Sarto, F, Impellizzeri, FM, Spörri, J, Porcelli, S, Olmo, J, Requena, B, Suarez-Arrones, L, Arundale, A, Bilsborough, J, Buchheit, M, Clubb, J, Coutts, A, Nabhan, D, Torres-Ronda, L, Mendez-Villanueva, A, Mujika, I, Maffiuletti, NA & Franchi, MV 2020, 'Impact of Potential Physiological Changes due to COVID-19 Home Confinement on Athlete Health Protection in Elite Sports: a Call for Awareness in Sports Programming.', Sports medicine (Auckland, N.Z.), vol. 50, no. 8, pp. 1417-1419.View/Download from: Publisher's site
Collins, J, McCall, A, Bilsborough, J & Maughan, R 2017, 'Football nutrition: time for a new consensus?', BRITISH JOURNAL OF SPORTS MEDICINE, vol. 51, no. 22, pp. 1577-+.View/Download from: Publisher's site
Bilsborough, JC, Kempton, T, Greenway, K, Cordy, J & Coutts, AJ 2017, 'Longitudinal Changes and Seasonal Variation in Body Composition in Professional Australian Football Players.', International Journal of Sports Physiology and Performance, vol. 12, no. 1, pp. 10-17.View/Download from: Publisher's site
To compare development and variations in body composition of early, mid and late career professional Australian Football (AF) players over three successive seasons.Regional and total body composition body (body mass (BM), fat mass (FM), fat-free soft tissue mass (FFSTM), and bone mineral content (BMC)) was assessed four times, at the same time of each season: 1) start pre-season (SP); 2) end pre-season (EP); mid-season (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-day food diaries. Players were classified according to their age at the beginning of the observational period as either early (<21 y; N = 8), mid (21-25 y; N = 9) or late (>25 y; N = 5) career athletes.Early career players had lower FFSTM, BMC and BM compared to mid and late throughout. FM and %FM had greatest variability, particularly in the early career players. FM reduced and FFSTM increased from SP to EP, whilst FM and FFSTM decreased from EP to MS. FM increased and FFSTM decreased from MS to ES, whilst FM and FFSTM increased during the off-season.Early career players may benefit from greater emphasis upon specific nutrition and resistance training strategies aimed at increasing FFSTM, whilst all players should balance training and diet towards the end of season to minimise increases in FM.
Bilsborough, JC, Greenway, K, Livingston, S, Cordy, J & Coutts, AJ 2016, 'Changes in Anthropometry, Upper Body Strength and Nutrient Intake in Professional Australian Football Players During a Season.', International journal of sports physiology and performance, vol. 11, no. 3, pp. 290-300.View/Download from: Publisher's site
The purpose of this study was to examine the seasonal changes in body composition, nutrition, and upper body strength in professional Australian Football (AF) players. A prospective longitudinal study examined changes in anthropometry (body mass, fat-free soft tissue mass (FFSTM) and fat mass (FM)) via dual-energy X-ray absorptiometry (DXA) five times during an AF season (start-preseason, mid-preseason, start-inseason, mid-inseason, end-inseason) in 45 professional AF players. Dietary intakes and strength (bench press and bench pull) were also assessed at these time points. Players were categorised as experienced (>4 y experience, N=23) or inexperienced (<4 y experience, N=22). FM decreased during the preseason but was stable through the inseason for both groups. %FFSTM was increased during the preseason and remained constant thereafter. Upper body strength increased during the preseason and was maintained during the inseason. Changes in upper body FFSTM were related to changes in UB strength performance (r = 0.37-0.40). 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 compared to 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.
Bilsborough, JC, Greenway, KG, Opar, DA, Livingstone, SG, Cordy, JT, Bird, SR & Coutts, AJ 2015, 'Comparison of anthropometry, upper-body strength, and lower-body power characteristics in different levels of Australian football players.', Journal of Strength and Conditioning Research, vol. 29, no. 3, pp. 826-834.View/Download from: Publisher's site
The aim of this study was to compare the anthropometry, upper-body strength, and lower-body power characteristics in elite junior, sub-elite senior, and elite senior Australian Football (AF) players. Nineteen experienced elite senior (≥4 years Australian Football League [AFL] experience), 27 inexperienced elite senior (<4 years AFL experience), 22 sub-elite senior, and 21 elite junior AF players were assessed for anthropometric profile (fat-free soft tissue mass [FFSTM], fat mass, and bone mineral content) with dual-energy x-ray absorptiometry, upper-body strength (bench press and bench pull), and lower-body power (countermovement jump [CMJ] and squat jump with 20 kg). A 1-way analysis of variance assessed differences between the playing levels in these measures, whereas relationships between anthropometry and performance were assessed with Pearson's correlation. The elite senior and sub-elite senior players were older and heavier than the elite junior players (p ≤ 0.05). Both elite playing groups had greater total FFSTM than both the sub-elite and junior elite players; however, there were only appendicular FFSTM differences between the junior elite and elite senior players (p < 0.001). The elite senior playing groups were stronger and had greater CMJ performance than the lower level players. Both whole-body and regional FFSTM were correlated with bench press (r = 0.43-0.64), bench pull (r = 0.58-0.73), and jump squat performance measures (r = 0.33-0.55). Australian Football players' FFSTM are different between playing levels, which are likely because of training and partly explain the observed differences in performance between playing levels highlighting the importance of optimizing FFSTM in young players.
Coutts, AJ, Kempton, T, Sullivan, C, Bilsborough, J, Cordy, J & Rampinini, E 2015, 'Metabolic power and energetic costs of professional Australian Football match-play', JOURNAL OF SCIENCE AND MEDICINE IN SPORT, vol. 18, no. 2, pp. 219-224.View/Download from: Publisher's site
Kempton, T, Sullivan, C, Bilsborough, JC, Cordy, J & Coutts, AJ 2015, 'Match-to-match variation in physical activity and technical skill measures in professional Australian Football', Journal Of Science And Medicine In Sport, vol. 18, no. 1, pp. 109-113.View/Download from: Publisher's site
Objectives To determine the match-to-match variability in physical activity and technical performance measures in Australian Football, and examine the influence of playing position, time of season, and different seasons on these measures of variability Design Longitudinal observational study. Methods Global positioning system (GPS), accelerometer and technical performance measures (total kicks, handballs, possessions and Champion Data rank) were collected from 33 players competing in the Australian Football League over 31 matches during 2011-2012 (N = 511 observations). The GPS data were categorised into total distance, mean speed (m·min-1), high-speed running (HSR, >14.4 km·h-1), very high-speed running (VHSR, >19.9 km·h-1), and sprint (>23.0 km·h-1) distance whilst player load was collected from the accelerometer. The data was log transformed to provide coefficient of variation (CV) and the between subject standard deviation (expressed as percentages). Results Match-to-match variability was increased for higher speed activities (HSR, VHSR, sprint distance, CV%: 13.3 - 28.6%) compared to global measures (speed, total distance, player load, CV%: 5.3 - 9.2%). The between-match variability was relativity stable for all measures between and within AFL seasons, with only few differences between positions. Higher speed activities (HSR, VHSR, sprint distance), but not mean speed, total distance nor player load, were all higher in the final third phase of the season compared to the start of the season.
Moreira, A, Bilsborough, JC, Sullivan, CJ, Cianciosi, M, Aoki, MS & Coutts, AJ 2015, 'Training Periodization of Professional Australian Football Players During an Entire Australian Football League Season', INTERNATIONAL JOURNAL OF SPORTS PHYSIOLOGY AND PERFORMANCE, vol. 10, no. 5, pp. 566-571.View/Download from: Publisher's site
Bilsborough, JC, Greenway, K, Opar, D, Livingstone, S, Cordy, J & Coutts, AJ 2014, 'The accuracy and precision of DXA for assessing body composition in team sport athletes', JOURNAL OF SPORTS SCIENCES, vol. 32, no. 19, pp. 1821-1828.View/Download from: Publisher's site
Sullivan, C, Bilsborough, JC, Cianciosi, M, Hocking, J, Cordy, J & Coutts, AJ 2014, 'Factors affecting match performance in professional Australian Football', International Journal of Sports Physiology and Performance, vol. 9, no. 3, pp. 561-566.View/Download from: Publisher's site
Objectives: To determine the physical activity measures and skill performance characteristics that contribute to coaches' perception of performance and player performance rank in professional Australian football (AF). Design: Prospective, longitudinal. Methods: Physical activity profiles were assessed via microtechnology (GPS and accelerometer) from 40 professional AF players from the same team during 15 Australian Football League games. Skill performance measure and player rank scores (Champion Data© Rank) were provided by a commercial statistical provider. The physical performance variables, skill involvements and individual player performance scores were expressed relative to playing time for each quarter. A stepwise multiple regression was used to examine the contribution of physical activity and skill involvements to coaches' perception of performance and player rank in AF. Results: Stepwise multiple regression analysis revealed that 42.2% of the variance in coaches' perception of a player's performance could be explained by the skill performance characteristics (player rank/min, effective kicks/min, pressure points/min, handballs/min and running bounces/min) with a small contribution from physical activity measures (accelerations/min) [Adjusted R2 =0.422; F 6,282=36.054; p<0.001]. Multiple regression also revealed that 66.4% of the adjusted variance in player rank could be explained by total disposals/min, effective kicks/min, pressure points/min, kick clangers/min, marks/min, speed (m.min-1) and peak speed) [Adjusted R2 =0.664; F 7,281=82.289; p <0.001]. Increased physical activity throughout a match (speed [m·min-1] ß-0.097 and peak speed ß-0.116) negatively impact player rank in AF. Conclusions: Skill performance rather than increased physical activity is more important to coaches' perception of performance and player rank in professional AF
Sullivan, C, Bilsborough, JC, Cianciosi, M, Hocking, J, Cordy, J & Coutts, AJ 2014, 'Match score affects activity profile and skill performance in professional Australian Football players', Journal Of Science And Medicine In Sport, vol. 17, pp. 326-331.View/Download from: Publisher's site
Objectives To examine the influence of quarter outcome and the margin of the score differential on both the physical activity profile and skill performance of players during professional Australian Football matches. Design Prospective, longitudinal. Methods Physical activity profiles were assessed via microtechnology (Global Positioning System and accelerometer) from 40 professional AF players from the same team during 15 Australian Football League games. Skill performance measures (involvement and effectiveness) and player rank scores (Champion Data© Rank) were provided by a commercial statistical provider. The physical performance variables, skill involvements and individual player performance scores were expressed relative to playing time for each quarter. The influence of the quarter result (i.e. win vs. loss) and score margin (i.e. small: <9 points, moderate: 1018 points, and large: >19 points) on activity profile and skill involvements and skill efficiency performance of players were examined. Results Skill involvements (total disposals/min, long kicks/min, marks/min, running bounces/min and player rank/min) were greater in quarters won (all p < 0.01). In contrast, the players high speed running distance per minute (>14.5 km h-1, HSR/min), sprints/min and peak speed were higher in losing quarters (all p < 0.01). Smaller score margins were associated with increased physical activity (m/min, HSR/min, and body load/min, all p < 0.05) and decreased skill efficiency (handball clangers/min and player rank/min, all p < 0.05).
Buchheit, M, Racinais, S, Bilsborough, JC, Bourdon, PC, Voss, SC, Hocking, J, Coutts, AJ, Cordy, J & Mendez-Villanueva, A 2013, 'Monitoring fitness, fatigue and running performance during a pre-season training camp in elite football players', Journal Of Science And Medicine In Sport, vol. 16, no. 6, pp. 550-555.View/Download from: Publisher's site
Objectives To examine the usefulness of selected physiological and perceptual measures to monitor fitness, fatigue and running performance during a pre-season, 2-week training camp in eighteen professional Australian Rules Football players (21.9 ± 2.0 years). Design Observational. Methods Training load, perceived ratings of wellness (e.g. fatigue, sleep quality) and salivary cortisol were collected daily. Submaximal exercise heart rate (HRex) and a vagal-related heart rate variability index (LnSD1) were also collected at the start of each training session. Yo-Yo Intermittent Recovery level 2 test (Yo-YoIR2, assessed pre-, mid- and post-camp, temperate conditions) and high-speed running distance during standardized drills (HSR, >14.4 km h-1, 4 times throughout, outdoor) were used as performance measures.