Dataset Information

Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League.

ABSTRACT: This study aimed to develop a model to objectively benchmark professional Australian Rules football (AF) player performance based on age, experience, positional role and both draft type and round in the Australian Football League (AFL). The secondary aims were to identify the stage of peak performance and specific breakpoints in AF player performance longitudinally. AFL Player Ratings data were obtained for all players (n = 1052) from the 1034 matches played during the 2013-2017 seasons, along with data pertaining to the abovementioned player characteristics. Two separate linear mixed models revealed that all factors influenced player performance, with age and experience the strongest in each model, respectively. Post hoc Tukey tests indicated that performance was affected by age at each level up until the age of 21 (effect ranging from 0.98 to 3.70 rating points), and by experience at the levels 1-20 and 21-40 matches in comparison to all higher levels of experience (effect ranging from 1.01 to 3.77 rating points). Two segmented models indicated that a point of marginal gains exists within longitudinal performance progression between the age levels 22 and 23, and the experience levels 41-60 and 61-80 matches. Professional sporting organisations may apply the methods provided here to support decisions regarding player recruitment and development.

SUBMITTER: McIntosh S

PROVIDER: S-EPMC6554430 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League.

McIntosh Sam S Kovalchik Stephanie S Robertson Sam S

Frontiers in psychology 20190531

This study aimed to develop a model to objectively benchmark professional Australian Rules football (AF) player performance based on age, experience, positional role and both draft type and round in the Australian Football League (AFL). The secondary aims were to identify the stage of peak performance and specific breakpoints in AF player performance longitudinally. AFL Player Ratings data were obtained for all players (<i>n</i> = 1052) from the 1034 matches played during the 2013-2017 seasons, ...[more]

PMID: 31214087

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Project description:Player evaluation plays a fundamental role in the decision-making processes of professional sporting organisations. In the Australian Football League, both subjective and objective evaluations of player match performance are commonplace. This study aimed to identify the extent to which performance indicators can explain subjective ratings of player performance. A secondary aim was to compare subjective and objective ratings of player performance. Inside Football Player Ratings (IFPR) and Australian Football League Player Ratings were collected as subjective and objective evaluations of player performance, respectively, for each player during all 1026 matches throughout the 2013-2017 Australian Football League seasons. Nine common player performance indicators, player role classification, player age and match outcomes were also collected. Standardised linear mixed model and recursive partitioning and regression tree models were undertaken across the whole dataset, as well as separately for each of the seven player roles. The mixed model analysis produced a model associating the performance indicators with IFPR at a root mean square error of 0.98. Random effects accounting for differences between seasons and players ranged by 0.09 and 1.73 IFPR each across the five seasons and 1052 players, respectively. The recursive partitioning and regression tree model explained IFPR exactly in 35.8% of instances, and to within 1.0 IFPR point in 81.0% of instances. When analysed separately by player role, exact explanation varied from 25.2% to 41.7%, and within 1.0 IFPR point from 70.3% to 88.6%. Overall, kicks and handballs were most associated with the IFPR. This study highlights that a select few features account for a majority of the variance when explaining subjective ratings of player performance, and that these vary by player role. Australian Football League organisations should utilise both subjective and objective assessments of performance to gain a better understanding of the differences associated with subjective performance assessment.

Project description:Introduction: Accurate interpretation of activity profile data requires an understanding of the variables influencing player movement during matches. Methods: Over 65,000 stints (player rotations) from all 207 matches of the 2018 Australian Football League (AFL) season were evaluated. The relative activity profile including total distance per minute (TD), high-speed running distance per minute (HSR) and Player LoadTM per minute (PL) was determined for each stint and analysed against a range of match-related, player-related and environment-related predictor variables using multivariate linear mixed modelling. Effect size statistics along with the uncertainty in the estimates (95% confidence interval) were used to interpret the findings. Results: The smallest important effects on TD, HSR, and PL were calculated as 1.5%, 5.5%, and 2.4%, respectively. Stint duration had small to moderate negative effects on TD (-6%), PL (-7.7%), and HSR (-13%), while recovery duration between stints had a small positive effect on HSR (+7%). There were moderate reductions in TD (-8%), HSR (-23%), and PL (-9.6%) in the last quarter compared to the first quarter of matches, while similar reductions existed in subsequent stints compared to the first stint in each quarter. Moderate to large differences of up to 9% in TD, 48% in HSR and 12% in PL existed between positions. The TD of less experienced players was slightly higher than their more experienced counterparts (2-3%). A 5% increase in body mass was associated with a small reduction in HSR (-5.5%). There were small reductions in TD (-2%), HSR (-10%), and PL (-3%) during the Finals Series compared to the Premiership Season. Moderate levels of rainfall during matches and higher apparent temperatures had small negative effects on TD (-2%) and HSR (-6 and -9%). The number of days break between matches, score margin, match outcome, ground hardness, ground size, and traveling for the current or the previous match had trivial effects on the activity profile. Conclusion: Player position and stage of the match (quarter) had the largest effects on match activity profile while stint duration, recovery duration, stint timing, professional experience, body mass, stage of the season, and weather conditions also had substantial effects.

Project description:CONTEXT:Postconcussion deficits in neurocognitive performance and postural control may persist at the time of return to sport participation. How these deficits, if present, affect athletic performance is largely unknown, with prior studies showing mixed results. OBJECTIVE:To evaluate postconcussion National Hockey League player performance using advanced hockey metrics over short- (5 games), medium- (10 games), and long-term (remainder of the season) seasonal performance. DESIGN:Retrospective cohort study. PATIENTS OR OTHER PARTICIPANTS:National Hockey League players who sustained a sport-related concussion (SRC; n = 93) and returned during the same season and players (n = 51) who missed time for non-injury-related reasons. MAIN OUTCOME MEASURE(S):Six performance metrics were used: (1) points per 60 minutes, (2) Corsi percentage, (3) personal Fenwick shooting percentage, (4) scoring chances per 60 minutes, (5) penalty difference, and (6) PDO (not an acronym but sometimes referred to as SVSP% [save percentage shooting percentage]). Performance was compared using 2 (group) × 2 (time) repeated-measures analyses of variance for 3 time windows: (1) ±5 games, (2) ±10 games, and (3) the remainder of the season postconcussion. Alpha values were set at a conservative .01 to account for the lack of independence among dependent variables. RESULTS:No significant interactions were present for any of the 6 dependent variables at any of the 3 time windows. Overall, none of the secondary variables differed. CONCLUSIONS:Using advanced, sport-specific metrics, we found that National Hockey League players did not display worse seasonal performance during 3 postinjury time frames after they sustained an SRC. Whereas laboratory studies have identified lingering neurologic deficits after concussion, our results suggest that these deficits, if present, either do not translate to worse athletic performance or were not captured by these 44 metrics. Further, prospective efforts are needed to accurately quantify performance after SRC among professional hockey players.

Dataset Information

Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League.

Publications

Multifactorial Benchmarking of Longitudinal Player Performance in the Australian Football League.

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