External Load Fluctuations Across an Amateur Athletic Union Basketball Season.

ABSTRACT: Kutson, CW, Russell, JL, Strack, D, Coutts, AJ, and McLean, BD. External load fluctuations across an Amateur Athletic Union basketball season. J Strength Cond Res 38(3): 592-598, 2024-Amateur Athletic Union (AAU) competitions are an important component of the developmental pathway for youth basketball athletes. Despite its relative importance, there is currently a paucity of research investigating the physical demands in AAU basketball. Therefore, the purpose of this study was to examine the physical demands encountered over the course of an AAU basketball season. External training load was quantified using inertial sensors (Catapult T6) from one male AAU basketball team (age: 17.5 ± 0.5 years, height: 197.3 ± 10.0 cm, and mass: 89.4 ± 11.6 kg) over the course of the 2021 AAU season and categorized post hoc into high-, medium-, and low-minute groups based on mean playing minutes. After player categorization, 2 linear mixed models were constructed, one for PlayerLoad (PL) and one for duration, to examine the differences across player category, month of the season, and activity types (practices or games). The results show that the highest training loads were encountered by high-minute players, who had total PLs of 9,766 ± 1,516 AU, 13,207 ± 2,561 AU, and 7,071 ± 2,122 AU during April, May, and June, respectively. Highly variable training loads were also evident over the course of a season, with peak PL values as high as 4,921 AU per week. Practitioners should be aware that AAU basketball players experience variable loads throughout the season, which peak around congested competition/tournament periods. In addition, players with high game minutes accumulate the most load over the course of a season. This information may be used to better inform planning and periodizing strategies during developmental phases.

The Relationship Between Mental Fatigue and Shooting Performance Over the Course of a National Collegiate Athletic Association Division I Basketball Season.

ABSTRACT: Daub, BD, McLean, BD, Heishman, AD, Peak, KM, and Coutts, AJ. The relationship between mental fatigue and shooting performance over the course of a National Collegiate Athletic Association Division I basketball season. J Strength Cond Res 38(2): 334-341, 2024-The aim of this investigation was to examine the presence of mental fatigue and concurrent changes in shooting performance across various experimental weeks throughout a National Collegiate Athletic Association (NCAA) basketball season. Fifteen elite male NCAA Division I collegiate basketball players (age 20.2 ± 1.2 years, height 199.3 ± 7.1 cm, and body mass 93.1 ± 8.6 kg) volunteered for this study. Mental fatigue and basketball shooting performance was evaluated at 4 timepoints with varying seasonal demands: high game volume (GAME), high academic load (ACADEMIC), no games and no academic load (PRACTICE), and standard number of games and academic requirements (TYPICAL). Subjective mental fatigue increased significantly ( p ≤ 0.05) from Pre to Post brief psychomotor vigilance test (PVT-B) measurements at the end of the ACADEMIC week ( p = 0.002, d = 1.51) and from beginning to end of the ACADEMIC week ( p < 0.001, d = 2.21). Ratings of mental effort were significantly increased during the ACADEMIC week ( p < 0.001, d = 1.67). Recovery stress questionnaire (REST-Q) showed significant differences between week GAME and ACADEMIC with an increase in Social Stress ( p = 0.001, d = 0.84), Fatigue ( p = 0.021, d = 1.12), Disturbed Breaks ( p = 0.024, d = 0.57), and Emotional Exhaustion ( p = 0.035, d = 0.75). Lower shooting performance was observed during the ACADEMIC week from Pre to Post ( p = 0.009, d = 0.35) and higher scores Pre to Post in the TYPICAL week ( p = 0.008, d = 0.25). Basketball shooting performance was significantly reduced after increased levels of mental fatigue stemming from added academic stress. In addition, an increase in sport-specific training or games had no effect on subsequent basketball shooting performance. Special consideration should be given by coaches around examination periods because the existence of academic stressors can influence basketball shooting performance.

How Do Young Soccer Players Train? A 5-Year Analysis of Weekly Training Load and its Variability Between Age Groups in an Elite Youth Academy.

ABSTRACT: Connolly, DR, Stolp, S, Gualtieri, A, Ferrari Bravo, D, Sassi, R, Rampinini, E, and Coutts, AJ. How do young soccer players train? A 5-year analysis of weekly training load and its variability between age groups in an elite youth academy. J Strength Cond Res 38(8): e423-e429, 2024-The aim of this study was to quantify the session rating of perceived exertion (sRPE), duration, and training load accrued across typical training weeks undertaken by youth soccer players. Differences between starters, nonstarters, and variations in training load variables were also investigated. Data were collected from 230 elite youth players in 4 age groups (U15, U16, U17, and U19) during 5 competitive seasons. Mixed models were used to describe variation between age groups and compare starters with nonstarters, with season as a fixed covariate effect. Week-to-week variation in training load was expressed as the percentage coefficient of variation. The main findings may be used to highlight a significant effect of age and playing status on training intensity, duration, and internal training load. Weekly training load increased progressively from the U15 to U17, with significant differences between each age group (p < 0.03). Lower mean weekly perceived intensity (sRPE) was noted in U15 when compared with the older age groups (4.2 vs. 4.6-4.9 arbitrary unit for U16 to U19, p < 0.001). Low weekly training load variation was observed across the different phases of the season in each age group, with the preseason exhibiting the greatest variance (3.6-6.2%). Differences in the training load are likely more attributable to changes in training duration rather than sRPE. Control of session duration seems to play an important role when aiming to control load in the academy environment, and practitioners should closely monitor the differences in duration and load being recorded between starters and nonstarters.

Contextual Factors Influencing Physical Activity and Technical Performance in Australian Football League Women's Competition Match-Play.

ABSTRACT: Leabeater, A, Clarke, A, and Sullivan, C. Contextual factors influencing physical activity and technical performance in AFLW competition match-play. J Strength Cond Res 37(1): 194-199, 2023-The purpose of this study was to examine the influence of contextual factors on physical activity and technical match performance during Australian Football League Women's (AFLW) competition match-play. The study was of a retrospective longitudinal design and used physical activity and technical data collected from female Australian Football players (n = 49) from 1 team during 23 AFLW competition games over 3 seasons. A three-level linear mixed model was constructed to investigate the influence of different contextual factors (match-related variables) on relative total distance (TD), relative high-speed running (HSR) distance, and ranking points during AFLW match-play. The results showed that from season 1 to season 3, relative TD increased by 2.0 m·min-1 (ES: 0.06 [-0.04 to 0.16], p < 0.05) and relative HSR increased by 4.1 m·min-1 (ES: 0.22 [0.14-0.31], p < 0.001). Interstate matches were associated with a reduction of 5.1 m·min-1 per match in TD (ES: -0.21 [-0.30 to -0.12], p < 0.001) and 2.5 m·min-1 in HSR distance (ES: -0.22 [-0.31 to -0.13], p < 0.001). Total disposals were associated with a 0.23 m·minute-1 reduction in HSR for that player (ES: -0.13 [-0.22 to 0.04], p < 0.01). Match margin was the only contextual factor to influence ranking points/min (0.007 AU·min-1, ES: 0.30 [0.21-0.38], p < 0.001). In conclusion, this study shows that player physical activity may be reduced during interstate AFLW matches; the average HSR has increased since the start of the AFLW competition and may reflect increasing match activity profiles, and players have a greater rate of accumulation of ranking points when the score difference is greater.

Sensitivity of Countermovement Jump Variables in Professional Rugby Union Players Within a Playing Season.

ABSTRACT: Howarth, DJ, McLean, BD, Cohen, DD, and Coutts, AJ. Sensitivity of countermovement jump variables in professional rugby union players within a playing season. J Strength Cond Res 37(7): 1463-1469, 2023-The aim of this study was to explore the measurement sensitivity of a wide range of countermovement jump (CMJ) variables to a full European professional rugby union season. A secondary purpose was to compare 3 different data treatment methods for the calculation of CMJ variables. Twenty-nine professional rugby union players (mean ± SD; age 24 ± 4 years, height 183.7 ± 8.0 cm, body mass 101.6 ± 10.7 kg) completed a minimum of 12 CMJ testing sessions on Thursdays-a day preceded by a rest day and a minimum of 96 hours after a match-throughout a season. Measurement sensitivity, quantified by signal-to-noise ratio (SNR), was determined for 74 CMJ variables and was calculated by dividing the signal, (week-to-week variation expressed as a coefficient of variation [CV%]) by the noise (interday test/retest reliability expressed as CV%). We also identified variables which had no overlap between the 95% confidence intervals (CIs) for the signal and the noise. The 3 data treatment methods for comparison were (a) mean output across 3 jump trials (Mean3), (b) single output from the trial with the highest jump (BestJH), and (c) the trial with the highest flight time to contraction time ratio (BestFTCT). Most variables had an SNR >1.0 (Mean3 = 60/74; BestFTCT = 59/74; BestJH = 48/74). Fewer variables displayed a nonoverlap of 95% CIs (Mean3 = 23/60; BestFTCT = 22/59; BestJH = 16/48). Most CMJ variables during a professional rugby season demonstrated a signal that exceeded measured noise (SNR > 1.0) and that using the Mean3 or BestFTCT data treatment methods yields a greater number of variables considered sensitive within a season (i.e., SNR > 1.0) than when using BestJH. We also recommend the calculation of the 95% CIs for both signal and noise, with nonoverlap indicative of a greater probability that the responsiveness of the variable at team level (i.e., SNR) also applies at the individual level. As sensitivity analysis is cohort and environment specific, practitioners should conduct a sensitivity analysis using internal signal and noise data to inform their own monitoring protocols.

Finding the Signal in the Noise-Interday Reliability and Seasonal Sensitivity of 84 Countermovement Jump Variables in Professional Basketball Players.

ABSTRACT: Mercer, RAJ, Russell, JL, McGuigan, LC, Coutts, AJ, Strack, DS, and McLean, BD. Finding the signal in the noise-interday reliability and seasonal sensitivity of 84 countermovement jump variables in professional basketball players. J Strength Cond Res 37(2): 394-402, 2023-This study examined the measurement characteristics of countermovement jump (CMJ) variables in basketball athletes using different variable selection criteria. Test-retest reliability (noise) and seasonal variability (signal) CMJ data were collected from 13 professional basketball athletes playing for the same club throughout 1 competitive season. Interday reliability (coefficient of variation [CV] and intraclass correlation coefficients) were calculated over 3 preseason tests conducted on 3 consecutive days. To evaluate sensitivity, signal-to-noise ratio (SNR) was calculated by dividing seasonal variability (CV) from 8 in-season CMJ tests (collected from November to February) by preseason reliability (CV). Players performed 3 CMJs each testing day, and 3 data analysis techniques were applied: a single variable from the trial with either the best jump height (BestJH; calculated by flight time) or the best flight time to contraction time (BestFT:CT) and mean output across 3 jumps (Mean3). Mean3 was the most reliable data analysis technique, with 79 and 82 of 84 variables displaying lower interday CVs compared with BestJH and BestFT:CT, respectively. Overall, many CMJ measures display seasonal changes that are greater than the inherent noise, with 77 variables producing SNR of >1.00 for Mean3 compared with 65 and 58 variables for BestJH and BestFT:CT, respectively. To improve reliability and sensitivity, it is recommended that practitioners use the average of multiple CMJ trials and regularly reassess measurement characteristics specific to their cohort and environment.

Establishing the Noise: Interday Ecological Reliability of Countermovement Jump Variables in Professional Rugby Union Players.

ABSTRACT: Howarth, DJ, Cohen, DD, McLean, BD, and Coutts, AJ. Establishing the noise: interday ecological reliability of countermovement jump variables in professional rugby union players. J Strength Cond Res 36(11): 3159-3166, 2022-The purpose of this study was to examine the interday "ecological" reliability of a wide range of ground reaction force-derived countermovement jump (CMJ) variables. Thirty-six male, professional rugby union players performed 3 CMJs on 4 separate days over an 8-day period during the first week of preseason. We calculated reliability for 86 CMJ variables across 5 interday combinations using 2 criteria: mean output across 3 jump trials (Mean 3 ) and single output from the highest jump (Best JH ). Interday coefficient of variation (CV) of the 86 variables in each CMJ phase, for Mean 3 and Best JH , respectively, ranged between concentric = 2-11% and 2-13%; eccentric = 1-45% and 1-107%; and landing = 4-32% and 6-45%. Mean 3 interday CV was lower in all 86 variables across every interday combination, compared with Best JH . CVs were lower in our cohort than previous studies, particularly for eccentric phase variables. There was no meaningful difference between interday conditions, suggesting any 2-day combination conducted within the first 8 days of preseason, represents a measure of "noise." We did not apply arbitrary reliability "cut-offs" used in previous work (e.g., CV <10%); therefore, our analysis provides reference reliability for a wide range of CMJ variables. However, we recommend that practitioners assess reliability in their athletes, as it is likely to be environment, protocol, and cohort specific.

Biological maturation influences selection process in youth elite soccer players.

This study examined the influence of birth date, salivary testosterone [sT] concentration, sexual maturity status, and general strength on the selection process of an elite Brazilian soccer club during a 12-month period, which was a 2nd phase of a 24-month selection process. The stature, body mass, sT, sexual maturity status [Tanner scale], and hand grip strength were assessed for 143 players during 2 weeks. From these 143 players, 100 players were dismissed [DIS] and 43 players were selected to integrate the club's under-14 squad. Following 1-year training period, the under-14 team was assembled with 9 players designated as starters [STA], and then, comparisons were conducted taking into account a group of non-starters (selected; SEL = 34 players) and STA (n = 09). The DIS, SEL, STA players, and reference population, were compared for birth distribution. A greater proportion of players was born in the first trimester in the STA [75.0%], SEL [57.1%] and DIS [50.0%] groups compared to the reference population [25.8%]. One-way ANOVA showed a higher sT for STA group [516.0 ± 129.9 pmol·L-1], compared to SEL [415.5 ± 117.9 pmol·L-1] and DIS groups [390.9 ± 84.9 pmol·L-1; p = 0.003), and Kruskall-Wallis test showed a higher gonadal development for STA compared to DIS [p = 0.001]. The current findings suggest a strong influence of birth date and biological maturation on young soccer players selection process. Soccer coaches should consider these influences when making decisions about player selection of elite youth players.

Analysis of the worst-case scenarios in an elite football team: Towards a better understanding and application.

This study investigated the variability in the worst-case scenario (WCS) and suggested a framework to improve the definition and guide further investigation. Optical tracking data from 26 male players across 38 matches were analysed to determine the WCS for total distance, high-speed running (>5.5 m.s-1) and sprinting (>7.0 m.s-1) using a 3-minute rolling window. Position, total output, previous epoch, match half, time of occurrence, classification of starter vs substitute, and minutes played were modelled as selected contextual factors hypothesized to have associations with the WCS. Linear mixed effects models were used to account for cross-sectional observations and repeated measures. Unexplained variance remained high (total distance R2 = 0.53, high-speed running R2 = 0.53 and sprinting R2 = 0.40). Intra-individual variability was also high (total distance CV = 4.6-8.2%; high-speed CV = 15.6-37.8% and Sprinting CV = 21.1-76.4%). The WCS defined as the maximal physical load in a given time-window, produces unstable metrics lacking context, with high variability. Furthermore, training drills targetting this metric concurrently across players may not have representative designs and may underprepare athletes for complete match demands and multifaceted WCS scenarios. Using WCS as benchmarks (reproducing similar physical activity for training purposes) is conceptually questionable.

The Influence of Mental Fatigue on Sessional Ratings of Perceived Exertion in Elite Open and Closed Skill Sports Athletes.

ABSTRACT: Coyne, JOC, Coutts, AJ, Newton, RU, and Haff, GG. The influence of mental fatigue on sessional ratings of perceived exertion in elite open and closed skill sports athletes. J Strength Cond Res 35(4): 963-969, 2021-The main purpose of this investigation was to examine influence of mental fatigue on sessional ratings of perceived exertion (sRPE) over a training week in elite athletes in open skill (OS, i.e., more unpredictable and externally paced sports) and closed skill (CS, i.e., more predictable and internally paced) sports. Visual analogue scales for mental fatigue, sRPE (CR-10 scale), and training duration were collected from an OS group (n = 27) of basketball and volleyball athletes and a CS group (n = 28) of weightlifting and track and field athletes during a typical training week 5 months before the 2016 Olympic Games. These variables were then examined using repeated measure correlations and linear mixed models with the level of significance set for the study at p < 0.05. There was a small significant correlation between mental fatigue and sRPE in the OS group (r = 0.23, p < 0.01), but not in the CS group (r = -0.07, p = 0.38). Mental fatigue had trivial influence on sRPE during individual sessions, but had a moderate effect on total sRPE over a week (p < 0.001, f2 = 0.265) when accounting for type of sport, training duration, and injury/illness burden. It seems mental fatigue may not significantly influence sRPE in individual training sessions, but may potentially have a cumulative effect that may affect the sRPE over a training week. This suggests monitoring mental fatigue independently of other training load (TL) measures may be worthwhile for strength and conditioning specialists and sports coaches to manage their athletes and researchers conducting studies into TL and performance.

Sleep and the athlete: narrative review and 2021 expert consensus recommendations.

Elite athletes are particularly susceptible to sleep inadequacies, characterised by habitual short sleep (<7 hours/night) and poor sleep quality (eg, sleep fragmentation). Athletic performance is reduced by a night or more without sleep, but the influence on performance of partial sleep restriction over 1-3 nights, a more real-world scenario, remains unclear. Studies investigating sleep in athletes often suffer from inadequate experimental control, a lack of females and questions concerning the validity of the chosen sleep assessment tools. Research only scratches the surface on how sleep influences athlete health. Studies in the wider population show that habitually sleeping <7 hours/night increases susceptibility to respiratory infection. Fortunately, much is known about the salient risk factors for sleep inadequacy in athletes, enabling targeted interventions. For example, athlete sleep is influenced by sport-specific factors (relating to training, travel and competition) and non-sport factors (eg, female gender, stress and anxiety). This expert consensus culminates with a sleep toolbox for practitioners (eg, covering sleep education and screening) to mitigate these risk factors and optimise athlete sleep. A one-size-fits-all approach to athlete sleep recommendations (eg, 7-9 hours/night) is unlikely ideal for health and performance. We recommend an individualised approach that should consider the athlete's perceived sleep needs. Research is needed into the benefits of napping and sleep extension (eg, banking sleep).

The efficacy of talent selection criteria in the Australian Football League.

This study investigated the association between talent selection criteria, draft order and match performance in professional Australian Football players. Physical performance results from the Australian Football League (AFL) National Draft combine and non-performance based talent selection criteria were collated for all players drafted in the National Draft with selections 1-80 between 2003 and 2008 (n = 318). Match performance was assessed via the AFL Player Ranking metric that was provided by a commercial statistical provider (Champion Data Pty Ltd). A combination of stepwise multiple regression and linear mixed model analyses examined the influence of National Draft combine physical performance assessments and non-performance based talent selection criteria on draft order and future match performance. Earlier draft selection was associated with Under-18 all Australian team selection, height, Under-18 National Championship participation and indigenous status. The 20 m sprint and state of origin were associated with later draft selection. Under-18 all Australian team selection increased both Player Ranking/game and total Player Ranking. Under-18 all Australian team selection displays efficacy for selecting players with the potential for success.

Perceptions and use of recovery strategies: Do swimmers and coaches believe they are effective?

This study aimed to investigate swimmer's use and coach prescription of recovery strategies during training and competition while examining perceived challenges, barriers, and beliefs in the importance of their effectiveness. A mixed-methods sequential explanatory design was implemented. Thirty-seven male and 45 female sub-elite to elite swimmers (age 18 ± 3 y), and 4 male and 6 female coaches (age 40 ± 9 y) completed an online, 78-item recovery strategy survey. Swimmers and coaches responded to questions regarding when, why, and how they used recovery strategies, perceived challenges and barriers to strategy inclusion during training and competition. Data were coded and analysed thematically. Fisher's Exact Test was conducted on 5-point Likert scale responses. Most recovery strategies were used and prescribed more during competition. Swimmers reported active recovery as the most effective recovery strategy (44%), whereas coaches rated sleep or napping (40%). Swimmers and coaches perceived most recovery strategies to be more effective and important during competition than in training. Swimmers used, and coaches prescribed, recovery strategies more during the competition, highlighting the discrepancies in use between training and competition. Targeted education programmes should enhance athletes and coach's recovery knowledge and practical application of strategies, while accounting for individual sport and life demands.

Understanding the presence of mental fatigue in English academy soccer players.

Research has demonstrated that induced mental fatigue impairs soccer-specific technical, tactical and physical performance in soccer players. The findings are limited by the lack of elite players and low ecological validity of the tasks used to induce mental fatigue, which do not resemble the cognitive demands of soccer. The current study collected survey data from English academy soccer players (n = 256; age groups - U14 - U23), with questions comprising of five themes (descriptors of physical and mental fatigue, travel, education, match-play and fixture congestion). The survey consisted of multiple choice responses, checkboxes and blinded/unblinded (for duration based questions) 0-100 arbitrary unit (AU) slider scales. Listening to music (81.6% of players), using social media (58.3%) and watching videos (34.3%) were the most common pre-match activities. Pre-match subjective mental fatigue was low (18.7±18.8 AU), and most frequently reported at the end of a match (47±26 AU) and remained elevated 24-hours post-match (36±27 AU). Travel (29±24 AU), fixture congestion (44±25 AU) and education (30±26 AU) demonstrated a low to moderate presence of subjective mental fatigue. These findings provide an overview of activities performed by English academy soccer players pre-match, and demonstrate that mental fatigue is experienced as a result of match-play.

Positional Demands and Physical Activity Profiles of Netball.

van Gogh, MJ, Wallace, LK, and Coutts, AJ. Positional demands and physical activity profiles of netball. J Strength Cond Res 34(5): 1422-1430, 2020-The aim of this study was to examine the activity profiles and physiological demands of netball. Eleven representative youth netball players participated in this study. Global positioning system, heart rate, and accelerometer data were collected during 8 competitive matches. Sport-specific skills were analyzed using notational methods. The main findings were that players traveled less distance during a match than previously reported. The center covered significantly greater distances than the other positions (p < 0.001). The goal shooter and goal keeper covered the least distance and endured lower accelerometer loads than other positions (p < 0.001). Very low levels of very high-speed running and sprint efforts were observed across all positions. The proportion of time spent in the high (>85% maximum heart rate [HRmax]) HR zone ranged from 7.0 to 62.6%, highlighting a high variation in cardiovascular demands between each position. The center and goal attack had the greatest cardiovascular demands spending significantly more time in the high (>85% HRmax) HR zone (p < 0.001). The goal shooter and goal keeper spent significantly more time in the low (<70% HRmax) HR zone (p < 0.001). Players in attacking positions were shown to pass/catch significantly more players than in defending positions (p < 0.001). Players in defending positions had higher number of deflections and intercepts compared with players in attacking positions (p < 0.001). These findings reveal significant positional differences in activity profiles and movement demands in netball. These data can be used to refine position-specific training practice and guide tactical strategies during competition.

Factors associated with early career progression in professional Australian Football players.

This study examined the association between individual and team characteristics and the probability of being offered a second contract in professional Australian Football. Contract status was obtained from the AFL for players who were drafted in the AFL National Draft between 1999 and 2013 (n = 999). Individual player characteristics were retrieved from the AFL while variables relating to performance were accessed online via Champion Data®. A binary logistic regression examined the influence of each characteristic on the probability of a professional Australian Football player receiving a second contract. Receiver operating characteristic (ROC) curves and the associated AUC were used to assess the discriminant ability of both a training (n = 938) and test data set (n = 61). The characteristics that influenced the probability of receiving a second contract included first year debut (pr 0.606), draft order (pr - 0.126), draft year (pr 0.059), games played (pr 1.848), team state (pr 0.458), rising star nomination (pr 1.553) and team ladder position (pr -0.043) (χ2 (8) = 198.28, p < 0.001). The ROC curve demonstrated an AUC of 82.4% (training) and 76.0% (test). A combination of individual and team based characteristics are associated with early career progression in professional Australian Football.

The physical profile of adult male basketball players: Differences between competitive levels and playing positions.

This study examined the physical differences in adult male basketball players of different competitive level and playing position using a large cohort. In the middle of the regular season, 129 players from four different Divisions completed a Yo-YoIR1 and, after 3-to-8 days, they performed a 6-min continuous running test (Mognoni's test), a counter-movement jump (CMJ) test and a 5-min High-intensity Intermittent running test (HIT). Magnitude-based inferences revealed that differences in HIT were very likely moderate between Division I and II and likely small between Division II and III. The differences in absolute peak power and force produced during CMJs between Division I and II and between Division II and III were possibly small. Differences in Yo-YoIR1 and Mognoni's test were very likely-to-almost certain moderate/large between Division III and VI. We observed possibly-to-likely small differences in HIT and Mognoni's test between guards and forwards and almost certainly moderate differences in absolute peak power and force during CMJs between guards and centres. The ability to sustain high-intensity intermittent efforts (i.e. HIT) and strength/power characteristics can differentiate between competitive level, while strength/power characteristics discriminate guards from forwards/centres. These findings inform practitioners on the development of identification programs and training activities in basketball.

Positional Differences in Running and Nonrunning Activities During Elite American Football Training.

Ward, PA, Ramsden, S, Coutts, AJ, Hulton, AT, and Drust, B. Positional differences in running and nonrunning activities during elite American football training. J Strength Cond Res XX(X): 000-000, 2017-The aim of this investigation was to describe differences in training loads between position groups within professional American football. Integrated micro technology data were collected on 63 NFL football players during an American football training camp. Five key metrics (total distance, high-speed distance, player load (PL), PL per minute, and total inertial movement analysis [IMA]) served to quantify both running and nonrunning activities. Players were classified into position groups (defensive back [DB], defensive linemen [DL], linebacker, offensive linemen [OL], quarterback, running back, tight end, and wide receiver [WR]). Training sessions were identified by their relationship to the upcoming match (e.g., -4, -3, and -2). Running and nonrunning activities varied between position groups relative to the training day. Differences in total distance between DB and WR were observed to be unclear across the 3 training days (game day [GD] -4: 74 ± 392 m; GD -3: -122 ± 348 m; and GD -2: -222 ± 371 m). However, moderate to large differences were observed between these 2 positions and the other positional groups. A similar relationship was observed in PL and PL per minute, with the DB and WR groups performing greater amounts of load compared with other positional groups. Differences in high-speed distance varied across positional groups, indicating different outputs based on ergonomic demands. The OL and DL groups ran less but engaged in a higher amount of nonrunning activities (total IMA) with differences ranging from moderate to large across the 3 training days. Total IMA differences between offensive and defensive linemen were unclear on GD -4 (-4 ± 9) and GD -2 (-2 ± 8) and likely moderate on GD -3 (-9 ± 9). Positional differences with regard to running and nonrunning activities highlight the existence of position-specific training within a training microcycle. In addition, total IMA provides a useful metric for quantifying sport-specific movements within the game of American football.

The expected value of possession in professional rugby league match-play.

This study estimated the expected point value for starting possessions in different field locations during rugby league match-play and calculated the mean expected points for each subsequent play during the possession. It also examined the origin of tries scored according to the method of gaining possession. Play-by-play data were taken from all 768 regular-season National Rugby League (NRL) matches during 2010-2013. A probabilistic model estimated the expected point outcome based on the net difference in points scored by a team in possession in a given situation. An iterative method was used to approximate the value of each situation based on actual scoring outcomes. Possessions commencing close to the opposition's goal-line had the highest expected point equity, which decreased as the location of the possession moved towards the team's own goal-line. Possessions following an opposition error, penalty or goal-line dropout had the highest likelihood of a try being scored on the set subsequent to their occurrence. In contrast, possessions that follow an opposition completed set or a restart were least likely to result in a try. The expected point values framework from our model has applications for informing playing strategy and assessing individual and team performance in professional rugby league.

Mental fatigue impairs soccer-specific decision-making skill.

This study aimed to investigate the impact of mental fatigue on soccer-specific decision-making. Twelve well-trained male soccer players performed a soccer-specific decision-making task on two occasions, separated by at least 72 h. The decision-making task was preceded in a randomised order by 30 min of the Stroop task (mental fatigue) or 30 min of reading from magazines (control). Subjective ratings of mental fatigue were measured before and after treatment, and mental effort (referring to treatment) and motivation (referring to the decision-making task) were measured after treatment. Performance on the soccer-specific decision-making task was assessed using response accuracy and time. Visual search behaviour was also assessed throughout the decision-making task. Subjective ratings of mental fatigue and effort were almost certainly higher following the Stroop task compared to the magazines. Motivation for the upcoming decision-making task was possibly higher following the Stroop task. Decision-making accuracy was very likely lower and response time likely higher in the mental fatigue condition. Mental fatigue had unclear effects on most visual search behaviour variables. The results suggest that mental fatigue impairs accuracy and speed of soccer-specific decision-making. These impairments are not likely related to changes in visual search behaviour.