the internal training-intensity distribution measured using time in HR zones.
Methods:
Using a longitudinal observational design, 10 competitive swimmers (8 male and 2 female, age: 22.0 [2.3] y, Fédération Internationale de Natation point score: 842.9 [58.5], mean [SD]) were monitored daily for 6 months. Each session, HR data, and coached-planned and athlete-reported session rating of perceived exertion (Modified Category Ratio 10 scale) were recorded. Based on previously determined training zones from an incremental step test, PVSI was calculated using the planned distance and planned intensity of each swim bout. Training-intensity distributions were analyzed using a linear mixed model (lme4).
Results:
The model revealed a small to moderate relationship between PVSI and time in HR zone, based on the Nakagawa R-squared value (range .14-.42).
Conclusions:
Training-intensity distribution differed between the internal measure (ie, HR) and the external measure of intensity (ie, PVSI). This demonstrates that internal and planned external measures of intensity cannot be used interchangeably to monitor training. Further research should explore how to best integrate these measures to better understand training in swimming.
Background
Current sports medicine and rehabilitation trends indicate an increasing use of wearable technology. The ability of these devices to collect, transmit, and process physiological, biomechanical, bioenergy, and environmental data may aid in anterior cruciate ligament reconstruction (ACLR) workload monitoring and return-to-sport decision-making. In addition, their ease of use allows assessments to occur outside the clinical or laboratory settings and across a broader timeline.
Purpose
To (1) determine how wearable technology can assess external workload deficits between limbs (involved and uninvolved) and between groups (healthy controls vs patients with ACLR) during physical activity (PA) or sport and (2) describe the types of sensors, sensor specifications, assessment protocols, outcomes of interest, and participant characteristics from the included studies.
Study Design
Scoping review; Level of evidence, 4.
Methods
In February 2023, a systematic search was performed in the MEDLINE, EMBASE, CINAHL, SPORTDiscus, Scopus, IEEE Xplore, Compendex, and ProQuest Dissertations and Theses Global databases. Eligible studies included assessments of PA or sports workloads via wearable technology after ACLR.
Results
Twenty articles met eligibility criteria and were included. The primary activity assessed was activities of daily living, although rehabilitation, training, and competition were also represented. Accelerometers, global positioning system units, pedometers, and pressure sensor insoles were worn to collect external workload data, which was quantified as kinetic, kinematic, and temporospatial data. Daily steps (count) and moderate to vigorous PA (min/day or week) were the most common units of measurement. A limited number of studies included outcomes related to between-limb asymmetries.
Conclusion
The findings of this scoping review highlight the versatility of wearable technologies to collect patients’ kinetic, kinematic, and temporospatial data and assess external workload outcomes after ACLR. In addition, some wearable technologies identified deficits in workload compared with healthy controls and between reconstructed and unaffected limbs.
The main aim of this study was identifying differences in physical load between training and match-play. Twelve professional basketball players were monitored during 5 games. The following workload variables were recorded: Movement load (ML), Training Impulse (TRIMP), average Heart Rate (HR). Non-significant differences were found between activities (game vs practice). Regarding to practical meaningfulness, greater match values were reached for EL and IL variables compared to practices. In this regard, large differences for ML (F = 0.71, ES = 1.69) and TRIMP (F = 0.02, ES = 1.71, large) were found. In conclusion, greater values of physical load but non-significant differences were achieved during games compared to practice for ML, TRIMP and HR. In this regard, physical demands remain consistent (large effects) regardless of activity (game vs practice) in professional basketball players.
O objetivo da revisão foi apresentar a carga de treino do microciclo da periodização esportiva. A revisão explicou a carga do microciclo da periodização de Matveev, do bloco de Verkhoshanski, da periodização ATR, da periodização individualizada de Bondarchuk e da periodização dos esportes coletivos (a periodização de microestrutura, a periodização tática e a periodização específica para o voleibol). A carga do microciclo pela periodização de Matveev interpreta esse acontecimento pela síndrome de adaptação geral e pela teoria da supercompensação. A evolução científica do treino esportivo gerou um novo conteúdo, a carga do microciclo pelo resíduo do treino e pelo treino integrado (ocorre ao mesmo tempo treino físico e técnico e tático). Nos jogos esportivos coletivos a carga do microciclo é através do aspecto técnico e tático. Mas no treino com bola da periodização para o voleibol a carga do microciclo é pelo esforço do fundamento e pela lesão do fundamento. Em conclusão, a carga do microciclo está relacionada com a modalidade que foi criada aquela concepção de periodização e conforme as ideias do autor da periodização.
Purpose: Assessing the respiratory frequency (f R) is practical in monitoring training progress in competitive athletes, especially during exercise. This study aimed to validate a new wearable chest-strap (wCS) device to measure f R against ergospirometry as a criterion device in healthy soccer players. • Methods: A total of 26 elite professional soccer players (23,6 [4,8] years; 180,6 [5,7] cm; 77,2 [5,4] kg) from three Italian Serie A League teams participated in this cross-sectional study. The sample included attackers, midfielders, and defenders. The f R was assessed during a maximal incremental exercise test on a treadmill using i) a breath-by-breath gas exchange analyzer (Vyntus TM CPX, Vyaire Medical); and ii) a novel wCS with sensors designed to assess breath frequency following the chest expansions. Pearson's correlation coefficient (r), adjusted coefficient of determination (aR²), Bland-Altman plot analysis, and Lin's concordance correlation coefficient (ρ c) were used for comparative analysis (correlation and concordance) among the methods. The repeated measures correlation coefficient (r rm) was used to assess the strength of the linear association between the methods. In contrast, the intraclass correlation coefficient (ICC) with its corresponding 95% confidence interval (95% CI) and the Finn coefficient (r F) were used for inter-rater reliability. All statistical analyses were performed within the R statistical computing environment with a statistical significance of P<0.05. • Results: 16529 comparisons were performed after collecting the maximal incremental exercise test data. No significant differences were found for both methods (P<0.05). Correlation among devices was statistically significant and very large (r [95% CI]: 0.970 [0.970, 0.971], P<0.01; aR 2 [95% CI]: 0.942 [0.942, 0.943], P<0.01). Similarly, a high concordance was found (ρ c [95% CI]: 0.970 [0.969, 0.971], bias correction factor: 0.999). However, the Vyntus TM CPX, as a standard criterion, showed moderate agreement with wCS after Bland-Altman analysis (bias [95% lower to the upper limit of agreement]; % agree: 0.170 [-4.582 to 4.923]; 69.9%). A strong association between measurements (r rm [95% CI]: 0.960 [0.959, 0.961]), a high absolute agreement between methods (ICC [95% CI]: 0.970 [0.970, 0.971]), and a high inter-rater reliability (r F : 0.947) was found.
There is a growing focus on developing person-adaptive strategies to support sustained exercise behavior, necessitating conceptual models to guide future research and applications. This paper introduces Flexible nonlinear periodization (FNLP) - a proposed, but underdeveloped person-adaptive model originating in sport-specific conditioning - that, pending empirical refinement and evaluation, may be applied in health promotion and disease prevention settings. To initiate such efforts, the procedures of FNLP (i.e., acutely and dynamically matching exercise demand to individual assessments of mental and physical readiness) are integrated with contemporary health behavior evidence and theory to propose a modified FNLP model and to show hypothesized pathways by which FNLP may support exercise adherence (e.g., flexible goal setting, management of affective responses, and provision of autonomy/variety-support). Considerations for future research are also provided to guide iterative, evidence-based efforts for further development, acceptability, implementation, and evaluation.
Purpose: The aim of this study was to investigate the dynamics of external training load (eTL), internal training load (iTL), and well-being status, during a regular season week with one game, and to examine the differential workloads of players depending on their distance from game day during a competitive season. Method: Subjects were 10 full-time professional basketball players (24.6 ± 4.9 years old; 204.2 ± 16.8 cm; 97.9 ± 10.4 kg). Workload was recorded and classified as total duration training and duration of full game during a competitive season. A wearable tracking system collected eTL via Player Load (PL) and Player Load per minute (PL/min). Training sessions were classified based on days before a match (four days before the match day = MD-4, MD-3, MD-2, and MD-1), and MD. Session rate of perceived exertion (sRPE) and rate of perceived exertion (RPE) were used for iTL. In addition, the Hooper index (HI) was used for well-being. Results: A significant difference was found between MD-1 and MD workload, MD workload being the highest of all variables: RPE (p < .001), PL/min (p <.001), PL (p <.001), and sRPE (p <.001). Regarding Hooper’s categories, significant differences between training days and match were only found in soreness (p <.001). Conclusion: The results show that MD provides a unique stimulus in terms of volume and intensity. Consequently, coaches must incorporate specific training exercises to adapt players to the demands of competition. Finally, special attention should be paid to MD-2 and MD-1 in terms of potential accumulated fatigue and thus to ensure appropriate recovery time for athletes to adapt before the match.
Understanding internal and external loading in exercise is important for safe rehabilitation. The physiological parameters of dogs have been studied in swimming, but those of dogs walking on an underwater treadmill have not been documented. In this study, four healthy beagle dogs were examined for changes in physiological parameters before and after walking in water for 20 min at a speed of 4 km/h with the water level set at the height of the hip joint as an external load. Statistical analysis of the results was performed using paired sample t-tests. Results indicated that heart rate (125 ± 11.8 beat/min to 163 ± 9.5 beat/min) and lactate levels (2 ± 0.1 mmol/L to 2.4 ± 0.2 mmol/ L) significantly increased from before to after walking on an underwater treadmill. Additional research is needed on internal loading when using underwater treadmills, which would further contribute to the safety of rehabilitation.
Weekly training loads are typically reported using absolute values and are not individualized according to competition positional demands (relative values). The aim of this study was to evaluate absolute and relative training loads and compare across playing positions during a full in-season in an elite soccer academy. 24 elite academy soccer players, categorized into five positions (CD: central defender [n = 4]; FB: full back [n = 5]; CM: central midfielder [n = 6]; WM: wide midfielder [n = 5]; FW: forward [n = 4]), were monitored using a global positioning system. Absolute training load was calculated using the total distance, the distance at moderate-speed ([15-20[ km·h-1), high-speed ([20-25[ km·h-1), sprint (> 25 km·h-1), the total number of accelerations (> 3 m·s-2) and decelerations (< -3 m·s-2). Relative training load was calculated by dividing absolute training loads by mean values from the competitive matches. Training loads were determined daily according to their distance from match day (MD). One-way ANOVAs were performed to evaluate differences between playing positions. Absolute moderate-speed distance was greater for WM compared to CD (p = 0.015, and p = 0.017), while the opposite was shown for relative values (p = 0.014, and p < 0.001) on MD-4 and MD-3, respectively. The absolute moderate-speed distance was not different between CD, FB, CM, and FW, whereas relative values were greater for CD on MD+2 and MD-4 (p < 0.05). FB and WM performed greater absolute high-speed distance than CD on MD-4 and MD-3 (p < 0.05) while no difference was highlighted for relative values.Our results demonstrated that in the present academy players, training load for CD was underestimated using absolute training loads for moderate and high-speed distances. In contrast, relative training loads highlighted WM as an underloaded position. Therefore, relative training loads are recommended as they contextualize training loads according to competitive demands and favor training individualization.
BACKGROUNDː Basketball players’ external and internal training loads have been extensively monitored. However, no study has evaluated if pre-training athlete-reported conditions influence them. Therefore, this study investigated the effects of athlete-reported pre-training well-being and recovery on subsequent external load intensity, perceived exertion scores and their ratio (efficiency index) in youth basketball training.
METHODSː The external load (EL) intensity (EL∙min-1), ratings of perceived exertion (RPE) and efficiency index (EL∙min-1:RPE) of 15 youth basketball players (age: 15.2 ± 0.3 years) were monitored during team-based training sessions. Before each session, players reported their levels of recovery (using a modifed 10-point Total Quality Recovery, TQR, scale), fatigue, sleep quality, muscle soreness, mood, and stress. Statistical analyses were performed via linear mixed models.
RESULTSː EL∙min-1 was higher when player reported better pre-training recovery (p= 0.001). Higher RPE scores and lower efficiency indexes were registered in players reporting better pre-training conditions, respectively. Specifically, RPE scores were higher when players reported better TQR, fatigue, muscle soreness and stress scores (all p< 0.05), while training efficiency was, conversely, lower influenced by in correspondence of better TQR and sleep (all p< 0.05)..
CONCLUSIONSː This study identified influences of athlete-reported pre-training well-being and recovery on subsequent external intensity, RPE and training efficiency index in youth basketball players. Recovery and well-being indicators could be monitored seen their influence on subsequent training loads. Current findings can be considered by basketball sport scientist when selecting athlete monitoring questionnaires and when interpreting training load outputs.
Objective: To establish whether a simple integration of selected internal and external training load (TL) metrics is useful for tracking and assessing training outcomes during team-sport training.
Methods: Internal [heart rate training impulse (HR-TRIMP), session rating of perceived exertion (sRPE-TL)] and selected external (global positioning systems; GPS) metrics were monitored over seven weeks in 38 professional male rugby league players. Relationships between internal and external measures of TL were determined, and an integrated novel training efficiency index (TEI) was established. Changes in TEI were compared to changes in both running performance (1.2 km shuttle test) and external TL completed.
Results: Moderate to almost perfect correlations (r = 0.35–0.96; ±~0.02; range ± 90% confidence limits) were observed between external TL and each measure of internal TL. The integration of HR-TRIMP and external TL measures incorporating both body mass and acceleration/deceleration were the most appropriate variables for calculating TEI, exhibiting moderate (ES= 0.87–0.89; ±~0.15) and small (ES = 0.29–0.33; ±~0.07) relationships with changes in running performance and completed external TL respectively.
Conclusions: Combination of the TEI and an athlete monitoring system should reveal useful information for continuous monitoring of team-sport athletes over several weeks.
Exercise training which meets the recommendations set by the National Physical Activity Guidelines ensues a multitude of health benefits towards the prevention and treatment of various chronic diseases. However, not all individuals respond well to exercise training. That is, some individuals have no response, while others respond poorly. Genetic background is known to contribute to the inter-individual (human) and -strain (e.g., mice, rats) variation with acute exercise and exercise training, though to date, no specific genetic factors have been identified that explain the differential responses to exercise. In this review, we provide an overview of studies in human and animal models that have shown a significant contribution of genetics in acute exercise and exercise training-induced adaptations with standardized endurance and resistance training regimens, and further describe the genetic approaches which have been used to demonstrate such responses. Finally, our current understanding of the role of genetics and exercise is limited primarily to the nuclear genome, while only a limited focus has been given to a potential role of the mitochondrial genome and its interactions with the nuclear genome to predict the exercise training-induced phenotype(s) responses. We therefore discuss the mitochondrial genome and literature that suggests it may play a significant role, particularly through interactions with the nuclear genome, in the inherent ability to respond to exercise.
Training monitoring is about keeping track of what athletes accomplish in training, for the purpose of improving the interaction between coach and athlete. Over history there have been several basic schemes of training monitoring. In the earliest days training monitoring was about observing the athlete during standard workouts. However, difficulty in standardizing the conditions of training made this process unreliable. With the advent of interval training, monitoring became more systematic. However, imprecision in the measurement of heart rate (HR) evolved interval training toward index workouts, where the main monitored parameter was average time required to complete index workouts. These measures of training load focused on the external training load, what the athlete could actually do. With the advent of interest from the scientific community, the development of the concept of metabolic thresholds and the possibility of trackside measurement of HR, lactate, VO 2 , and power output, there was greater interest in the internal training load, allowing better titration of training loads in athletes of differing ability. These methods show much promise but often require laboratory testing for calibration and tend to produce too much information, in too slow a time frame, to be optimally useful to coaches. The advent of the TRIMP concept by Banister suggested a strategy to combine intensity and duration elements of training into a single index concept, training load. Although the original TRIMP concept was mathematically complex, the development of the session RPE and similar low-tech methods has demonstrated a way to evaluate training load, along with derived variables, in a simple, responsive way. Recently, there has been interest in using wearable sensors to provide high-resolution data of the external training load. These methods are promising, but problems relative to information overload and turnaround time to coaches remain to be solved. Watching athletes perform well, set personal records or win competitions, are great pleasures for sports scientists. To think that the information that you have collected on the athlete, or synthesized from the literature, has helped the athlete achieve optimal performance is " as good as it gets " for support staff. Conversely, watching a poor performance inspires analysis of what went wrong, with preparation, tactics, or execution of the competitive plan. This provides the basis for the questions that drive sport-science research. Because so much of the preparation of athletes is related to the structure and details of the training program, there is a natural emphasis on how training influences performance. This interest goes into history, to Milo of Crotona, the Italian farm boy who lifted a growing bullock daily until he became the strongest man in the world and legend of the ancient Olympics. This story provides the historical grounding for the quest to understand the training response, most uniquely characterized by the concept of progression of the training load, and to the idea that training loads can be quantitatively expressed 1 and related to performance outcomes. 2–6 Although it is not known if Milo had a coach, most top athletes throughout history have had one, someone with more knowledge and experience, and the objectivity to evaluate their training and performance. The concept of training monitoring, regardless of historical time frame is in essence about the coach-athlete interface. Although not always appreciated, one can make the argument that the greatest value of sports science is related to optimizing the coach-athlete interface; to give the athlete a smarter, better-informed coach. Accepting the premise that the proper role of sport science is to inform and support the coach-athlete relationship, we need to ask what the coach needs from the sport-science community. A reasonable approximation is provided in Table 1. The reality is that sports scientists are rather good at providing the first 2 of these needs to the coach but less good at the last 2. As addressed previously, 9 index workouts could be performed routinely by groups of athletes as a normal part of the training program, giving the coach high-frequency data useful for predicting progress toward training goals, and decision making regarding when the training program needs to be modified. The laboratory, is hard to schedule, is not well suited to testing large numbers of athletes quickly, and is not available for high-frequency testing. It is also much harder to provide the information which the coach needs to " translate " the results of the training to specif-ics about the progress and performance of the athlete (Figure 1).
Training monitoring is about keeping track of what athletes accomplish in training, for the purpose of improving the interaction between coach and athlete. Over history there have been several basic schemes of training monitoring. In the earliest days training monitoring was about observing the athlete during standard workouts. However, difficulty in standardizing the conditions of training made this process unreliable. With the advent of interval training, monitoring became more systematic. However, imprecision in the measurement of HR evolved interval training toward index workouts, where the main monitored parameter was average time required to complete index workouts. These measures of training load focused on the external training load, what the athlete could actually do. With the advent of interest from the scientific community, the development of the concept of metabolic thresholds, and the possibility of trackside measurement of HR, lactate, VO2 and power output, there was greater interest in the internal training load, allowing better titration of training loads in athletes of differing ability. These methods show much promise, but often require laboratory testing for calibration, and tend to produce too much information, in too slow of a time frame, to be optimally useful to coaches. The advent of the TRIMP concept by Banister suggested a strategy to combine intensity and duration elements of training into a single index concept, training LOAD. Although the original TRIMP concept was mathematically complex, the development of the Session RPE and similar low tech methods has demonstrated a way to evaluate training LOAD, along with derived variables, in a simple, responsive way. Recently, there has been interest in using wearable sensors to provide high resolution data of the external training load. These methods are promising, but problems relative to information overload and turn-around time to coaches remain to be solved.
Resistance exercise is difficult to quantify owing to its inherent complexity with numerous training variables contributing to the training dose (type of exercise, load lifted, training volume, inter-set rest periods, and repetition velocity). In addition, the intensity of resistance training is often inadequately determined as the relative load lifted (% 1-repetition maximum), which does not account for the effects of inter-set recovery periods, repetition velocity, or the number of repetitions performed in each set at a given load. Methods to calculate the volume load associated with resistance training, as well as the perceived intensity of individual sets and entire training sessions have been shown to provide useful information regarding the actual training stimulus. In addition, questionnaires to subjectively assess how athletes are coping with the stressors of training and portable technologies to quantify performance variables such as concentric velocity may also be valuable. However, while several methods have been proposed to quantify resistance training, there is not yet a consensus regarding how these methods can be best implemented and integrated to complement each other. Therefore, the purpose of this review is to provide practical information for strength coaches to highlight effective methods to assess resistance training, and how they can be integrated into a comprehensive monitoring program.
Many athletes, coaches, and support staff are taking an increasingly scientific approach to both designing and monitoring training programs. Appropriate load monitoring can aid in determining whether an athlete is adapting to a training program and in minimizing the risk of developing non-functional overreaching, illness, and/or injury. In order to gain an understanding of the training load and its effect on the athlete, a number of potential markers are available for use. However, very few of these markers have strong scientific evidence supporting their use, and there is yet to be a single, definitive marker described in the literature. Research has investigated a number of external load quantifying and monitoring tools, such as power output measuring devices, time-motion analysis, as well as internal load unit measures, including perception of effort, heart rate, blood lactate, and training impulse. Dissociation between external and internal load units may reveal the state of fatigue of an athlete. Other monitoring tools used by high-performance programs include heart rate recovery, neuromuscular function, biochemical/hormonal/immunological assessments, questionnaires and diaries, psychomotor speed, and sleep quality and quantity. The monitoring approach taken with athletes may depend on whether the athlete is engaging in individual or team sport activity; however, the importance of individualization of load monitoring cannot be over emphasized. Detecting meaningful changes with scientific and statistical approaches can provide confidence and certainty when implementing change. Appropriate monitoring of training load can provide important information to athletes and coaches; however, monitoring systems should be intuitive, provide efficient data analysis and interpretation, and enable efficient reporting of simple, yet scientifically valid, feedback.
High-intensity interval training (HIT) is a well-known, time-efficient training method for improving cardiorespiratory and metabolic function and, in turn, physical performance in athletes. HIT involves repeated short (<45 s) to long (2-4 min) bouts of rather high-intensity exercise interspersed with recovery periods (refer to the previously published first part of this review). While athletes have used 'classical' HIT formats for nearly a century (e.g. repetitions of 30 s of exercise interspersed with 30 s of rest, or 2-4-min interval repetitions ran at high but still submaximal intensities), there is today a surge of research interest focused on examining the effects of short sprints and all-out efforts, both in the field and in the laboratory. Prescription of HIT consists of the manipulation of at least nine variables (e.g. work interval intensity and duration, relief interval intensity and duration, exercise modality, number of repetitions, number of series, between-series recovery duration and intensity); any of which has a likely effect on the acute physiological response. Manipulating HIT appropriately is important, not only with respect to the expected middle- to long-term physiological and performance adaptations, but also to maximize daily and/or weekly training periodization. Cardiopulmonary responses are typically the first variables to consider when programming HIT (refer to Part I). However, anaerobic glycolytic energy contribution and neuromuscular load should also be considered to maximize the training outcome. Contrasting HIT formats that elicit similar (and maximal) cardiorespiratory responses have been associated with distinctly different anaerobic energy contributions. The high locomotor speed/power requirements of HIT (i.e. ≥95 % of the minimal velocity/power that elicits maximal oxygen uptake [v/p[Formula: see text]O2max] to 100 % of maximal sprinting speed or power) and the accumulation of high-training volumes at high-exercise intensity (runners can cover up to 6-8 km at v[Formula: see text]O2max per session) can cause significant strain on the neuromuscular/musculoskeletal system. For athletes training twice a day, and/or in team sport players training a number of metabolic and neuromuscular systems within a weekly microcycle, this added physiological strain should be considered in light of the other physical and technical/tactical sessions, so as to avoid overload and optimize adaptation (i.e. maximize a given training stimulus and minimize musculoskeletal pain and/or injury risk). In this part of the review, the different aspects of HIT programming are discussed, from work/relief interval manipulation to HIT periodization, using different examples of training cycles from different sports, with continued reference to the cardiorespiratory adaptations outlined in Part I, as well as to anaerobic glycolytic contribution and neuromuscular/musculoskeletal load.
Is determination of exercise intensities as percentages of V̇O2max or HRmax adequate? Med. Sci. Sports Exerc., Vol. 31, No. 9, pp. 1342-1345, 1999. Often exercise intensities are defined as percentages of maximal oxygen uptake (V̇O2max) or heart rate (HRmax).
Purpose: The purpose of this investigation was to test the applicability of these criteria in comparison with the individual anaerobic threshold.
Methods: One progressive cycling test to exhaustion (initial stage 100 W, increment 50 W every 3 min) was analyzed in a group of 36 male cyclists and triathletes (24.9 ± 5.5 yr; 71.6 ± 5.7 kg; V̇O2max: 62.2 ± 5.0 mL·min-1·kg-1; individual anaerobic threshold = IAT: 3.64 ± 0.41 W·kg-1; HRmax: 188 ± 8 min). Power output and lactate concentrations for 60 and 75% of V̇O2max as well as for 70 and 85% of HRmax were related to the LAT.
Results: There was no significant difference between the mean value of IAT (261 ± 34 W, 2.92 ± 0.65 mmol·L-1), 75% of V̇O2max (257 ± 24 W, 2.84 ± 0.92 mmol·L-1), and 85% of HRmax (259 ± 30 W, 2.98 ± 0.87 mmol·L-1). However, the percentages of the IAT ranged between 86 and 118% for 75% V̇O2max and 87 and 116% for 85% HRmax (corresponding lactate concentrations: 1.41-4.57 mmol·L-1 and 1.25-4.93 mmol·L-1, respectively). The mean values at 60% of V̇O2max (198 ± 19 W, 1.55 ± 0.67 mmol·L-1) and 70% of HRmax (180 ± 27 W, 1.45 ± 0.57 mmol·L-1) differed significantly (P < 0.0001) from the IAT and represented a wide range of intensities (66-91% and 53-85% of the IAT, 0.70-3.16 and 0.70-2.91 mmol·L-1, respectively).
Conclusions: In a moderately to highly endurance-trained group, the percentages of V̇O2max and HRmax vary considerably in relation to the IAT. As most physiological responses to exercise are intensity dependent, reliance on these parameters alone without considering the IAT is not sufficient.
It has not been established which physiological processes contribute to endurance training-related changes (Delta) in aerobic performance. For example, the relationship between intramuscular metabolic responses at the intensity used during training and improved human functional capacity has not been examined in a longitudinal study. In the present study we hypothesized that improvements in aerobic capacity (Vo(2max)) and metabolic control would combine equally to explain enhanced aerobic performance. Twenty-four sedentary males (24 +/- 2 yr; 1.81 +/- 0.08 m; 76.6 +/- 11.3 kg) undertook supervised cycling training (45 min at 70% of pretraining Vo(2max)) 4 times/wk for 6 wk. Performance was determined using a 15-min cycling time trial, and muscle biopsies were taken before and after a 10-min cycle at 70% of pretraining Vo(2max) to quantify substrate metabolism. Substantial interindividual variability in training-induced adaptations was observed for most parameters, yet "low responders" for DeltaVo(2max) were not consistently low responders for other variables. While Vo(2max) and time trial performance were related at baseline (r(2) = 0.80, P < 0.001), the change in Vo(2max) was completely unrelated to the change in aerobic performance. The maximal parameters DeltaVe(max) and DeltaVeq(max) (DeltaVe/Vo(2max)) accounted for 64% of the variance in DeltaVo(2max) (P < 0.001), whereas Deltaperformance was related to changes in the submaximal parameters Veq(submax) (r(2) = 0.33; P < 0.01), muscle Deltalactate (r(2) = 0.32; P < 0.01), and Deltaacetyl-carnitine (r(2) = 0.29; P < 0.05). This study demonstrates that improvements in high-intensity aerobic performance in humans are not related to altered maximal oxygen transport capacity. Altered muscle metabolism may provide the link between training stimulus and improved performance, but metabolic parameters do not change in a manner that relates to aerobic capacity changes.
Mental fatigue is a psychobiological state caused by prolonged periods of demanding cognitive activity. Although the impact of mental fatigue on cognitive and skilled performance is well known, its effect on physical performance has not been thoroughly investigated. In this randomized crossover study, 16 subjects cycled to exhaustion at 80% of their peak power output after 90 min of a demanding cognitive task (mental fatigue) or 90 min of watching emotionally neutral documentaries (control). After experimental treatment, a mood questionnaire revealed a state of mental fatigue (P = 0.005) that significantly reduced time to exhaustion (640 +/- 316 s) compared with the control condition (754 +/- 339 s) (P = 0.003). This negative effect was not mediated by cardiorespiratory and musculoenergetic factors as physiological responses to intense exercise remained largely unaffected. Self-reported success and intrinsic motivation related to the physical task were also unaffected by prior cognitive activity. However, mentally fatigued subjects rated perception of effort during exercise to be significantly higher compared with the control condition (P = 0.007). As ratings of perceived exertion increased similarly over time in both conditions (P < 0.001), mentally fatigued subjects reached their maximal level of perceived exertion and disengaged from the physical task earlier than in the control condition. In conclusion, our study provides experimental evidence that mental fatigue limits exercise tolerance in humans through higher perception of effort rather than cardiorespiratory and musculoenergetic mechanisms. Future research in this area should investigate the common neurocognitive resources shared by physical and mental activity.
I. PHYSIOLOGICAL SIGNIFICANCE
A. Significance of Adaptations to Environment
The ability of an animal to adapt to repeated bouts of physical exercise over a period of weeks such that exercise capacity is improved is termed physical training. Some of the inherent mechanisms that are crucial for adaptation to changes in the environment likely carry over to some of the adaptations occurring because of physical training. Prosser (316, 317) has written that cellular, organ, and systemic alterations that favor survival of an animal to an environmental change are said to be adaptive. Physical exercise, like environmental change, disrupts the milieu interieur. Fisher (103) has emphasized that biochemical and physiological adaptations to a changed environment or physiological stimulus fall into two categories based on their duration . Cellular, organ, or systemic alterations that occur on the same time scale as a single exercise bout are said to be acute exercise responses. On the other hand, changes in cells, organs, or systems that persist for appreciable periods after or as a consequence of physical training are said to be exercise adaptations. A function of exercise adaptation seems to be to minimize disruption of homeostasis during an exercise bout. It is this better maintenance of the milieu interieur by the exercise adaptations that favors the functional effectiveness of the animal beyond the resting state. Less disruption in homeostasis permits the animal or human to undergo physical work for longer durations at the same absolute power before fatigue. This review considers molecular and cellular responses to exercise that may signal molecular and cellular adaptations during physical training.
B. Significance of Adaptations to Exercise
This review is organized to use some of the known causes of fatigue during physical exercise as links between molecular and cellular changes that occur as a result of physical training and the chronic adaptations that are characteristic of physical training. One can speculate that adaptations that improved an animal's work capacity enhanced its survival. The genetic ability to alter exercise performance through physical training has not been lost along the evolutionary scale. Consequently, not all known molecular and cellular changes to exercise are considered here ; this is because their function may not yet be recognized to be associated with adaptations that ameliorate fatigue. In addition, this review does not repeat in great detail material that is available in other reviews. There are 11,689 documents for the Medline MESH word "exertion," Medline's term for exercise, between 1984-1989, inclusive. To the reader unfamiliar with the causes of fatigue during physical exertion, enough description has been given (Table 1) to permit understanding of the physiological significance of the molecular and cellular events. A more detailed review on fatigue is available (108) . In addition, the reader is referred to earlier reviews that have comprehensively documented biochemical responses to a single exercise bout and biochemical adaptations of muscle to physical training.
The ability to accurately control and monitor internal training load is an important aspect of effective coaching. The aim of this study was to apply in soccer the RPE-based method proposed by Foster et al. to quantify internal training load (session-RPE) and to assess its correlations with various methods used to determine internal training load based on the HR response to exercise.
Nineteen young soccer players (mean +/- SD: age 17.6 +/- 0.7 yr, weight 70.2 +/- 4.7 kg, height 178.5 +/- 4.8 cm, body fat 7.5 +/- 2.2%, VO2max, 57.1 +/- 4.0 mL x kg x min) were involved in the study. All subjects performed an incremental treadmill test before and after the training period during which lactate threshold (1.5 mmol x L above baseline) and OBLA (4.0 mmol x L) were determined. The training loads completed during the seven training weeks were determined multiplying the session RPE (CR10-scale) by session duration in minutes. These session-RPE values were correlated with training load measures obtained from three different HR-based methods suggested by Edwards, Banister, and Lucia, respectively.
Individual internal loads of 479 training sessions were collected. All individual correlations between various HR-based training load and session-RPE were statistically significant (from r = 0.50 to r = 0.85, P < 0.01).
The results of this study show that the session-RPE can be considered a good indicator of global internal load of soccer training. This method does not require particular expensive equipment and can be very useful and practical for coaches and athletic trainer to monitor and control internal load, and to design periodization strategies.
Physiological assessment of soccer training usually refers to the measurement of anatomical, physiological, biochemical and functional changes specific to the sport discipline (training outcome). The quality, quantity and organization of physical exercises (training process) are, on the other hand, usually described by the external work imposed by the coach on his or her athletes. In this review, we demonstrate that this approach is not appropriate in soccer, as training is often based on group exercises. The physiological stress (internal load) induced by such training often differs between individuals. Here, we present some physiological laboratory-based tests and field tests used to evaluate training outcomes in soccer, together with methods based on heart rate and perceived exertion to quantify internal load imposed during training. The integrated physiological assessment of both training outcome and process allows researchers: (1) to improve interpretation of physical tests used to verify the effectiveness of training programmes; (2) to evaluate the organization of the training load in order to design periodization strategies; (3) to identify athletes who are poor responders; (4) to control the compliance of the training completed to that planned by the coach; and (5) to modify the training process before the assessment of its outcome, thus optimizing soccer performance.
Locomotor muscle fatigue, defined as an exercise-induced reduction in maximal voluntary force, occurs during prolonged exercise, but its effects on cardiorespiratory responses and exercise performance are unknown. In this investigation, a significant reduction in locomotor muscle force (-18%, P < 0.05) was isolated from the metabolic stress usually associated with fatiguing exercise using a 100-drop-jumps protocol consisting of one jump every 20 s from a 40-cm-high platform. The effect of this treatment on time to exhaustion during high-intensity constant-power cycling was measured in study 1 (n = 10). In study 2 (n = 14), test duration (871 +/- 280 s) was matched between fatigue and control condition (rest). In study 1, locomotor muscle fatigue caused a significant curtailment in time to exhaustion (636 +/- 278 s) compared with control (750 +/- 281 s) (P = 0.003) and increased cardiac output. Breathing frequency was significantly higher in the fatigue condition in both studies despite similar oxygen consumption and blood lactate accumulation. In study 2, high-intensity cycling did not induce further fatigue to eccentrically-fatigued locomotor muscles. In both studies, there was a significant increase in heart rate in the fatigue condition, and perceived exertion was significantly increased in study 2 compared with control. These results suggest that locomotor muscle fatigue has a significant influence on cardiorespiratory responses and exercise performance during high-intensity cycling independently from metabolic stress. These effects seem to be mediated by the increased central motor command and perception of effort required to exercise with weaker locomotor muscles.
The global epidemic of obesity and its associated chronic diseases is largely attributed to an imbalance between caloric intake and energy expenditure. While physical exercise remains the best solution, the development of muscle-targeted "exercise mimetics" may soon provide a pharmaceutical alternative to battle an increasingly sedentary lifestyle. At the same time, these advances are fueling a raging debate on their escalating use as performance-enhancing drugs in high-profile competitions such as the Olympics.
Purpose:
To describe the training demands of contemporary dance and determine the validity of using the session-RPE (sRPE) method to monitor exercise intensity and training load in this activity. In addition, we examined the contribution of training (i.e. accelerometry and heart rate) and non-training related factors (i.e. sleep and wellness) to perceived exertion during dance training.
Methods:
Training load and actigraphy for sixteen elite amateur contemporary dancers were collected during a 49 day period, using heart rate monitors, accelerometry and sRPE. Within-individual correlation analysis was used to determine relationships between sRPE and several other measures of training intensity and load. Stepwise multiple regressions were used to determine a predictive equation to estimate sRPE during dance training.
Results:
Average weekly training load was 4283 ±2442 AU, monotony 2.13 ±0.92 AU, strain 10677± 9438 AU, and average weekly vector magnitude load 1809707 ±1015402 AU. There were large-to-very large within-individual correlations between sRPE-TL and various other internal and external measures of intensity and load. The stepwise multiple regression analysis also revealed that 49.7% of the adjusted variance in sRPE-TL was explained by HRpeak, METs, soreness, motivation and sleep quality (Y = -4.637 + 13.817 %HRpeak + 0.316 METS + 0.100 soreness + 0.116 motivation - 0.204 sleep quality).
Conclusion:
The current findings demonstrate; the validity of the sRPE method for quantifying training load in dance, that dancers undertake very high training loads and a combination of training and non-training factors contribute to perceived exertion in dance training.
The need to quantify aspects of training in order to improve training prescription has been the holy grail of sport scientists and coaches for many years. Recently, there has been an increase in scientific interest, possibly due to technological advancements and better equipment to quantify training activities. Over the last few years there has been an increase in the number of studies assessing training load in various athletic cohorts with a bias towards subjective reports and/or quantifications of external load. It is evident the lack of extensive longitudinal studies employing objective internal load measurements possibly due to the cost/effectiveness and the invasiveness of measures necessary to quantify objective internal loads. Advances in technology might help in developing better wearable tools able to ease the difficulties and costs associated with conducting longitudinal observational studies in athletic cohorts and possibly provide better information on the biological implications of specific external load patterns. Considering the recent technological developments for monitoring training load and the extensive use of various tools for research and applied work, the aim of this work was to review applications, challenges and opportunities of various wearable technologies.
The response to an exercise intervention is often described in general terms, with the assumption that the group average represents a typical response for most individuals. In reality, however, it is more common for individuals to show a wide range of responses to an intervention rather than a similar response. This phenomenon of 'high responders' and 'low responders' following a standardized training intervention may provide helpful insights into mechanisms of training adaptation and methods of training prescription. Therefore, the aim of this review was to discuss factors associated with inter-individual variation in response to standardized, endurance-type training. It is well-known that genetic influences make an important contribution to individual variation in certain training responses. The association between genotype and training response has often been supported using heritability estimates; however, recent studies have been able to link variation in some training responses to specific single nucleotide polymorphisms. It would appear that hereditary influences are often expressed through hereditary influences on the pre-training phenotype, with some parameters showing a hereditary influence in the pre-training phenotype but not in the subsequent training response. In most cases, the pre-training phenotype appears to predict only a small amount of variation in the subsequent training response of that phenotype. However, the relationship between pre-training autonomic activity and subsequent maximal oxygen uptake response appears to show relatively stronger predictive potential. Individual variation in response to standardized training that cannot be explained by genetic influences may be related to the characteristics of the training program or lifestyle factors. Although standardized programs usually involve training prescribed by relative intensity and duration, some methods of relative exercise intensity prescription may be more successful in creating an equivalent homeostatic stress between individuals than other methods. Individual variation in the homeostatic stress associated with each training session would result in individuals experiencing a different exercise 'stimulus' and contribute to individual variation in the adaptive responses incurred over the course of the training program. Furthermore, recovery between the sessions of a standardized training program may vary amongst individuals due to factors such as training status, sleep, psychological stress, and habitual physical activity. If there is an imbalance between overall stress and recovery, some individuals may develop fatigue and even maladaptation, contributing to variation in pre-post training responses. There is some evidence that training response can be modulated by the timing and composition of dietary intake, and hence nutritional factors could also potentially contribute to individual variation in training responses. Finally, a certain amount of individual variation in responses may also be attributed to measurement error, a factor that should be accounted for wherever possible in future studies. In conclusion, there are several factors that could contribute to individual variation in response to standardized training. However, more studies are required to help clarify and quantify the role of these factors. Future studies addressing such topics may aid in the early prediction of high or low training responses and provide further insight into the mechanisms of training adaptation.
Often exercise intensities are defined as percentages of maximal oxygen uptake ((V) over dot O-2max) or heart rate (HRmax). Purpose: The purpose of this investigation was to test the applicability of these criteria in comparison with the individual anaerobic threshold. Methods: One progressive cycling test to exhaustion (initial stage 100 W. increment 50 W every 3 min) was analyzed in a group of 36 male cyclists and triathletes (24.9 +/- 5.5 yr; 71.6 +/- 5.7 kg; W. increment 50 W every 3 min) was analyzed in a group of 36 male cyclists and triathletes (24.9 +/- 5.5 yr; 71.6 +/- 5.7 kg; (V) over dot O-2max; 62.2 +/- 5.0 mL.min(-1).kg(-1); individual anaerobic threshold = IAT: 3.64 +/- 0.41 W.kg(-1); HRmax: 188 +/- 8 min). Power output and lactate concentrations for 60 and 75% of (V) over dot O-2max as well as for 70 and 85% of HRmax were related to the IAT. Results: There was no significant difference between the mean value of WT (261 +/- 34 W, 2.92 +/- 0.65 mmol.L-1), 75% of (V) over dot O-2max (257 +/- 24 W, 2.84 +/- 0.92 mmol.L-1), and 85% of HRmax (259 +/- 30 W, 2.98 +/- 0.87 mmol.L-1). However, the percentages of the IAT ranged between 86 and 118% for 75% (V) over dot O-2max and 87 and 116% for 85% HRmax (corresponding lactate concentrations: 1.41-4.57 mmol.L-1 and 1.25-4.93 mmol.L-1, respectively). The mean values at 60% of (V) over dot O-2max (198 +/- 19 W, 1.55 +/- 0.67 mmol.L-1) and 70% of HRmax (180 +/- 27 W, 1.45 +/- 0.57 mmol.L-1) differed significantly (P < 0.0001) from the WT and represented a wide range of intensities (66-91% and 53-85% of the IAT, 0.70-3.16 and 0.70-2.91 mmol.L-1, respectively). Conclusions: In a moderately to highly endurance-trained group, the percentages of (V) over dot O-2max and HRmax vary considerably in relation to the IAT. As most physiological responses to exercise are intensity dependent, reliance on these parameters alone without considering the IAT is not sufficient.
This article is devoted to the role of genetic variation and gene-exercise interactions in the biology of adaptation to exercise. There is evidence from genetic epidemiology research that DNA sequence differences contribute to human variation in physical activity level, cardiorespiratory fitness in the untrained state, cardiovascular and metabolic response to acute exercise, and responsiveness to regular exercise. Methodological and technological advances have made it possible to undertake the molecular dissection of the genetic component of complex, multifactorial traits, such as those of interest to exercise biology, in terms of tissue expression profile, genes, and allelic variants. The evidence from animal models and human studies is considered. Data on candidate genes, genome-wide linkage results, genome-wide association findings, expression arrays, and combinations of these approaches are reviewed. Combining transcriptomic and genomic technologies has been shown to be more powerful as evidenced by the development of a recent molecular predictor of the ability to increase VO2max with exercise training. For exercise as a behavior and physiological fitness as a state to be major players in public health policies will require that the role of human individuality and the influence of DNA sequence differences be understood. Likewise, progress in the use of exercise in therapeutic medicine will depend to a large extent on our ability to identify the favorable responders for given physiological properties to a given exercise regimen. © 2011 American Physiological Society. Compr Physiol 1:1603-1648, 2011.
Video match analysis is used for the assessment of physical performances of professional soccer players, particularly for the identification of "high intensities" considered as "high running speeds." However, accelerations are also essential elements setting metabolic loads, even when speed is low. We propose a more detailed assessment of soccer players' metabolic demands by video match analysis with the aim of also taking into account accelerations.
A recent study showed that accelerated running on a flat terrain is equivalent to running uphill at constant speed, the incline being dictated by the acceleration. Because the energy cost of running uphill is known, this makes it possible to estimate the instantaneous energy cost of accelerated running, the corresponding instantaneous metabolic power, and the overall energy expenditure, provided that the speed (and acceleration) is known. Furthermore, the introduction of individual parameters makes it possible to customize performance profiles, especially as it concerns energy expenditure derived from anaerobic sources. Data from 399 "Serie-A" players (mean +/- SD; age = 27 +/- 4 yr, mass = 75.8 +/- 5.0 kg, stature = 1.80 +/- 0.06 m) were collected during the 2007-2008 season.
Mean match distance was 10,950 +/- 1044 m, and average energy expenditure was 61.12 +/- 6.57 kJ x kg(-1). Total distance covered at high power (>20 W x kg(-1)) amounted to 26% and corresponding energy expenditure to approximately 42% of the total. "High intensities" expressed as high-power output are two to three times larger than those based only on running speed.
The present approach for the assessment of top-level soccer players match performance through video analysis allowed us to assess instantaneous metabolic power, thus redefining the concept of "high intensity" on the basis of actual metabolic power rather than on speed alone.
Detraining is the partial or complete loss of training-induced adaptations, in response to an insufficient training stimulus. Detraining characteristics may be different depending on the duration of training cessation or insufficient training. Short term detraining (less than 4 weeks of insufficient training stimulus) is analysed in part I of this review, whereas part II will deal with long term detraining (more than 4 weeks of insufficient training stimulus). Short term cardiorespiratory detraining is characterised in highly trained athletes by a rapid decline in maximal oxygen uptake (VO2max) and blood volume. Exercise heart rate increases insufficiently to counterbalance the decreased stroke volume, and maximal cardiac output is thus reduced. Ventilatory efficiency and endurance performance are also impaired. These changes are more moderate in recently trained individuals. From a metabolic viewpoint, short term inactivity implies an increased reliance on carbohydrate metabolism during exercise, as shown by a higher exercise respiratory exchange ratio, and lowered lipase activity, GLUT-4 content, glycogen level and lactate threshold. At the muscle level, capillary density and oxidative enzyme activities are reduced. Training-induced changes in fibre cross-sectional area are reversed, but strength performance declines are limited. Hormonal changes include a reduced insulin sensitivity, a possible increase in testosterone and growth hormone levels in strength athletes, and a reversal of short term training-induced adaptations in fluid-electrolyte regulating hormones.
The development of performance in competition is achieved through a training process that is designed to induce automation of motor skills and enhance structural and metabolic functions. Training also promotes self-confidence and a tolerance for higher training levels and competition. In general, there are two broad categories of athletes that perform at the highest level: (i) the genetically talented (the thoroughbred); and (ii) those with a highly developed work ethic (the workhorse) with a system of training guiding their effort. The dynamics of training involve the manipulation of the training load through the variables: intensity, duration and frequency. In addition, sport activities are a combination of strength, speed and endurance executed in a coordinated and efficient manner with the development of sport-specific characteristics. Short- and long-term planning (periodisation) requires alternating periods of training load with recovery for avoiding excessive fatigue that may lead to overtraining. Overtraining is long-lasting performance incompetence due to an imbalance of training load, competition, non-training stressors and recovery. Furthermore, annual plans are normally constructed in macro-, meso- and microcycles around the competitive phases with the objective of improving performance for a peak at a predetermined time. Finally, at competition time, optimal performance requires a healthy body, and integration of not only the physiological elements but also the psychological, technical and tactical components.
Electromyographic (EMG) activity of the leg muscles and the ground reaction forces were recorded in 17 elite male middle-distance runners, who performed isometric maximal voluntary contractions (MVC) as well as running at different speeds. Electromyograms were recorded from the gluteus maximus, vastus lateralis, biceps femoris, gastrocnemius and tibialis anterior. The results indicated that the averaged EMG (aEMG) activities of all the muscles studied increased (P < 0.05) with increasing running speed, especially in the pre-contact and braking phases. At higher speeds, the aEMG activities of the gastrocnemius, vastus lateralis, biceps femoris and gluteus maximus exceeded 100% MVC in these same phases. These results suggest that maximal voluntary contractions cannot be used as an indicator of the full activation potential of human skeletal muscle. Furthermore, the present results suggest that increased pre-contact EMG potentiates the functional role of stretch reflexes, which subsequently increases tendomuscular stiffness and enhances force production in the braking and/or propulsive phases in running. Furthermore, a more powerful force production in the optimal direction for increasing running speed effectively requires increased EMG activity of the two-joint muscles (biceps femoris, rectus femoris and gastrocnemius) during the entire running cycle.
Monitoring training load in Italian football. Paper presented at: 8th Annual Congress of the European College of Sport Science
- F M Impellizzeri
Impellizzeri FM. Monitoring training load in Italian football. Paper
presented at: 8th Annual Congress of the European College of Sport
Science; 2003. Salzburg, Austria.
Developing athlete monitoring systems: theoretical basis and practical applications
- A J Coutts
- S Crowcroft
- T Kempton
Coutts AJ, Crowcroft S, Kempton T. Developing athlete monitoring
systems: theoretical basis and practical applications. In: Kellmann M,
Beckmann J, eds. Sport, Recovery and Performance: Interdisciplinary Insights. Abingdon, UK: Routledge; 2018:19-32.
- I D Pubmed
PubMed ID: 18184760 doi:10.1152/ajpregu.00678.2007