The prevalence of relative age effects and the influence of the talent pool size on Australian male and female youth football.

The current study explored the association between talent pool size and relative age effects in Football Australia's talent pathway. It also compared relative age effects between male and female players. Participants were 54,207 youth football players (females: n = 12,527, age-range = 14.0-15.9; males: n = 41,680, age-range = 13.0-14.9) eligible for the National Youth Championships. We developed linear regression models to examine the association between the member federation size and the probability of a player being born earlier in the year. We also analysed selection probabilities based on birth quartile and year half across three layers. Overall, talent pool size was associated with a higher probability of selecting a player born in the first half of the year over the second. More specifically, an increase of 760 players led to a 1% higher selection probability for those born in the first six months of a chronological age group. In addition, there were more occurrences of relative age effects in the male than the female sample. Future studies should focus on the impact of the talent pool size on relative age effects at each major talent identification/selection stage of a talent pathway.

Match simulation practice may not represent competitive match play in professional Australian football.

Match simulation in team sport should sample representative constraints and behaviours to those observed in competitive matches to enhance near skill transfer. This study compared task constraints (field length, field width, length per width ratio, space per player), time-standardised skill metrics (goals, shots on goal, handballs, kicks, marks, turnovers, tackles, handball proficiency, kick proficiency) and cooperative passing metrics (connectedness, indegree variability and outdegree variability) between match simulation practice and competitive Australian Football League (AFL) games for one professional team. MANOVAs identified activity-related differences for task constraints, skill metrics and cooperative passing networks. During match simulation, goals were scored more frequently, but with less passing actions per minute. Receiving and distributing passing networks were more centralised (reliance on fewer key individuals), with less turnovers and tackles per minute compared to AFL matches. If match simulation is designed to reflect competition, then player and team skill preparation may be compromised. Furthermore, the competing demands in high-performance sport may restrict the degree of representativeness that can be achieved during practice. These findings provide valuable insight and may assist practitioners and/or coaches to understand the value of match simulation practice and to maximise near skill transfer from match simulation to competition.

Implementation of path analysis and piecewise structural equation modelling to improve the interpretation of key performance indicators in team sports: An example in professional rugby union.

Analysis of key performance indicators (KPIs) in team sports has frequently involved multiple univariate analyses and modelling of direct associations between each KPI and match outcomes. This study aimed to show a more appropriate framework and modelling process to establish causal plausibility for future confirmatory studies. A cross-sectional design was adopted, using 337 team-match observations of Australian Super Rugby performances. A tentative model was developed in consultation with a domain expert (national analyst) and analysed using piecewise structural equation modelling. Model fit was assessed using Fisher's C and the Akaike Information Criterion (AIC). Hypothesised relationships were modelled using linear mixed effects models and unmodelled pathways were investigated using tests of directed separation. The model was an acceptable fit overall, and adjustments were identified in collaboration with the national head analyst, improving the AIC from 127.15 to 120.77 (Fisher's C = 66.78; p = 0.382). Modelling the hierarchical data structure and developing models that contain more logical hypothesised associations (in consultation with domain experts) is a more useful and important step to analyse and interpret effects of KPIs on team performance. This analysis provides support to the plausibility of the causal structure and generation of new and more precise hypotheses.

An assessment of physical and spatiotemporal behaviour during different phases of match play in professional Australian football.

Despite advancements in the scale of data available for quantifying the physical and spatiotemporal characteristics of match play, there is an absence of research combining these aspects in professional sport. This study sought to differentiate between phases of play in professional Australian football using novel physical and spatiotemporal metrics. Data was obtained from Australian Football League games to provide new insight into the specific characteristics of each phase of play. A retrospective cross-sectional design was utilised with team's physical and spatiotemporal variables, measured via global navigation satellite system devices. A multinomial logistic regression was conducted to determine which physical and spatiotemporal measures were associated with each phase of play (contested play, defence, offence, set shot, goal reset, umpire stoppage). The addition of the predictors to a model that contained only the intercept significantly improved the fit between the model and data, with the logistic model correctly predicting the phase of play for 63.7% of the cases. This was the first study to concurrently examine differences in physical and spatiotemporal characteristics with respect to phase of play in an Australian football context. Differences in duration, physical and spatiotemporal properties were observed, providing new insight for coaches and subsequently providing direction for conditioning and practice design.

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.

Cycling Power Profile Characteristics of National-Level Junior Triathletes.

Stevens, CJ, Bennett, KJM, Novak, AR, Kittel, AB, and Dascombe, BJ. Cycling power profile characteristics of national-level junior triathletes. J Strength Cond Res 33(1): 197-202, 2019-With the draft-legal rule recently introduced to junior triathlon competition, it has become difficult to assess cycling performance through race results. Therefore, this study assessed the cycling power profile characteristics of national-level junior triathletes to assist with physical assessment and program design. Thirteen male (17.0 ± 1.0 years) and 11 female (17.2 ± 1.3 years) national-level junior triathletes completed a cycling power profile that consisted of maximal intervals that lasted 6, 15, 30, 60, 240, and 600 seconds in duration. Each power profile was completed on a LeMond ergometer using the subject's own bicycle, with power output and cadence recorded for all intervals. Mean power output values for males (783 ± 134, 768 ± 118, 609 ± 101, 470 ± 65, 323 ± 38, and 287 ± 34 W) were significantly (p ≤ 0.05) higher than those for females (554 ± 92, 510 ± 89, 437 ± 75, 349 ± 56, 248 ± 39, and 214 ± 37 W) across all intervals, respectively. Peak power output values for males across the 6- and 15-second intervals (1,011 ± 178 and 962 ± 170 W) were also significantly higher than those for females (674 ± 116 and 624 ± 114 W), respectively (p ≤ 0.05). Developing junior triathletes should aim to increase their capacity across the power profile above the mean values listed. Athletes should further aim to have power outputs equal to that of the best performers and beyond to ensure that they can meet the demands of any competition situation.

Power Profiles of Competitive and Noncompetitive Mountain Bikers.

Novak, AR, Bennett, KJM, Pluss, MA, Fransen, J, Watsford, ML, and Dascombe, BJ. Power profiles of competitive and noncompetitive mountain bikers. J Strength Cond Res 33(2): 538-543, 2019-The performance of Olympic distance cross-country mountain bikers (XCO-MTB) is affected by constraints such as erosion of track surfaces and mass start congestion which can affect race results. Standardized laboratory assessments quantify interseasonal and intraseasonal cycling potential through the assessment of multiple physiological capacities. Therefore, this study examined whether the power profile assessment (PPA) could discriminate between competitive XCO-MTB and noncompetitive mountain bikers (NC-MTB). Second, it aimed to report normative power profile data for competitive XCO-MTB cyclists. Twenty-nine male participants were recruited across groups of XCO-MTB (n = 14) and NC-MTB (n = 15) mountain bikers. Each cyclist completed a PPA that consisted of increasing duration maximal efforts (6, 15, 30, 60, 240, and 600 seconds) that were interspersed by longer rest periods (174, 225, 330, 480, and 600 seconds) between efforts. Normative power outputs were established for XCO-MTB cyclists ranging between 13.8 ± 1.5 W·kg (5-second effort) and 4.1 ± 0.6 W·kg (600-second effort). No differences in absolute peak power or cadence were identified between groups across any effort length (p > 0.05). However, the XCO-MTB cyclists produced greater mean power outputs relative to body mass than the NC-MTB during the 60-second (6.9 ± 0.8 vs 6.4 ± 0.6 W·kg; p = 0.002), 240-second (4.7 ± 0.7 vs. 3.8 ± 0.4 W·kg; p < 0.001), and 600-second (4.1 ± 0.6 vs. 3.4 ± 0.3 W·kg; p < 0.001) efforts. The PPA is a useful discriminative assessment tool for XCO-MTB and highlights the importance of aerobic power for XCO-MTB performance.

Predictors of performance in a 4-h mountain-bike race.

This study aimed to cross validate previously developed predictive models of mountain biking performance in a new cohort of mountain bikers during a 4-h event (XC4H). Eight amateur XC4H cyclists completed a multidimensional assessment battery including a power profile assessment that consisted of maximal efforts between 6 and 600 s, maximal hand grip strength assessments, a video-based decision-making test as well as a XC4H race. A multiple linear regression model was found to predict XC4H performance with good accuracy (R2 = 0.99; P < 0.01). This model consisted of [Formula: see text] relative to total cycling mass (body mass including competition clothing and bicycle mass), maximum power output sustained over 60 s relative to total cycling mass, peak left hand grip strength and two-line decision-making score. Previous models for Olympic distance MTB performance demonstrated merit (R2 = 0.93; P > 0.05) although subtle changes improved the fit, significance and normal distribution of residuals within the model (R2 = 0.99; P < 0.01), highlighting differences between the disciplines. The high level of predictive accuracy of the new XC4H model further supports the use of a multidimensional approach in predicting MTB performance. The difference between the new, XC4H and previous Olympic MTB predictive models demonstrates subtle differences in physiological requirements and performance predictors between the two MTB disciplines.

A multidimensional approach to performance prediction in Olympic distance cross-country mountain bikers.

This study adopted a multidimensional approach to performance prediction within Olympic distance cross-country mountain biking (XCO-MTB). Twelve competitive XCO-MTB cyclists (VO2max 60.8 ± 6.7 ml · kg-1 · min-1) completed an incremental cycling test, maximal hand grip strength test, cycling power profile (maximal efforts lasting 6-600 s), decision-making test and an individual XCO-MTB time-trial (34.25 km). A hierarchical approach using multiple linear regression analyses was used to develop predictive models of performance across 10 circuit subsections and the total time-trial. The strongest model to predict overall time-trial performance achieved prediction accuracy of 127.1 s across 6246.8 ± 452.0 s (adjusted R2 = 0.92; P < 0.01). This model included VO2max relative to total cycling mass, maximal mean power across 5 and 30 s, peak left hand grip strength, and response time for correct decisions in the decision-making task. A range of factors contributed to the models for each individual subsection of the circuit with varying predictive strength (adjusted R2: 0.62-0.97; P < 0.05). The high prediction accuracy for the total time-trial supports that a multidimensional approach should be taken to develop XCO-MTB performance. Additionally, individual models for circuit subsections may help guide training practices relative to the specific trail characteristics of various XCO-MTB circuits.

A holistic analysis of collective behaviour and team performance in Australian Football via structural equation modelling.

Despite awareness of the importance of quantifying technical, tactical, and physical characteristics of match play, few studies have examined the structural relationship of these aspects in professional sport. Accordingly, this study concurrently examined these components in relation to quarter outcome (n = 272) in Australian Football. The study followed a retrospective longitudinal case study design where one teams' cooperative passing network, skill counts, physical loads, and spatiotemporal behaviours during official Australian Football League games were collected from a period spanning four seasons (2016-2019). A principal components analysis (PCA) and structural equation modelling were used to explore the structural relationships between components and examine the influence on quarter outcome as determined by the point differential (quarter margin). Scoring opportunity and ball movement had direct associations with quarter margin, while unpredictability, uncontested behaviour and physical behaviour did not. Negative associations between uncontested behaviour and scoring opportunity suggest that elevated high-pressure success and a lack of synchrony may positively influence scoring opportunity, a determinant of quarter margin. Further, negative associations between physical behaviour and ball movement suggest that with less physical work, a team's collective ability to transfer possession between teammates is facilitated, offering an interesting dichotomy between skill and physical demands of Australian Football. While hundreds of different metrics are available, the present study was the first to concurrently examine the influence of a variety of match play components on performance outcomes in Australian Football. These results may provide direction for coaches and practitioners when contemplating practice design, tactical strategies, or the development of behaviour through specific training exercises. Game plans and training drills that focus on optimising attacking and low-pressure ball movement coupled with high levels of mutual interaction between teammates may be beneficial for performance.

Development and Validation of Single Items for Fatigue and Recovery in Dancers.

PURPOSE: To examine the construct validity and reliability of 2 single items for fatigue and recovery in dancers. The construct validity was assessed using reference instruments: the fatigue items of the Brunel Mood Scale (BRUMS) and the Short Recovery and Stress Scale (SRSS). A secondary aim was to explore the respondent interpretation of these 2 items using a concept identification approach. METHODS: Two hundred forty-three (N = 243) dancers completed single-item fatigue and recovery (unipolar and bipolar), BRUMS, and SRSS once for construct validity. For reliability, 49 dancers completed the questionnaires twice, 1 week apart. Using a concept identification approach, 49 dancers were also asked comprehension and interpretation of fatigue and recovery. RESULTS: The fatigue item correlated with SRSS stress items (rs = .37-.51) and BRUMs fatigue items (rs = .63-.66). The recovery item was only partially confirmed in terms of construct validity, when using the SRSS recovery items as reference (rs = .39-.43). Reliability was confirmed for the single items of fatigue (κ = .77-.78) and recovery (κ = .71-.78). Main responses for the concept of fatigue were tiredness (34.7%), muscle soreness (17.3%), and energy (13.0%). Main responses for the concept of recovery were muscle soreness (43.0%), tiredness (27.9%), and fatigue (24.0%). CONCLUSION: We provide preliminary confirmation of the validity and reliability of the single item fatigue in dancers. The recovery item was only partially confirmed in terms of construct validity, when using the SRSS recovery items as reference, but did display acceptable reliability and agreement. Further research is warranted further exploring other measurement properties.

Factors associated with cooperative network connectedness in a professional Australian football small-sided game.

OBJECTIVES: Connectedness is a cooperative network measure that describes how well players in the team bi-directionally connect and how easily reachable they are to other players. It has been associated with an increased probability of winning competitive matches in professional Australian Football (AF), although applications towards training have not been reported. Therefore, this study investigated associations between constraints manipulated by professional AF coaches and the connectedness of cooperative passing networks during a small-sided game (SSG). DESIGN: Data were collected describing the task constraints manipulated by professional coaches across one SSG performed on multiple occasions. The SSG focused on transitioning between defence and attack and was performed fifteen times across a whole season, resulting in 36 observations of team connectedness. METHOD: A linear mixed-effects model was constructed to examine the collective influence of constraints manipulations made by professional coaches (e.g. field size) and team skill characteristics (e.g. kick efficiency) on connectedness scores. RESULTS: The number of team shots on goal and the time on task both positively contributed to connectedness scores, explaining 65% of its variance. CONCLUSION: The findings show that the number of shots on goal and the time on task may be used to elicit higher or lower connectedness scores in AF SSGs. Skill acquisition specialists, in conjunction with coaching staff, can use these metrics to aid practice design in professional AF or indeed other invasion-style team sports.

Tactical analysis of individual and team behaviour in professional Australian Football.

INTRODUCTION: This study sought to reduce the dimensionality of commonly reported spatiotemporal characteristics obtained from Australian Football games to facilitate their practical use and interpretability. METHODS: A retrospective longitudinal design was utilised with team and individual spatiotemporal variables, measured via global navigation satellite system devices, collected during official Australian Football League matched over three seasons. Two separate principal component analyses were conducted at the team and individual level to reduce correlated spatiotemporal characteristics into a smaller set of uncorrelated components. RESULTS: At the team level, eighteen variables were reduced to five components pertaining to dispersive coordination, lateral predictability and spacing, multidirectional synchrony, longitudinal predictability and longitudinal behaviour whilst maintaining 69% of variance in the original dataset. At the individual level, fifteen variables were reduced to four components pertaining to multidirectional and spacing synchrony, unpredictability, player movement and player positioning whilst maintaining 64% of variance. CONCLUSION: This study is the first to provide a simplified, novel method for analysing spatiotemporal behaviour in an Australian Football context with both the team- and individual- derived metrics revealing useful information for coaches and practitioners. Components may provide insight into behaviours that emerge and persist throughout a game and allow coaches to distinguish between different playing/behavioural styles.

Using cooperative networks to analyse behaviour in professional Australian Football.

OBJECTIVES: Reducing the dimensionality of commonly reported complex network characteristics obtained from Australian Football League (AFL) games to facilitate their practical use and interpretability. DESIGN: Retrospective longitudinal design where individual players' interactions, determined through the distribution and receipt of kicks and handballs, during official AFL games were collected over three seasons. METHODS: A principal component analysis was used to reduce the number of characteristics related to the cooperative network analysis. RESULTS: The principal component analysis derived two individual-based principal components pertaining to in- and out-degree importance and three team-based principal components related to connectedness and in- and out-degree centralisation. CONCLUSIONS: This study is the first to provide a simplified, novel method for analysing complex network structures in an Australian Football context with both the team- and individual-derived metrics revealing useful information for coaches and practitioners. This may consequently guide opposition analysis, training implementation, player performance ratings and player selection.

Improving the interpretation of skill indicators in professional Australian Football.

OBJECTIVES: This study aimed to provide a simplified, novel method for analysing technical skill involvements in an Australian Football context by reducing the dimensionality of commonly reported skill counts obtained from Australian Football League (AFL) games. This may facilitate their practical use and interpretability. DESIGN: Retrospective longitudinal design where individual players' technical skill counts were collected over three seasons of official AFL games. METHODS: Seventy-three skill count values provided publicly by ChampionData® were collected for each match over a three-year analysis period. A principal component analysis was used to reduce the dimensionality of a large number of correlated technical skill indicators into a smaller set of uncorrelated components whilst maintaining most of the variance from the original data set. RESULTS: The principal component analysis derived four principal components pertaining to high-pressure success, low-pressure success, attacking ball movement ability and scoring ability. CONCLUSIONS: This study is the first to provide a simplified, novel method for analysing technical skill counts in Australian Football. The derived metrics reveal useful information for coaches and practitioners. This may consequently ease the interpretation of skill count data available to coaches from games, guide opposition analysis, help in the design of representative practice and inform player performance ratings.

Assessing the validity of a video-based decision-making assessment for talent identification in youth soccer.

OBJECTIVES: To investigate the construct and discriminant validity of a video-based decision-making assessment for talent identification in youth soccer. DESIGN: Observational study. METHOD: A total of 328 academy youth soccer players (tier one, tier two, and tier three) from three developmental stages (late childhood, early adolescence, and mid-adolescence) participated in this study. The control group consisted of 59 youth athletes with no soccer experience in the last five years. Players completed a video-based decision-making assessment on an iPad, with response accuracy and response time recorded for various attacking situations (2 vs. 1, 3 vs. 1, 3 vs. 2, 4 vs. 3, and 5 vs. 3). RESULTS: The video-based decision-making assessment showed some construct validity. Response times were significantly faster in early and mid-adolescent players when compared to those in the late childhood group. Furthermore, an overall decline in decision-making performance (i.e. decrease in response accuracy and increase in response time) was observed from the 2 vs. 1 to the 4 vs. 3 situations. The video-based decision-making assessment lacked discriminant validity as minimal differences between academies were evident for response accuracy and response time. Only response accuracy was able to discriminate youth academy soccer players from the control group to some extent. CONCLUSIONS: Coaches and sporting professionals should apply caution when interpreting data from practical, video-based decision-making assessments. There is currently limited conclusive evidence supporting the effectiveness of these assessments for talent identification.

Esports: The Chess of the 21st Century.

For many decades, researchers have explored the true potential of human achievement. The expertise field has come a long way since the early works of de Groot (1965) and Chase and Simon (1973). Since then, this inquiry has expanded into the areas of music, science, technology, sport, academia, and art. Despite the vast amount of research to date, the capability of study methodologies to truly capture the nature of expertise remains questionable. Some considerations include (i) the individual bias in the retrospective recall of developmental activities, (ii) the ability to develop ecologically valid tasks, and (iii) difficulties capturing the influence of confounding factors on expertise. This article proposes that expertise research in electronic sports (esports) presents an opportunity to overcome some of these considerations. Esports involves individuals or teams of players that compete in video game competitions via human-computer interaction. Advantages of applying the expert performance approach in esports include (i) developmental activities are objectively tracked and automatically logged online, (ii) the constraints of representative tasks correspond with the real-world environment of esports performance, and (iii) expertise has emerged without the influence of guided systematic training environments. Therefore, this article argues that esports research provides an ideal opportunity to further advance research on the development and assessment of human expertise.