Ward, PA, Ramsden, S, Coutts, AJ, Hulton, AT & Drust, B 2018, 'Positional Differences in Running and Non-Running Activities During Elite American Football Training', Journal of Strength and Conditioning Research, vol. 32, no. 7, pp. 2072-2084.View/Download from: UTS OPUS or Publisher's site
The aim of this investigation was to describe differences in training loads between position groups within professional American football. Integrated micro technology data was collected on 63 NFL football players during an American football training camp. Five key metrics (total distance, high speed distance, Player Load, Player Load per Minute, and Total Inertial Movement Analysis (IMA)) served to quantify both running and non-running activities. Players were classified into position groups (DB, DL, LB, OL, QB, RB, TE, and WR). Training sessions were identified by their relationship to the upcoming match (e.g., -4, -3, -2). Running and non-running activities varied between position groups relative to the training day. Differences in total distance were between DB and WR were observed to be unclear between the three training days (Game Day (GD) -4: 74 ± 392 m; GD -3: -122 ± 348; GD - 2: -222 ± 371 m). However, moderate to large differences were observed between these two positions and the other positional groups. A similar relationship was observed in Player Load and Player Load per Minute, with the DB and WR groups performing greater amounts of load compared to other positional groups. Differences in High Speed Distance varied across positional groups, indicating different outputs based on ergonomic demands. The OL and DL groups ran less but engaged in a higher amount of non-running activities (Total IMA) with differences ranging from moderate to large across the three training days. Total IMA differences between offensive and defensive linemen were unclear on GD -4 (-4 ± 9) and GD -2 (-2 ± 8) and likely moderate on GD -3 (-9 ± 9). Positional differences with regard to running and non-running activities highlight the existence of position specific training within a training micro-cycle. Additionally, Total IMA provides a useful metric for quantifying sport specific movements within the game of American football.
Sullivan, C, Kempton, T, Ward, P & Coutts, AJ 2018, 'Factors associated with early career progression in professional Australian Football players.', Journal of sports sciences, vol. 36, no. 19, pp. 2196-2201.View/Download from: UTS OPUS or Publisher's site
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.