Preseason Body Composition Is Associated With In-season Player Availability in Elite Male Australian Footballers.

ABSTRACT: McCaskie, CJ, Sim, M, Newton, RU, Heasman, J, Rogalski, B, and Hart, NH. Preseason body composition is associated with in-season player availability in elite male Australian footballers. J Strength Cond Res 37(5): 1089-1095, 2023-The purpose of this study was to examine whether end of preseason body composition characteristics was associated with in-season match availability and injury. Sixty ( n = 60) elite Australian football players had body composition characteristics assessed using dual-energy X-ray absorptiometry across 3 seasons (2016, 2018, and 2021). Match availability and injury were recorded throughout each season. Pearson's correlations were calculated to assess the associations between body composition and in-season match availability and injury. Logistic regression models were used to assess the odds of missing games as a result of injury throughout a season. Regional lean soft tissue mass asymmetry and its relationship to injury and availability was explored. Statistical significance was set at p ≤ 0.05. Body composition characteristics expressed as relative values seemed to be more highly associated with in-season availability and injury than characteristics expressed as absolute values. Players with lower relative fat mass (FM) (<12.1% total body FM) were available for 89.7% of in-season matches compared with 80.7% for players with higher relative FM (>12.1% total body FM). Subsequently, players with higher relative FM had 3.3-3.5 times greater odds of missing one game to injury (odds ratio [OR] = 3.33; 95% confidence interval [CI] = 1.00-11.14; p ≤ 0.05) and missing 2 or more games to injury (OR = 3.50; 95% CI = 1.20-10.20; p ≤ 0.05) throughout a season compared with players with lower relative FM. Higher proportions of fat mass may accelerate the onset of fatigue and place players at a greater risk of injury. Reducing players' FM across the preseason phase should be a key aim for practitioners to reduce the odds of injury throughout the competitive season.

Post-game recovery of isometric hamstring strength in a high-risk hamstring strain injury group throughout an Australian Football League season.

This study sought to investigate post-game hamstring strength recovery of 26 Australian Football League (AFL) players with a previous hamstring strain injury (HSI) across an AFL season. Maximal unilateral isometric knee flexion strength was assessed using an externally fixed dynamometer, and inter-session reliability was measured during the pre-season period. Linear mixed effects models investigated the influence of numerous variables on post-game hamstring strength decrement (relative change between initial weekly test and individual baseline) and individual within-week strength change following gameplay. The test demonstrated good inter-tester reliability (ICC = 0.81-0.88; CV = 6.73-7.33), and an acceptable level of error (MAE = 5.77-7.14%). Player as a random effect strongly influenced post-game strength decrement and within-week strength change (marginal R2 = 0.185-0.407; conditional R2 = 0.455-0.654). Within-week hamstring strength change was strongly determined by post-game strength decrement alone (estimate = 0.51, 95% CI = -0.66- -0.36 ; η2 = 0.32; P=<0.001) and in interaction with number of days post-game (estimate = 0.43, 95% CI = 0.20-0.66; η2 = 0.096; P=<0.001). This study shows the importance of early individual assessment of post-game hamstring strength in players with prior hamstring injury and could be valuable to inform post-game hamstring recovery in future applications.

Pre-season body composition has minimal influence on in-season match availability, and match performance in female Australian Football League (AFLW) players.

This study examined the relationship between pre-season body composition, in-season match performance, and match availability in female players competing in the Australian Football League Women's (AFLW) competition. With the outlawing of body composition assessments as part of pre-draft player evaluations in the AFLW, this study seeks to examine whether this is justified. Twenty-two (n = 22) players had body composition assessed with dual-energy x-ray absorptiometry at the beginning of the 2021 AFLW pre-season (whole-body and regional fat mass and lean soft-tissue mass [LSTM]). In-season match availability and match performance data (Coaches Score [CS], Champion Data Player Rank, average disposals, disposal and kicking efficiency) were collected throughout the 2021 competition. Pearson correlations were performed to assess if associations existed between body composition and in-season match performance and availability. A median split was performed to divide players into higher and lower performing groups for match performance variables. Two-sample independent t-tests were then used to assess differences between groups. No body composition characteristics could differentiate between in-season match availability groups (100% availability vs. <100% availability) or higher and lower performing groups for all match performance variables. Total leg LSTM asymmetry shared a moderate negative association with CS. Body composition may not be important for determining in-season match availability and performance in female AFLW players. Thus, the repercussions following the removal of pre-draft body composition assessments across the league may not be as significant as is currently perceived. Other physiological, biomechanical, or performance qualities are more variable and may mask the effect of body composition in these players. AFLW practitioners should prioritize the development of other important attributes, such as aerobic fitness, muscular strength and power, and technical skill.

Characterising lower-body musculoskeletal morphology and whole-body composition of elite female and male Australian Football players.

BACKGROUND: Physical demands and injury rates differ between elite female and male Australian Football (AF) players. To improve understanding of contributing physical factors to these differences, the purpose of this study was to investigate lower-body morphology and whole-body composition of elite footballers competing in the Australian Football League (AFL) and Australian Football League Women's (AFLW). METHODS: Lower-body morphology and whole-body composition of 23 AFL players and 23 AFLW players were assessed using peripheral Quantitative Computed Tomography and Dual-energy X-ray Absorptiometry at the beginning of pre-season. Differences between cohorts, with sub-analyses of kicking vs. support limbs, and experienced vs. inexperienced player status were assessed using two-sample independent t-tests. Magnitude of differences were assessed using Cohen's d effect sizes. RESULTS: AFL players had greater absolute (p < 0.001; ES = 3.28) and relative (p < 0.001; ES = 2.29) whole body lean soft-tissue mass, with less absolute (p = 0.004; ES = 0.91) and relative (p < 0.001; ES = 2.29) fat mass than AFLW players. For AFLW players, no significant differences existed between kicking and support limbs with few differences observed between experienced and inexperienced players. CONCLUSIONS: Greater emphasis on physical development in AFLW players may be required to enable increases in muscle mass and skeletal robustness, to ensure they can tolerate the loads of elite competition.

Subsequent Injury Risk Is Elevated Above Baseline After Return to Play: A 5-Year Prospective Study in Elite Australian Football.

BACKGROUND: The risk of sustaining a subsequent injury is elevated in the weeks after return to play (RTP) from an index injury. However, little is known about the magnitude, duration, and nature by which subsequent injury risk is increased. PURPOSE: To quantify and describe the risk of injury in a 12-week period after RTP from an index injury in Australian football players. STUDY DESIGN: Cohort study; Level of evidence, 2. METHODS: Injury data were collected from 79 players over 5 years at 1 Australian Football League club. Injuries were classified with the Orchard Sports Injury Classification System and by side of the body. Furthermore, injury severity was classified as time loss (resulting in ≥1 matches being missed) or non-time loss (no matches missed). Subsequent injury was categorized with the SIC-2.0 model and applied to the data set via an automated script. The probability of a time loss subsequent injury was calculated for in-season index injuries for each week of a 12-week period after RTP via a mixed effect logistic regression model. RESULTS: Subsequent injury risk was found to be highest in the week of RTP for both time loss injuries (9.4%) and non-time loss injuries (6.9%). Risk decreased with each week survived after RTP; however, it did not return to baseline risk of participation (3.6%). CONCLUSION: These findings demonstrate that athletes returning to play are at an increased risk of injury for a number of weeks, thus indicating the requirement for tertiary prevention strategies to ensure that they survive this period.

How much is enough in rehabilitation? High running workloads following lower limb muscle injury delay return to play but protect against subsequent injury.

OBJECTIVES: Examine the influence of rehabilitation training loads on return to play (RTP) time and subsequent injury in elite Australian footballers. DESIGN: Prospective cohort study. METHODS: Internal (sessional rating of perceived exertion: sRPE) and external (distance, sprint distance) workload and lower limb non-contact muscle injury data was collected from 58 players over 5 seasons. Rehabilitation periods were analysed for running workloads and time spent in 3 rehabilitation stages (1: off-legs training, 2: non-football running, 3: group football training) was calculated. Multi-level survival analyses with random effects accounting for player and season were performed. Hazard ratios (HR) and 95% confidence intervals (CI) for each variable were produced for RTP time and time to subsequent injury. RESULTS: Of 85 lower limb muscle injuries, 70 were rehabilitated to RTP, with 30 cases of subsequent injury recorded (recurrence rate=11.8%, new site injury rate=31.4%). Completion of high rehabilitation workloads delayed RTP (distance: >49,775m [reference: 34,613-49,775m]: HR 0.12, 95%CI 0.04-0.36, sRPE: >1266AU [reference: 852-1266AU]: HR 0.09, 95%CI 0.03-0.32). Return to running within 4days increased subsequent injury risk (3-4days [reference: 5-6 days]: HR 25.88, 95%CI 2.06-324.4). Attaining moderate-high sprint distance (427-710m) was protective against subsequent injury (154-426m: [reference: 427-710m]: HR 37.41, 95%CI 2.70-518.64). CONCLUSIONS: Training load monitoring can inform player rehabilitation programs. Higher rehabilitation training loads delayed RTP; however, moderate-high sprint running loads can protect against subsequent injury. Shared-decision making regarding RTP should include accumulated training loads and consider the trade-off between expedited RTP and lower subsequent injury risk.

Improvement of Prediction of Noncontact Injury in Elite Australian Footballers With Repeated Exposure to Established High-Risk Workload Scenarios.

OBJECTIVES: To assess the effect of multiple high-risk-scenario (HRS) exposures on noncontact injury prediction in elite Australian footballers. DESIGN: Retrospective cohort study. METHODS: Sessional workload data (session rating of perceived exertion, global positioning system-derived distance, sprint distance, and maximum velocity) from 1 club (N = 60 players) over 3 seasons were collated; several established HRSs were also defined. Accumulated HRS sessional exposures were calculated retrospectively (previous 1-8 wk). Noncontact injury data were documented. Univariate and multivariate Poisson regression models determined injury incidence rate ratios (IRRs) while accounting for moderating effects (preseason workload volume and playing experience). Model performance was evaluated using receiver operating characteristics (area under curve). RESULTS: Very low (0-8 sessions: IRR = 5.76; 95% confidence interval [CI], 1.69-19.66) and very high (>15 sessions: IRR = 4.70; 95% CI, 1.49-14.87) exposures to >85% of an individual's maximal velocity over the previous 8 wk were associated with greater injury risk compared with moderate exposures (11-12 sessions) and displayed the best model performance (area under curve = 0.64). A single session corresponding to a very low chronic load condition over the previous week for all workload variables was associated with increased injury risk, with sprint distance (IRR = 3.25; 95% CI, 1.95-5.40) providing the most accurate prediction model (area under curve = 0.63). CONCLUSIONS: Minimal exposure to high-velocity efforts (maximum speed exposure and sprint volume) was associated with the greatest injury risk. Being underloaded may be a mediator for noncontact injury in elite Australian football. Preseason workload and playing experience were not moderators of this effect.

Identifying high risk loading conditions for in-season injury in elite Australian football players.

OBJECTIVES: To examine different timeframes for calculating acute to chronic workload ratio (ACWR) and whether this variable is associated with intrinsic injury risk in elite Australian football players. DESIGN: Prospective cohort study. METHODS: Internal (session rating of perceived exertion: sRPE) and external (GPS distance and sprint distance) workload and injury data were collected from 70 players from one AFL club over 4 seasons. Various acute (1-2 weeks) and chronic (3-8 weeks) timeframes were used to calculate ACWRs: these and chronic load categories were then analysed to determine the injury risk in the subsequent month. Poisson regression with robust errors within a generalised estimating equation were utilised to determine incidence rate ratios (IRR). RESULTS: Altering acute and/or chronic timeframes did not improve the ability to detect high injury risk conditions above the commonly used 1:4 week ACWR. Twenty-seven ACWR/chronic load combinations were found to be "high risk conditions" (IRR>1, p<0.05) for injury within 7 days. Most (93%) of these conditions occurred when chronic load was low or very low and ACWR was either low (<0.6) or high (>1.5). Once a high injury risk condition was entered, the elevated risk persisted for up to 28 days. CONCLUSIONS: Injury risk was greatest when chronic load was low and ACWR was either low or high. This heightened risk remained for up to 4 weeks. There was no improvement in the ability to identify high injury risk situations by altering acute or chronic time periods from 1:4 weeks.

Multivariate modelling of subjective and objective monitoring data improve the detection of non-contact injury risk in elite Australian footballers.

OBJECTIVES: To assess the association between workload, subjective wellness, musculoskeletal screening measures and non-contact injury risk in elite Australian footballers. DESIGN: Prospective cohort study. METHODS: Across 4 seasons in 70 players from one club, cumulative weekly workloads (acute; 1 week, chronic; 2-, 3-, 4-week) and acute:chronic workload ratio's (ACWR: 1-week load/average 4-weekly load) for session-Rating of Perceived Exertion (sRPE) and GPS-derived distance and sprint distance were calculated. Wellness, screening and non-contact injury data were also documented. Univariate and multivariate regression models determined injury incidence rate ratios (IRR) while accounting for interaction/moderating effects. Receiver operating characteristics determined model predictive accuracy (area under curve: AUC). RESULTS: Very low cumulative chronic (2-, 3-, 4- week) workloads were associated with the greatest injury risk (univariate IRR=1.71-2.16, 95% CI=1.10-4.52) in the subsequent week. In multivariate analysis, the interaction between a low chronic load and a very high distance (adj-IRR=2.60, 95% CI=1.07-6.34) or low sRPE ACWR (adj-IRR=2.52, 95% CI=1.01-6.29) was associated with increased injury risk. Subjectively reporting "yes" (vs. "no") for old lower limb pain and heavy non-football activity in the previous 7 days (multivariate adj-IRR=2.01-2.25, 95% CI=1.02-4.95) and playing experience (>9 years) (multivariate adj-IRR=2.05, 95% CI=1.03-4.06) was also associated with increased injury risk, but screening data were not. Predictive capacity of multivariate models was significantly better than univariate (AUCmultivariate=0.70, 95% CI 0.64-0.75; AUCunivariate range=0.51-0.60). CONCLUSIONS: Chronic load is an important moderating factor in the workload-injury relationship. Low chronic loads coupled with low or very high ACWR are associated with increased injury risk.

Preseason Workload Volume and High-Risk Periods for Noncontact Injury Across Multiple Australian Football League Seasons.

Colby, MJ, Dawson, B, Heasman, J, Rogalski, B, Rosenberg, M, Lester, L, and Peeling, P. Preseason workload volume and high-risk periods for noncontact injury across multiple Australian Football League seasons. J Strength Cond Res 31(7): 1821-1829, 2017-The purpose of this study was to assess the association between preseason workloads and noncontact injury risk in Australian football players. Individual player injury data were recorded over 4 full seasons (2012-15) from one professional club. Noncontact injury incidence (per 1,000 "on legs" field training and game hours) was compared across the preseason, precompetition, and in-season phases to determine relative noncontact injury risk. Preseason workloads (global positioning system-derived total distance run and sprint distance) and individual (fixed) injury risk factors (age, previous injury history) were incorporated into the analysis. A generalized estimating equation with a binary logistic function modeled potential risk factors with noncontact injury for selected periods across the annual cycle. Odds ratios were calculated to determine the relative injury risk. The (preseason) precompetition phase (19.1 injuries per 1,000 hours) and (in-season) rounds 12-17 (16.0 injuries per 1,000 hours) resulted in the highest injury incidence. Low cumulative total distances in late preseason (<108 km) and precompetition (76-88 km) periods were associated with significantly (p ≤ 0.05) greater injury risk during the in-season phase. In conclusion, these results suggest players are at the greatest injury risk during the precompetition period, with low preseason cumulative workloads associated with increased in-season injury risk. Therefore, strength and conditioning staff should place particular emphasis on achieving at least moderate training loads during and leading into this phase, where competitive game play is first introduced.

Sleep patterns and injury occurrence in elite Australian footballers.

OBJECTIVES: To examine the potential relationship between sleep duration and efficiency and injury incidence in elite Australian footballers. DESIGN: Prospective cohort study. METHODS: Australian footballers (n=22) from one AFL club were studied across the 2013 competitive season. In each week sleep duration and efficiency were recorded via actigraphy for 5 nights (the 3 nights preceding a game, the night of the game and the night after the game). Injury incidence was monitored and matched with sleep data: n=9 players suffered an injury that caused them to miss a game. Sleep in the week of the injury (T2) was compared to the average of the previous 2 weeks (T1). A two-way repeated measures ANOVA was used to determine any effect of sleep duration and efficiency on injury. Significance was accepted at p<0.05. RESULTS: Injury incidence was not significantly affected by sleep duration, sleep efficiency or a combination of these factors. Analysis of individual nights for T2 versus T1 also showed no differences in sleep quality or efficiency. However, a main effect for time was found for sleep duration and efficiency, with these being slightly, but significantly greater (p<0.05) at T2 (437±61min and 82±7%) than T1 (414±64min and 79±7%). CONCLUSIONS: No significant effect of sleep duration and efficiency on injury occurrence was found in elite Australian footballers.

Accelerometer and GPS-derived running loads and injury risk in elite Australian footballers.

The purpose of this study was to investigate the relationship between overall physical workload (global positioning systems [GPS]/accelerometer) measures and injury risk in elite Australian football players (n = 46) during a season. Workload data and (intrinsic) injury incidence were monitored across preseason and in-season (18 matches) phases. Multiple regression was used to compare cumulative (1-, 2-, 3-, and 4-weekly loads) and absolute change (from previous-to-current week) in workloads between injured and uninjured players for all GPS/accelerometer-derived variables: total distance, V1 distance (total distance above individual's aerobic threshold speed), sprint distance, force load, velocity load, and relative velocity change. Odds ratios (ORs) were calculated to determine the relative injury risk. Cumulative loads showed the strongest relationship with greater intrinsic injury risk. During preseason, 3-weekly distance (OR = 5.489, p = 0.008) and 3-weekly sprint distance (OR = 3.667, p = 0.074) were most indicative of greater injury risk. During in-season, 3-weekly force load (OR = 2.530, p = 0.031) and 4-weekly relative velocity change (OR = 2.244, p = 0.035) were associated with greater injury risk. No differences in injury risk between years of Australian Football League system experience and GPS/accelerometer data were seen. From an injury risk (prevention) perspective, these findings support consideration of several GPS/accelerometer running load variables in Australian football players. In particular, cumulative weekly loads should be closely monitored, with 3-weekly loads most indicative of a greater injury risk across both seasonal phases.

Training and game loads and injury risk in elite Australian footballers.

OBJECTIVES: To examine the relationship between combined training and game loads and injury risk in elite Australian footballers. DESIGN: Prospective cohort study. METHODS: Forty-six elite Australian footballers (mean±SD age of 22.2±2.9 y) from one club were involved in a one-season study. Training and game loads (session-RPE multiplied by duration in min) and injuries were recorded each time an athlete exerted an exercise load. Rolling weekly sums and week-to-week changes in load were then modelled against injury data using a logistic regression model. Odds ratios (OR) were reported against a reference group of the lowest training load range. RESULTS: Larger 1 weekly (>1750 AU, OR=2.44-3.38), 2 weekly (>4000 AU, OR=4.74) and previous to current week changes in load (>1250 AU, OR=2.58) significantly related (p<0.05) to a larger injury risk throughout the in-season phase. Players with 2-3 and 4-6 years of experience had a significantly lower injury risk compared to 7+ years players (OR=0.22, OR=0.28) when the previous to current week change in load was more than 1000 AU. No significant relationships were found between all derived load values and injury risk during the pre-season phase. CONCLUSIONS: In-season, as the amount of 1-2 weekly load or previous to current week increment in load increases, so does the risk of injury in elite Australian footballers. To reduce the risk of injury, derived training and game load values of weekly loads and previous week-to-week load changes should be individually monitored in elite Australian footballers.

Movement pattern comparisons in elite (AFL) and sub-elite (WAFL) Australian football games using GPS.

This study examined differences in movement patterns between AFL (elite) and WAFL (sub-elite) players using Global Positioning System (GPS) devices. Maximum speed data and totals of high intensity efforts (>15 km h⁻¹), sprint efforts (>20 km h⁻¹) and distance covered were collected on 41 players during the 2008 season. Data were expressed per min of game time played, separated into first and second halves, and also into positions, for both elite and sub-elite players. Overall, elite players had higher movement demands, including 9% more distance covered/min (128±12 m min⁻¹ vs. 117±15 m min⁻¹; p<0.01, ES=0.84), and 21% more high intensity efforts/min (2.9±0.6 vs. 2.4±0.6; p<0.01, ES=0.83). Movement demands significantly declined (p<0.05-0.01) from first to second half, in both competition levels. For both leagues, Small Forwards/Small Backs and Midfield players covered significantly greater (p<0.05-0.01) total distances and completed more high intensity efforts than other positions. Ruckmen recorded significantly lower (p<0.05-0.01) movement demands than Small Forwards/Small Backs, Midfielders and Centre Half-Forwards/Centre Half-Backs over most variables. In conclusion, elite players recorded higher overall movement demands than sub-elite players. This information may be useful for coaches and conditioning staff in designing appropriate training drills for specific role requirements of individual players and assist in the progression of players from sub-elite to elite levels of competition.