Professional Australian Football Players Research Articles

Pain mapping of the anterior knee: injured athletes know best.

Background and aims Research investigating differences in pain location and distribution across conditions is lacking. Mapping a patient's pain may be a useful way of understanding differences in presentations, however the use of pain mapping during a pain provocation task has not been investigated. The aim of this study was to assess the reliability of patient and clinician rated pain maps during a pain provocation task for the anterior knee. Methods Participants were recruited from a larger study of professional Australian rules football players (n=17). Players were invited to participate if they reported a current or past history of patellar tendon pain. No clinical diagnosis was performed for this reliability study. Participants were asked to point on their own knee where they usually experienced pain, which was recorded by a clinician on a piloted photograph of the knee using an iPad. Participants then completed a single leg decline squat (SLDS), after which participants indicated where they experienced pain during the task with their finger, which was recorded by a clinician. Participants then recorded their own self-rated pain map. This process was repeated 10 min later. Pain maps were subjectively classified into categories of pain location and spread by two raters. Pain area was quantified by the number of pixels shaded. Intra- and inter-rater reliability (between participants and clinicians) were analysed for pain area, similarity of location as well as subjective classification. Results Test-retest reliability was good for participants (intraclass correlation coefficients [ICC]=0.81) but only fair for clinicians (ICC=0.47) for pain area. There was poor agreement between participants and clinicians for pain area (ICC=0.16) and similarity of location (Jaccard index=0.19). Clinicians had good inter- and intra-rater reliability of classification of pain spread (k=0.75 and 0.67). Conclusions Participant completed pain maps were more reliable than clinician pain maps. Clinicians were reliable at classifying pain based on location and type of spread. Implications Clinicians should ask patients to complete their own pain maps following a pain provocation test, to elicit the most reliable and consistent understanding of their pain perception.

Factors associated with early career progression in professional Australian Football players

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

To examine the collective influence of a range of physical preparation elements on selected performance measures during Australian football match play. Prospective and longitudinal. 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. 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. 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.

Early unprotected return to contact sport after metacarpal fixation in professional athletes.

To determine whether an early return to sport in professional Australian Rules Football players after fixation of a non-thumb metacarpal fracture was safe and effective. A total of 16 patients with a mean age of 25 years (19 to 30) identified as having a non-thumb metacarpal fracture underwent open reduction and internal plate and screw fixation. We compared the players' professional performance statistics before and after the injury to determine whether there was any deterioration in their post-operative performance. Of the 16, 12 sustained their fracture during the season: their mean time to return to unrestricted professional play was two weeks (1 to 5). All except two of the 48 player performance variables showed no reduction in performance post-operatively. Our data suggest that professional athletes who sustained a non-thumb metacarpal fracture can safely return to professional play without restriction two weeks after internal fixation. Cite this article: Bone Joint J 2017;99-B:1343-7.

Relationships Between Model Estimates and Actual Match-Performance Indices in Professional Australian Footballers During an In-Season Macrocycle.

To assess and compare the validity of internal and external Australian football (AF) training-load measures for predicting match exercise intensity (MEI/min) and player-rank score (PRScore) using a variable dose-response model. A cohort of 25 professional AF players (23 ± 3y, 188.3 ± 7.2cm, 87.7 ± 8.4kg) completed a 24-wk in-season macrocycle. In-season internal training and match load were quantified using session rating of perceived exertion (sRPE) and external load from satellite and accelerometer data. Using a training-impulse (TRIMP) calculation, external load (au) was represented as distance (TRIMPDist), distance ≥4.16m/s (TRIMPHSDist), and PlayerLoad (TRIMPPL). In-season training load, MEI/min, and PRScore were applied to a variable dose-response model, which provided estimates of MEI/min and PRScore. Predicted MEI/min and PRScore were correlated with actual measures from each match. The magnitude of the difference between MEI/min and PRScore estimates for each model input and the difference between the precision of internal and external load measures to predict MEI/min and PRScore were calculated using the effect size ± 90% confidence interval (CI). Estimates of MEI/min demonstrated very large associations with actual MEI/min (r, 90% CI) (eg, TRIMPDist .76 ± .13, and sRPESkills .73 ± .14). Estimates of PRScore demonstrated associations of large magnitude with actual PRScore using the same inputs. Precision of actual MEI/min was lowest using sRPE compared with (ES ± 90% CI) TRIMPDist, -.67 ± .34, and TRIMPPL, -.91 ± .39. There were trivial and unclear differences in the precision of PRScore estimates between TRIMP and sRPE inputs. Dose-response models from multiple training-load inputs can predict within-individual variation of MEI/min and PRScore. Internal and external training-input methods exhibited comparable predictive power.

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

ObjectivesTo examine the effects of match-related and individual player characteristics on activity profile and technical performance during rotations in professional Australian football. DesignLongitudinal observational study. MethodsGlobal 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. ResultsRotation 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. ConclusionThe complex relationship between factors that influence activity profile and technical performance during rotations in Australian football needs to be considered when interpreting match performance.

Laterality frequency, team familiarity, and game experience affect kicking-foot identification in Australian football players

This study examined whether laterality frequency, team familiarity, and game experience affected preferred kicking foot identification in professional Australian Football players. Using a repeated-measures experimental design, 13 and 10 players, respectively, identified the kicking foot of 30 teammates and 30 opponents using static images in a randomised sequence. Accuracy (%), reaction time (RT ms), and discrimination capability indices were examined. Overall, participants were less accurate and had slower reaction times when identifying the kicking foot of opposing team players relative to the speed and accuracy of identifying teammates. Significantly lower discrimination accuracy was also evident in participants’ capability to identify left-footed players from two different opposing teams. In moderating trends, opposing player game experience was correlated with accuracy and reduced reaction times, while participant game experience correlated with faster reaction times only. Laterality, (opposing) team familiarity, and game experience affect kicking foot identification in Australian Football with training and performance implications.

Factors Affecting Match Running Performance in Professional Australian Football.

To examine the influence of a range of individual player characteristics and match-related factors on activity profiles during professional Australian football matches. 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. 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. 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.

Self-Reported Wellness Profiles of Professional Australian Football Players During the Competition Phase of the Season.

Gallo, TF, Cormack, SJ, Gabbett, TJ, and Lorenzen, CH. Self-reported wellness profiles of professional Australian football players during the competition phase of the season. J Strength Cond Res 31(2): 495-502, 2017-With the prevalence of customized self-report measures in high-performance sport, and the incomplete understanding of athletes' perceived wellness in response to matches and training load, the objective of this study was to explore weekly wellness profiles within the context of the competitive season of professional Australian football. Internal match load, measured through the session-rating of perceived exertion method, match-to-match microcycle, stage of the season, and training load were included in multivariate linear models to determine their effect on weekly wellness profile (n = 1,835). There was a lower weekly training load on a 6-day microcycle compared with a 7-day and 8-day microcycle. Match load had no significant impact on weekly wellness profile, while there was an interaction between microcycle and days postmatch. There was a likely moderately lower wellness Z-score 1 day postmatch for an 8-day microcycle (mean; 95% confidence interval: -1.79; -2.02 to -1.56) compared with a 6-day (-1.19; -1.30 to -1.08) and 7-day (-1.22; -1.34 to -1.09) cycle (d; 95% confidence interval: -0.82; -1.3 to -0.36, -0.78; -1.3 to -0.28, respectively). The second half of the season saw a possibly small reduction in overall wellness Z-score than the first half of the season (0.22; 0.12-0.32). Finally, training load had no effect on wellness Z-score when controlled for days postmatch, microcycle, and stage of the season. These results provide information on the status of players in response to matches and fixed conditions. Knowing when wellness Z-score returns to baseline relative to the length of the microcycle may lead practitioners to prescribe the heaviest load of the week accordingly. Furthermore, wellness "red flags" should be made relative to the microcycles and stage of the season to determine an athlete's status relative to their typical weekly profile.

Duration-specific running intensities of Australian Football match-play.

To establish the position and duration-specific running demands of Australian Football (AF) competition for the prescription and monitoring of specific training drills. An observational time-motion analysis was performed on 40 professional AF players during 30 games throughout the 2014-15 competitive seasons. Player movements were collected and peak values were calculated for moving averages of between 1-10min in duration for relative distance (mmin-1), high-speed relative distance (HSmmin-1), average acceleration/deceleration (ms2) and metabolic power (Pmet). A mixed-model analysis was used to detect positional differences, and differences were described using a magnitude-based network. Relative distance was likely greater for midfielders (MID), and mobile forwards (MF) compared to tall backs (TB) across all moving average durations assessed, with MF peaking at 223±35mmin-1 for a 1-min window. High-speed relative distance was at least likely to be greater for MF compared to all other positions, across all moving average durations (ES=0.27-0.94). Acceleration/deceleration demands were similar across positions. The present study demonstrated that the peak running intensities of AF are well above previously reported peak intensities when considering the distance-based running requirements of match-play. Whilst the acceleration-based metric was unable to detect large differences between positions, it is important to note their contribution to the overall competition demands. This study presents a useful framework for the prescription and monitoring of drills specific to AF competition requirements.

Predicting ratings of perceived exertion in Australian football players: methods for live estimation

Abstract The ability of machine learning techniques to predict athlete ratings of perceived exertion (RPE) was investigated in professional Australian football players. RPE is commonly used to quantifying internal training loads and manage injury risk in team sports. Data from global positioning systems, heart-rate monitors, accelerometers and wellness questionnaires were recorded for each training session (n=3398) from 45 professional Australian football players across a full season. A variety of modelling approaches were considered to investigate the ability of objective data to predict RPE. Models were compared using nested cross validation and root mean square error (RMSE) on RPE predictions. A random forest model using player normalised running and heart rate variables provided the most accurate predictions (RMSE ± SD = 0.96 ± 0.08 au). A simplification of the model using only total distance, distance covered at speeds between 18-24 km·h−1, and the product of total distance and mean speed provided similarly accurate predictions (RMSE ± SD = 1.09 ± 0.05 au), suggesting that running distances and speeds are the strongest predictors of RPE in Australian football players. The ability of non-linear machine learning models to accurately predict athlete RPE has applications in live player monitoring and training load planning.

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

To compare development and variations in body composition of early-, mid-, and late-career professional Australian Football (AF) players over 3 successive seasons. 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. 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. 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.

Relationships Between Internal and External Training Load in Team-Sport Athletes: Evidence for an Individualized Approach.

The aim of this study was to quantify and predict relationships between rating of perceived exertion (RPE) and GPS training-load (TL) variables in professional Australian football (AF) players using group and individualized modeling approaches. TL data (GPS and RPE) for 41 professional AF players were obtained over a period of 27 wk. A total of 2711 training observations were analyzed with a total of 66 ± 13 sessions/player (range 39-89). Separate generalized estimating equations (GEEs) and artificial-neural-network analyses (ANNs) were conducted to determine the ability to predict RPE from TL variables (ie, session distance, high-speed running [HSR], HSR %, m/min) on a group and individual basis. Prediction error for the individualized ANN (root-mean-square error [RMSE] 1.24 ± 0.41) was lower than the group ANN (RMSE 1.42 ± 0.44), individualized GEE (RMSE 1.58 ± 0.41), and group GEE (RMSE 1.85 ± 0.49). Both the GEE and ANN models determined session distance as the most important predictor of RPE. Furthermore, importance plots generated from the ANN revealed session distance as most predictive of RPE in 36 of the 41 players, whereas HSR was predictive of RPE in just 3 players and m/min was predictive of RPE in just 2 players. This study demonstrates that machine learning approaches may outperform more traditional methodologies with respect to predicting athlete responses to TL. These approaches enable further individualization of load monitoring, leading to more accurate training prescription and evaluation.

Do Australian Football players have sensitive groins? Players with current groin pain exhibit mechanical hyperalgesia of the adductor tendon.

This is the first study to evaluate the mechanical sensitivity, clinical classifications and prevalence of groin pain in Australian football players. Case-control. Professional (n=66) and semi-professional (n=9) Australian football players with and without current or previous groin injuries were recruited. Diagnoses were mapped to the Doha Agreement taxonomy. Point and career prevalence of groin pain was calculated. Pressure pain thresholds (PPTs) were assessed at regional and distant sites using handheld pressure algometry across four sites bilaterally (adductor longus tendon, pubic bone, rectus femoris, tibialis anterior muscle). To assess the relationship between current groin pain and fixed effects of hyperalgesia of each site and a history of groin pain, a mixed-effect logistic regression model was utilised. Receiver Operator Characteristic (ROC) curve were determined for the model. Point prevalence of groin pain in the preseason was 21.9% with a career prevalence of 44.8%. Adductor-related groin pain was the most prevalent classification in the pre-season period. Hyperalgesia was observed in the adductor longus tendon site in athletes with current groin pain (OR=16.27, 95% CI 1.86 to 142.02). The ROC area under the curve of the regression model was fair (AUC=0.76, 95% CI 0.54 to 0.83). Prevalence data indicates that groin pain is a larger issue than published incidence rates imply. Adductor-related groin pain is the most common diagnosis in pre-season in this population. This study has shown that hyperalgesia exists in Australian football players experiencing groin pain indicating the value of assessing mechanical pain sensitivity as a component of the clinical assessment.

Changes in Anthropometry, Upper-Body Strength, and Nutrient Intake in Professional Australian Football Players During a Season.

The purpose of this study was to examine the seasonal changes in body composition, nutrition, and upper-body (UB) strength in professional Australian Football (AF) players. The prospective longitudinal study examined changes in anthropometry (body mass, fat-free soft-tissue mass [FFSTM], and fat mass) via dual-energy X-ray absorptiometry 5 times during an AF season (start preseason, midpreseason, start season, midseason, end season) in 45 professional AF players. Dietary intakes and strength (bench press and bench pull) were also assessed at these time points. Players were categorized as experienced (>4 y experience, n = 23) or inexperienced (<4 y experience, n = 22). Fat mass decreased during the preseason but was stable through the in-season for both groups. %FFSTM was increased during the preseason and remained constant thereafter. UB strength increased during the preseason and was maintained during the in-season. Changes in UB FFSTM were related to changes in UB-strength performance (r = .37-.40). Total energy and carbohydrate intakes were similar between the experienced and inexperienced players during the season, but there was a greater ratio of dietary fat intake at the start-preseason point and an increased alcohol, reduced protein, and increased total energy intake at the end of the season. The inexperienced players consumed more fat at the start of season and less total protein during the season than the experienced players. Coaches should also be aware that it can take >1 y to develop the appropriate levels of FFSTM in young players and take a long-term view when developing the physical and performance abilities of inexperienced players.

GPS variables most related to match performance in an elite Australian football team

The purpose of this study is to identify which GPS variables are most related to Australian football (AF) physical performance. Data was collected from thirty-five professional AF players over 11 games early in the 2013 Australian Football League (AFL) season. Match performance was measured by the Champion Data© Player Rank (PR) and coaches’ ratings (CR). Variables were sampled at 10Hz and partial correlations adjusted for game time were calculated between all variables and both performance measures, by position. Variables that displayed the highest partial correlations with both performance measures were used in a stepwise regression to identify the most relevant to performance. For the nomadic group, a negative relationship (P<0.05) was found between walking (distance and # entries) and PR. For the fixed players, a negative relationship (P<0.05) was evident between sprinting (# entries) and PR. However, a positive relationship (P<0.05) was found between CR and HSR (% time) and sprinting (distance). This indicates that the GPS variables that most relate to performance depend on the performance measure employed by coaches.

Effects of northbound long-haul international air travel on sleep quantity and subjective jet lag and wellness in professional Australian soccer players.

The current study examined the effects of 10-h northbound air travel across 1 time zone on sleep quantity, together with subjective jet lag and wellness ratings, in 16 male professional Australian football (soccer) players. Player wellness was measured throughout the week before (home training week) and the week of (away travel week) travel from Australia to Japan for a preseason tour. Sleep quantity and subjective jet lag were measured 2 d before (Pre 1 and 2), the day of, and for 5 d after travel (Post 1-5). Sleep duration was significantly reduced during the night before travel (Pre 1; 4.9 [4.2-5.6] h) and night of competition (Post 2; 4.2 [3.7-4.7] h) compared with every other night (P<.01, d>0.90). Moreover, compared with the day before travel, subjective jet lag was significantly greater for the 5 d after travel (P<.05, d>0.90), and player wellness was significantly lower 1 d post-match (Post 3) than at all other time points (P<.05, d>0.90). Results from the current study suggest that sleep disruption, as a result of an early travel departure time (8 PM) and evening match (7:30 PM), and fatigue induced by competition had a greater effect on wellness ratings than long-haul air travel with a minimal time-zone change. Furthermore, subjective jet lag may have been misinterpreted as fatigue from sleep disruption and competition, especially by the less experienced players. Therefore, northbound air travel across 1 time zone from Australia to Asia appears to have negligible effects on player preparedness for subsequent training and competition.

Training periodization of professional Australian football players during an entire Australian Football League season.

To examine the training periodization of an elite Australian Football team during different phases of the season. Training-load data were collected during 22 wk of preseason and 23 wk of in-season training. Training load was measured using the session rating of perceived exertion (session-RPE) for all training sessions and matches from 44 professional Australian Football players from the same team. Training intensity was divided into 3 zones based on session-RPE (low, <4; moderate, >4 AU and <7 AU; and high, >7 AU). Training load and intensity were analyzed according to the type of training session completed. Higher training load and session duration were undertaken for all types of training sessions during the preseason than in-season (P<.05), with the exception of "other" training (ie, re/prehabilitation training, cross-training, and recovery activities). Training load and intensity were higher during the preseason, with the exception of games, where greater load and intensity were observed during the in-season. The overall distribution of training intensity was similar between phases with the majority of training performed at moderate or high intensity. The current findings may allow coaches and scientists to better understand the characteristics of Australian Football periodization, which in turn may aid in developing optimal training programs. The results also indicate that a polarized training-intensity distribution that has been reported in elite endurance athletes does not occur in professional Australian Football.

Biomechanical characteristics of handballing maximally in Australian football

The handball pass is influential in Australian football, and achieving higher ball speeds in flight is an advantage in increasing distance and reducing the chance of interceptions. The purpose of this study was to provide descriptive kinematic data and identify key technical aspects of maximal handball performance. Three-dimensional full body kinematic data from 19 professional Australian football players performing handball pass for maximal speed were collected, and the hand speed at ball contact was used to determine performance. Sixty-four kinematic parameters initially obtained were reduced to 15, and then grouped into like components through a two-stage supervised principal components analysis procedure. These components were then entered into a multiple regression analysis, which indicated that greater hand speed was associated with greater shoulder angular velocity and separation angle between the shoulders and pelvis at ball contact, as well as an earlier time of maximum upper-trunk rotation velocity. These data suggested that in order to increase the speed of the handball pass in Australian football, strategies like increased shoulder angular velocity, increased separation angle at ball contact, and earlier achievement of upper-trunk rotation speed might be beneficial.

The accuracy and precision of DXA for assessing body composition in team sport athletes

This study determined the precision of pencil and fan beam dual-energy X-ray absorptiometry (DXA) devices for assessing body composition in professional Australian Football players. Thirty-six professional Australian Football players, in two groups (fan DXA, N = 22; pencil DXA, N = 25), underwent two consecutive DXA scans. A whole body phantom with known values for fat mass, bone mineral content and fat-free soft tissue mass was also used to validate each DXA device. Additionally, the criterion phantom was scanned 20 times by each DXA to assess reliability. Test–retest reliability of DXA anthropometric measures were derived from repeated fan and pencil DXA scans. Fat-free soft tissue mass and bone mineral content from both DXA units showed strong correlations with, and trivial differences to, the criterion phantom values. Fat mass from both DXA showed moderate correlations with criterion measures (pencil: r = 0.64; fan: r = 0.67) and moderate differences with the criterion value. The limits of agreement were similar for both fan beam DXA and pencil beam DXA (fan: fat-free soft tissue mass = −1650 ± 179 g, fat mass = −357 ± 316 g, bone mineral content = 289 ± 122 g; pencil: fat-free soft tissue mass = −1701 ± 257 g, fat mass = −359 ± 326 g, bone mineral content = 177 ± 117 g). DXA also showed excellent precision for bone mineral content (coefficient of variation (%CV) fan = 0.6%; pencil = 1.5%) and fat-free soft tissue mass (%CV fan = 0.3%; pencil = 0.5%) and acceptable reliability for fat measures (%CV fan: fat mass = 2.5%, percent body fat = 2.5%; pencil: fat mass = 5.9%, percent body fat = 5.7%). Both DXA provide precise measures of fat-free soft tissue mass and bone mineral content in lean Australian Football players. DXA-derived fat-free soft tissue mass and bone mineral content are suitable for assessing body composition in lean team sport athletes.