Assessment of Physical, Technical, and Tactical Analysis in the Australian Football League: A Systematic Review.

BACKGROUND: Elite Australian Football (AF) match-play requires proficiency in physical, technical, and tactical elements. However, when analysing player movement practitioners commonly exclude technical and tactical considerations, failing to recognise the multifactorial nature of AF match-play and providing little context into the movement requirements of the players. OBJECTIVES: This systematic review aimed to identify the physical, technical, and tactical requirements of the Australian Football League (AFL) and to highlight the importance of integrating data from multiple sources when analysing player output. METHODS: A systematic search of electronic databases (CINAHL, PubMed, Scopus, SPORTDiscus, and Web of Science) was conducted from January 2009 to June 2022. Keywords relating to physical, technical, and tactical match requirements were used. RESULTS: Forty-eight studies met the inclusion criteria. In isolation, physical requirements were the most analysed construct within the AFL (n = 17), followed by technical (n = 9) and then tactical (n = 6). Thirteen studies integrated physical and technical elements, one study integrated technical and tactical elements, one study integrated physical and tactical elements, and one study integrated all three elements. Movement analysis centred around average 'whole' match requirements, whereas technical and tactical match analyses focused on key performance indicators of match performance. CONCLUSION: While the physical requirements of the AFL have been well documented, there is little understanding of how player technical output and various team tactics influence player movement requirements. Knowledge of how the elements of AF match-play interact with one another could enhance our understanding of match performance and provide a greater resource for training prescription.

Technical involvements and pressure applied influence movement demands in elite Australian Football Match-play.

Match activity analyses in Australian Football (AF) have provided information on the loads of match-play and identified contextual factors influencing physical activity. Match physical activity has been shown to be influenced by technical and tactical factors. This study examined the association of in-game contextual factors and technical involvements on the activity demands of elite AF players. Global positioning system data were recorded from 35 players in 13 matches throughout the 2019 Australian Football League (AFL) season. Technical involvements - player possession, and defensive pressure applied - were attained from Champion Data (AFL statistics provider), while possession phases and the commencing possession chain event were manually coded. Mixed models examined the influence possession chain contextual factors had on the total distance (TD) and high-speed running (HSR). During attacking phases, physical activity increased when a player had a possession, when a greater number of opposition players applied pressure, and when play was initiated from a turnover (p ≤ 0.001). During defensive phases, physical activity was greatest when an individual player applied pressure, however, also increased when the total number of players applying pressure increased and when play was initiated from a turnover or kick-in (p ≤ 0.001). Overall, this study combines the three constructs of AF performance (physical, technical and tactical) and demonstrates that TD and HSR demands are greatest in a chain when a player was directly involved in the play or applying pressure on the opposition.

A Qualitative Investigation of Factors Influencing the Dietary Intakes of Professional Australian Football Players.

(1) Background: Many professional Australian Football (AF) players do not meet recommended sports nutrition guidelines despite having access to nutrition advice. There are a range of factors that can influence players' ability to meet their nutrition goals and awareness of the barriers players face is essential to ensure that dietary advice translates into practice. Therefore, this qualitative research study aimed to explore the factors influencing AF players' dietary intakes and food choice. (2) Methods: Semi-structured interviews were conducted with twelve professional male AF players. (3) Results: Less experienced players restricted their carbohydrate intake to meet body composition goals, particularly during preseason and surrounding body composition assessment. During the competition season players had a greater focus on performance and placed more emphasis on carbohydrate intake in the lead up to matches. Players felt nutrition goals were easier to achieve when dietary choices were supported by their families and peers. One-on-one consultations provided by a sports dietitian were players' preferred mode of nutrition intervention. Individualized nutrition advice is required for less experienced AF players who may be vulnerable to unsustainable dietary habits. Experienced AF players can support junior teammates by promoting positive team culture related to body composition, nutrition and performance.

Possession chain factors influence movement demands in elite Australian football match-play.

Contemporary analysis of physical activity in Australian Football (AF) is typically presented as a total measure and independent of game context, which is not representative of how the game is played and/or assessed by coaches. This study examines the activity profile of individual possession chains and determines the influence that field position, initial chain state, and possession phase have on these activity characteristics in men's AF.Global positioning system data were attained from 35 players in 13 matches across the 2019 Australian Football League season. Matches were coded into different possession phases, initial field location of the ball, and initial chain state. Mixed models were built to observe the influence of field position and initial chain state for each possession phase.Less TD and HSR distance were covered during attacking chains in the forward 50 and attacking midfield, while defensive chains covered less TD and HSR in the defensive 50 and defensive midfield (p < 0.001). Significant main effects for possession phase and initial chain state were observed for TD and HSR. TD and HSR were higher during attacking chains, while chains beginning from a stoppage were lower than intercept and kick-ins (p < 0.001).Overall, the most intense moments of the game appear similar across all possession phases when field location is accounted for and that transitioning the ball quickly from the defensive end of the field results in greater physical activity. These findings can be used for prescription and monitoring of training drills specific to AF requirements.

Associations between refined athlete monitoring measures and individual match performance in professional Australian football.

The purpose of this study was to assess relationships between measures of training load, training response and neuromuscular performance and changes in individual match performance in professional Australian football. Data were collected from 45 professional Australian footballers from one club during the 2019 competition season. External load was measured by GPS technology. Internal load was measured via session rate of perceived exertion (sRPE). Perceptual wellness was measured via pre-training questionnaires (1-5 Likert scale rating of soreness, sleep, fatigue, stress and motivation). Percentage of maximum speed was calculated relative to individual maximum recorded during preseason testing. Rolling derivative training load measures (7-day and 28-day) were calculated. Principal Component Analysis (PCA) identified eight uncorrelated components. PCA factor loadings were used to calculate summed variable covariates and single variables were chosen from components based on practicality and statistical contribution. Associations between covariates and performance were determined via linear Generalised Estimating Equations. Performance was assessed via Player Ratings from a commercial statistics company. Seven-day total distance, IMA event count and sRPE load showed significant positive relationships with performance (18-23% increase in performance z-score). No other covariates displayed significant associations with performance. Individual relative increases in training load within the 7-day period prior to a match may be beneficial for enhancing individual performance.

Data Reduction Approaches to Athlete Monitoring in Professional Australian Football.

PURPOSE: To apply data reduction methods to athlete-monitoring measures to address the issue of data overload for practitioners of professional Australian football teams. METHODS: Data were collected from 45 professional Australian footballers from 1 club during the 2018 Australian Football League season. External load was measured in training and matches by 10-Hz OptimEye S5 and ClearSky T6 GPS units. Internal load was measured via the session rate of perceived exertion method. Perceptual wellness was measured via questionnaires completed before training sessions with players providing a rating (1-5 Likert scale) of muscle soreness, sleep quality, fatigue, stress, and motivation. Percentage of maximum speed was calculated relative to individual maximum velocity recorded during preseason testing. Derivative external training load measures (total daily, weekly, and monthly) were calculated. Principal-component analyses (PCAs) were conducted for Daily and Chronic measures, and components were identified via scree plot inspection (eigenvalue > 1). Components underwent orthogonal rotation with a factor loading redundancy threshold of 0.70. RESULTS: The Daily PCA identified components representing external load, perceived wellness, and internal load. The Chronic PCA identified components representing 28-d speed exposure, 28-d external load, 7-d external load, and 28-d internal load. Perceived soreness did not meet the redundancy threshold. CONCLUSIONS: Monitoring player exposure to maximum speed is more appropriate over chronic than short time frames to capture variations in between-matches training-cycle duration. Perceived soreness represents a distinct element of a player's perception of wellness. Summed-variable and single-variable approaches are novel methods of data reduction following PCA of athlete monitoring data.

Career Performance Trajectories of Professional Australian Football Players.

PURPOSE: To develop position-specific career performance trajectories and determine the age of peak performance of professional Australian Football players. METHODS: Match performance data (Australian Football League [AFL] Player Rank) were collected for Australian Football players drafted via the AFL National Draft between 1999 and 2015 (N = 207). Players were subdivided into playing positions: forwards (n = 60; age 23 [3] y), defenders (n = 71; age 24 [4] y), midfielders (n = 58; age 24 [4] y), and ruckmen (n = 18; age 24 [3] y). Linear mixed models were fitted to the data to estimate individual career trajectories. RESULTS: Forwards, midfielders, and defenders experienced peak match performance earlier than ruckmen (24-25 vs 27 y). Midfielders demonstrated the greatest between-subjects variability (intercept 0.580, age 0.0286) in comparison with ruckmen, who demonstrated the least variability (intercept 0.112, age 0.005) in AFL Player Rank throughout their careers. Age had the greatest influence on the career trajectory of midfielders (ß [SE] = 0.226 [0.025], T = 9.10, P < .01) and the least effect on ruckmen (ß [SE] = 0.114 [0.049], T = 2.30, P = .02). CONCLUSIONS: Professional Australian Football players peak in match performance between 24 and 27 years of age with age, having the greatest influence on the match performance of midfielders and the least on ruckmen.

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.

Measurement Characteristics of Athlete Monitoring Tools in Professional Australian Football.

PURPOSE: To examine the measurement reliability and sensitivity of common athlete monitoring tools in professional Australian Football players. METHODS: Test-retest reliability (noise) and weekly variation (signal) data were collected from 42 professional Australian footballers from 1 club during a competition season. Perceptual wellness was measured via questionnaires completed before main training sessions (48, 72, and 96 h postmatch), with players providing a rating (1-5 Likert scale) regarding their muscle soreness, sleep quality, fatigue level, stress, and motivation. Eccentric hamstring force and countermovement jumps were assessed via proprietary systems once per week. Heart rate recovery was assessed via a standard submaximal run test on a grass-covered field with players wearing a heart rate monitor. The heart rate recovery was calculated by subtracting average heart rate during final 10 seconds of rest from average heart rate during final 30 seconds of exercise. Typical test error was reported as coefficient of variation percentage (CV%) and intraclass coefficients. Sensitivity was calculated by dividing weekly CV% by test CV% to produce a signal to noise ratio. RESULTS: All measures displayed acceptable sensitivity. Signal to noise ratio ranged from 1.3 to 11.1. Intraclass coefficients ranged from .30 to .97 for all measures. CONCLUSIONS: The heart rate recovery test, countermovement jump test, eccentric hamstring force test, and perceptual wellness all possess acceptable measurement sensitivity. Signal to noise ratio analysis is a novel method of assessing measurement characteristics of monitoring tools. These data can be used by coaches and scientists to identify meaningful changes in common measures of fitness and fatigue in professional Australian football.

Business Intelligence: How Sport Scientists Can Support Organization Decision Making in Professional Sport.

The application of scientific principles to inform practice has become increasingly common in professional sports, with increasing numbers of sport scientists operating in this area. The authors believe that in addition to domain-specific expertise, effective sport scientists working in professional sport should be able to develop systematic analysis frameworks to enhance performance in their organization. Although statistical analysis is critical to this process, it depends on proper data collection, integration, and storage. The purpose of this commentary is to discuss the opportunity for sport-science professionals to contribute beyond their domain-specific expertise and apply these principles in a business-intelligence function to support decision makers across the organization. The decision-support model aims to improve both the efficiency and the effectiveness of decisions and comprises 3 areas: data collection and organization, analytic models to drive insight, and interface and communication of information. In addition to developing frameworks for managing data systems, the authors suggest that sport scientists' grounding in scientific thinking and statistics positions them to assist in the development of robust decision-making processes across the organization. Furthermore, sport scientists can audit the outcomes of decisions made by the organization. By tracking outcomes, a feedback loop can be established to identify the types of decisions that are being made well and the situations where poor decisions persist. The authors have proposed that sport scientists can contribute to the broader success of professional sporting organizations by promoting decision-support services that incorporate data collection, analysis, and communication.

Measurement Properties of an Adductor Strength-Assessment System in Professional Australian Footballers.

PURPOSE: To examine the measurement properties of an adductor strength-assessment system in professional Australian footballers. METHODS: Observational, longitudinal design. Test-retest reliability data were collected from 18 professional Australian footballers from 1 club on the same day during the 2017 Australian Football League season. Week-to-week variation data were collected on 45 professional Australian footballers from 1 club during the same season at 48, 72, and 120 h postmatch (rounds 1-23). Players lay beneath a GroinBar hip-strength testing system in supine position with their knee joints at an angle of 60°. Force (in newtons) was extracted for the left and right limbs of each player and a pain score from 0 to 10 (0 = no pain, 10 = maximum pain) was provided. Coefficient of variation (CV) and smallest worthwhile change were calculated on test-retest data. Signal-to-noise ratio was calculated for each major time point. Mean difference between force scores in a subgroup of players with and without groin pain (n = 18) was collected as evidence of construct validity for the system. RESULTS: Test CV was 6.3% (4.9-9.0%). CV exceeded the smallest worthwhile change on both limbs. Intraclass correlation coefficient was .94. Signal-to-noise ratio ranged from 1.6 to 2.6 on average for 48, 72, and 120 h postmatch. Groin pain had a very likely moderate negative effect on adductor strength (effect size: 0.41). CONCLUSIONS: The system possesses greater measurement precision than dynamometry and sphygmomanometer adductor strength-assessment methods in professional Australian footballers. Increased groin pain reduced groin squeeze force production. Practitioners may interpret changes exceeding 6.3% in adductor strength as real.

Dietary intake of professional Australian football athletes surrounding body composition assessment.

BACKGROUND: Sports Dietitians aim to assist in improving performance by developing nutrition knowledge (NK), enhancing dietary intake and optimising body composition of athletes. In a high-pressure environment, it is important to identify factors that may compromise an athlete's nutrition status. Body composition assessments are regularly undertaken in sport to provide feedback on training adaptions; however, no research has explored the impact of these assessments on the dietary intake of professional athletes. METHODS: This cross-sectional study assessed dietary intake (7-day food diary), nutrition knowledge (Nutrition for Sport Knowledge Questionnaire) and body composition (Dual-energy X-ray absorptiometry) of 46 professional male Australian football (AFL) athletes during a 2017 pre-season training week (7 days) where body composition assessments were undertaken. Dietary intake was assessed against International Olympic Committee recommendations for professional athletes. RESULTS: Overall, no athlete met dietary their recommended energy intake (15 ± 1.1 vs. 9.1 ± 1.8 MJ, respectively) or carbohydrate recommendations (6-10 vs. 2.4 ± 0.9 g·kg-1·day-1). Only 54% met protein recommendations. Secondary analyses demonstrated significant associations between education status and energy intake (P < 0.04) and vegetable intake (P < 0.03), with higher levels of education being associated with higher intakes. A moderately positive association was observed between NK scores and meeting estimated energy requirements (r = 0.33, P = 0.03). NK scores were also positively associated with protein (r = 0.35, P = 0.02), fibre (r = 0.51, P = 0.001) and calcium intakes (r = 0.43, P = 0.004). CONCLUSIONS: This research identified that the dietary intake of professional AFL athletes during a pre-season training week where body composition assessments were undertaken did not meet current recommendations. Several factors may influence the dietary intake of AFL athletes, including lower education levels, poor NK and dietary intake restriction surrounding body composition assessment. Athletes may require support to continue with performance-based nutrition plans in periods surrounding body composition assessment.

Physical Preparation Factors That Influence Technical and Physical Match Performance in Professional Australian Football.

OBJECTIVES: To examine the collective influence of a range of physical preparation elements on selected performance measures during Australian football match play. DESIGN: Prospective and longitudinal. METHODS: Data were collected from 34 professional Australian football players from the same club during the 2016 Australian Football League competition season. Match activity profiles and acute (7-d) and chronic (3-wk) training loads were collected using global positioning system devices. Training response was measured by well-being questionnaires completed prior to the main training session each week. Maximal aerobic running speed (MAS) was estimated by a 2-km time trial conducted during preseason. Coach ratings were collected from the senior coach and 4 assistants after each match on a 5-point Likert scale. Player ratings were obtained from a commercial statistics provider. Fifteen matches were analyzed. Linear mixed models were constructed to examine the collective influence of training-related factors on 4 performance measures. RESULTS: Muscle soreness had a small positive effect (ES: 0.12) on Champion Data rating points. Three-week average high-speed running distance had a small negative effect (ES: 0.14) on coach ratings. MAS had large to moderate positive effects (ES: 0.55 to 0.47) on relative total and high-speed running distances. Acute total and chronic average total running distance had small positive (ES: 0.13) and negative (ES: 0.14) effects on relative total and high-speed running distance performed during matches, respectively. CONCLUSIONS: MAS should be developed to enhance players' running performance during competition. Monitoring of physical preparation data may assist in reducing injury and illness and increasing player availability but not enhance football performance.

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.

Physical demands and technical performance in Australian Football League Women's (AFLW) competition match-play.

OBJECTIVES: To compare positional differences in the physical and technical demands of Australian Football League Women's (AFLW) match-play. A secondary aim was to examine the time course changes in activity profiles during AFLW match-play. DESIGN: Longitudinal observational study. METHODS: Global positioning system data were collected from 26 players (6 positional groups) from the same club during seven AFLW matches. Absolute and relative physical performance data were categorised into total distance, high-speed running (>14.4kmh-1, HSR), very high-speed running (>18.0kmh-1, VHSR), and sprinting distance (>20.0kmh-1, Sprint). Technical performance data was obtained from a commercial statistics provider. A mixed model analysis was used to examine differences between positional groups and playing quarters. RESULTS: Absolute measures of running performance did not differ between position groups. Relative total distance was moderately greater (ES=∼0.80, p<0.05) for midfielders, small backs and small forwards (125-128mmin-1) than tall backs and tall forwards (102-107mmin-1). Relative HSR distance was greater (ES=∼0.73) for midfielders and small backs (∼28mmin-1) than tall backs (17mmin-1). Analysis of technical performance indicators showed: midfielders and small forwards had the most inside 50s; tall backs had the highest number of rebound 50s; tall forwards scored more goals; while midfielders made more tackles (p<0.05). All relative running performance measures were reduced in the fourth quarter when compared to the first and second quarters (ES=0.32-0.77). CONCLUSIONS: These data can be used as benchmarks for temporal analysis of AFLW match demands and assist in developing specific training strategies.

Interchange rotation factors and player characteristics influence physical and technical performance in professional Australian Rules football.

OBJECTIVES: To examine the effects of match-related and individual player characteristics on activity profile and technical performance during rotations in professional Australian football. DESIGN: Longitudinal observational study. METHODS: Global positioning system data and player rating scores were collected from 33 professional Australian football players during 15 Australian football League matches. Player rating scores were time aligned with their relative total and high-speed running (HSR) distance (>20kmh-1) for each on ground rotation. Individual players' maximal aerobic running speed (MAS) was determined from a two-kilometre trial. A multilevel linear mixed model was used to examine the influence of rotations on physical activity profiles and skill execution during match play. RESULTS: Rotation duration and accumulated distance resulted in a trivial-to-moderate reduction in relative total and HSR distances as well as relative rating points. The number of disposals in a rotation had a small positive effect on relative total and HSR distances and a large positive effect on relative rating points. MAS was associated with a moderate-to-large increase in relative total distance, but had a large negative effect on relative rating points. Previous rotation time, stoppages and the number of rotations in the quarter had a trivial-to-small negative effect on relative total and HSR distances. A greater speed (mmin-1) was associated with a trivial increase in rating points during a rotation, while there was a trivial decrease in relative total distance as rating points increased. CONCLUSION: The complex relationship between factors that influence activity profile and technical performance during rotations in Australian football needs to be considered when interpreting match performance.

Factors Affecting Match Running Performance in Professional Australian Football.

PURPOSE: To examine the influence of a range of individual player characteristics and match-related factors on activity profiles during professional Australian football matches. METHODS: Global positioning system (GPS) profiles were collected from 34 professional Australian football players from the same club over 15 competition matches. GPS data were classified into relative total and high-speed running (HSR; >20 km/h) distances. Individual player aerobic fitness was determined from a 2-km time trial conducted during the preseason. Each match was classified according to match location, season phase, recovery length, opposition strength, and match outcome. The total number of stoppages during the match was obtained from a commercial statistics provider. A linear mixed model was constructed to examine the influence of player characteristics and match-related factors on both relative total and HSR outputs. RESULTS: Player aerobic fitness had a large effect on relative total and HSR distances. Away matches and matches lost produced only small reductions in relative HSR distances, while the number of rotations also had a small positive effect. Matches won, more player rotations, and playing against strong opposition all resulted in small to moderate increases in relative total distance, while early season phase, increased number of stoppages, and away matches resulted in small to moderate reductions in relative total distance. CONCLUSIONS: There is a likely interplay of factors that influence running performance during Australian football matches. The results highlight the need to consider a variety of contextual factors when interpreting physical output from matches.

Longitudinal Changes and Seasonal Variation in Body Composition in Professional Australian Football Players.

PURPOSE: To compare development and variations in body composition of early-, mid-, and late-career professional Australian Football (AF) players over 3 successive seasons. METHODS: Regional and total-body composition (body mass [BM], fat mass [FM], fat-free soft-tissue mass [FFSTM], and bone mineral content [BMC]) were assessed 4 times, at the same time of each season-start preseason (SP), end preseason (EP), midseason (MS), and end season (ES)-from 22 professional AF players using pencil-beam dual-energy X-ray absorptiometry. Nutritional intake for each player was evaluated concomitantly using 3-d food diaries. Players were classified according to their age at the beginning of the observational period as either early- (<21 y, n = 8), mid- (21 to 25 y, n = 9), or late- (>25 y, n = 5) career athletes. RESULTS: Early-career players had lower FFSTM, BMC, and BM than mid- and late-career throughout. FM and %FM had greatest variability, particularly in the early-career players. FM reduced and FFSTM increased from SP to EP, while FM and FFSTM decreased from EP to MS. FM increased and FFSTM decreased from MS to ES, while FM and FFSTM increased during the off-season. CONCLUSIONS: Early-career players may benefit from greater emphasis on specific nutrition and resistance-training strategies aimed at increasing FFSTM, while all players should balance training and diet toward the end of season to minimize increases in FM.

A Comparison of Physical and Technical Performance Profiles Between Successful and Less-Successful Professional Rugby League Teams.

PURPOSE: To examine differences in physical and technical performance profiles using a large sample of match observations drawn from successful and less-successful professional rugby league teams. METHODS: Match activity profiles were collected using global positioning satellite (GPS) technology from 29 players from a successful rugby league team during 24 games and 25 players from a less-successful team during 18 games throughout 2 separate competition seasons. Technical performance data were obtained from a commercial statistics provider. A progressive magnitude-based statistical approach was used to compare differences in physical and technical performance variables between the reference teams. RESULTS: There were no clear differences in playing time, absolute and relative total distances, or low-speed running distances between successful and less-successful teams. The successful team possibly to very likely had lower higher-speed running demands and likely had fewer physical collisions than the less-successful team, although they likely to most likely demonstrated more accelerations and decelerations and likely had higher average metabolic power. The successful team very likely gained more territory in attack, very likely had more possessions, and likely committed fewer errors. In contrast, the less-successful team was likely required to attempt more tackles, most likely missed more tackles, and very likely had a lower effective tackle percentage. CONCLUSIONS: In the current study, successful match performance was not contingent on higher match running outputs or more physical collisions; rather, proficiency in technical performance components better differentiated successful and less-successful teams.

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.