Bourdon PC, Cardinale M, Murray A, Gastin P, Kellmann M, Varley MC, et al. Monitoring athlete training loads: consensus statement. Int J Sports Physiol Perform. 2017;12(Suppl 2):161–70. https://doi.org/10.1123/ijspp.2017-0208.
Article
Google Scholar
Stares J, Dawson B, Peeling P, Heasman J, Rogalski B, Drew M, et al. Identifying high risk loading conditions for in-season injury in elite Australian football players. J Sci Med Sport. 2018;21(1):46–51 doi:https://doi.org/10.1016/j.jsams.2017.05.012.
Article
Google Scholar
Soligard T, Schwellnus M, Alonso J-M, Bahr R, Clarsen B, Dijkstra HP, et al. How much is too much? (part 1) International Olympic Committee consensus statement on load in sport and risk of injury. Br J Sports Med. 2016;50(17):1030–41. https://doi.org/10.1136/bjsports-2016-096581.
Article
PubMed
Google Scholar
Impellizzeri FM, Rampinini E, Marcora SM. Physiological assessment of aerobic training in soccer. J Sports Sci. 2005;23(6):583–92. https://doi.org/10.1080/02640410400021278.
Article
PubMed
Google Scholar
Bannister EW, Calvert, T.W., Savage, M.V. and Bach, T.M. A systems model of training for athletic performance. Aust J Sports Med 1975(7):57–61.
Drew MK, Finch CF. The relationship between training load and injury, illness and soreness: a systematic and literature review. Sports Med. 2016;46(6):861–83. https://doi.org/10.1007/s40279-015-0459-8.
Article
PubMed
Google Scholar
McLaren SJ, Macpherson TW, Coutts AJ, Hurst C, Spears IR, Weston M. The relationships between internal and external measures of training load and intensity in team sports: a meta-analysis. Sports Med. 2018;48(3):641–58. https://doi.org/10.1007/s40279-017-0830-z.
Article
PubMed
Google Scholar
Saw AE, Main LC, Gastin PB. Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review. Br J Sports Med. 2016;50(5):281–91. https://doi.org/10.1136/bjsports-2015-094758.
Article
PubMed
Google Scholar
Smith MR, Fransen J, Coutts A. Inducing and assessing cognitive fatigue. Amsterdam: European College of Sport Science Annual Congress; 2014.
Google Scholar
Burgess DJ. The research doesn’t always apply: practical solutions to evidence-based training-load monitoring in elite team sports. Int J Sports Physiol Perform. 2017;12(Suppl 2):S2-136–S2-41. https://doi.org/10.1123/ijspp.2016-0608.
Article
Google Scholar
Saw AE, Kellmann M, Main LC, Gastin PB. Athlete self-report measures in research and practice: considerations for the discerning reader and fastidious practitioner. Int J Sports Physiol Perform. 2017;12:S2–127 S2–35.
Article
Google Scholar
Gabbett TJ. The development and application of an injury prediction model for noncontact, soft-tissue injuries in elite collision sport athletes. J Strength Con Res. 2010;24(10):2593–603. https://doi.org/10.1519/JSC.0b013e3181f19da4.
Article
Google Scholar
Gabbett TJ. The training-injury prevention paradox: should athletes be training smarter and harder? Br J Sports Med. 2016;50(5):273–80. https://doi.org/10.1136/bjsports-2015-095788.
Article
PubMed
PubMed Central
Google Scholar
Blanch P, Gabbett TJ. Has the athlete trained enough to return to play safely? The acute:chronic workload ratio permits clinicians to quantify a player’s risk of subsequent injury. Br J Sports Med. 2015;50(8):471–5. https://doi.org/10.1136/bjsports-2015-095445.
Article
PubMed
Google Scholar
Ritchie D, Hopkins WG, Buchheit M, Cordy J, Bartlett JD. Quantification of training load during return to play after upper- and lower-body injury in Australian rules football. Int J Sports Physiol Perform. 2017;12(5):634–41. https://doi.org/10.1123/ijspp.2016-0300.
Article
PubMed
Google Scholar
Fanchini M, Rampinini E, Riggio M, Coutts AJ, Pecci C, McCall A. Despite association, the acute:chronic work load ratio does not predict non-contact injury in elite footballers. Sci Med in Football. 2018:1–7. https://doi.org/10.1080/24733938.2018.1429014.
Pickering C, Kiely J. ACTN3: more than just a gene for speed. Front Physiol. 2017;8:1080. https://doi.org/10.3389/fphys.2017.01080.
Article
PubMed
PubMed Central
Google Scholar
Fulton J, Wright K, Kelly M, Zebrosky B, Zanis M, Drvol C, et al. Injury risk is altered by previous injury: a systematic review of the literature and presentation of causative neuromuscular factors. Int J Sports Phys Ther. 2014;9(5):583–95.
PubMed
PubMed Central
Google Scholar
Mann JB, Bryant K, Johnstone B, Ivey P, Sayers SP. The effect of physical and academic stress on illness and injury in division 1 college football players. J Strength Con Res. 2015;30(1):20–5. https://doi.org/10.1519/jsc.0000000000001055.
Article
Google Scholar
Timpka T, Jacobsson J, Bargoria V, Périard JD, Racinais S, Ronsen O, et al. Preparticipation predictors for championship injury and illness: cohort study at the Beijing 2015 International Association Of Athletics Federations World Championships. Br J Sports Med. 2017;51(4):271–6. https://doi.org/10.1136/bjsports-2016-096580.
Article
PubMed
Google Scholar
Timpka T, Jacobsson J, Dahlström Ö, Kowalski J, Bargoria V, Ekberg J, et al. The psychological factor ‘self-blame’ predicts overuse injury among top-level Swedish track and field athletes: a 12-month cohort study. Br J Sports Med. 2015;49(22):1472–7. https://doi.org/10.1136/bjsports-2015-094622.
Article
PubMed
Google Scholar
Tranaeus U, Johnson U, Engstrom B, Skillgate E, Werner S. A psychological injury prevention group intervention in Swedish Floorball. Knee Surg Sports Traumatol Arthrosc. 2015;23(11):3414–20. https://doi.org/10.1007/s00167-014-3133-z.
Article
PubMed
Google Scholar
Ekstrand J, Lundqvist D, Lagerbäck L, Vouillamoz M, Papadimitiou N, Karlsson J. Is there a correlation between coaches’ leadership styles and injuries in elite football teams? A study of 36 elite teams in 17 countries. Br J Sports Med. 2018;52:527–31. https://doi.org/10.1136/bjsports-2017-098001.
Article
PubMed
Google Scholar
Hulin BT. The never-ending search for the perfect acute:chronic workload ratio: what role injury definition? Br J Sports Med. 2017;51(13):991–2. https://doi.org/10.1136/bjsports-2016-097279.
Article
PubMed
Google Scholar
Toohey LA, Drew MK, Fortington LV, Finch CF, Cook JL. An updated subsequent injury categorisation model (SIC-2.0): data-driven categorisation of subsequent injuries in sport. Sports Med. 2018. https://doi.org/10.1007/s40279-018-0879-3.
Jeukendrup AE. Periodized nutrition for athletes. Sports Med (Auckland, Nz). 2017;47(Suppl 1):51–63. https://doi.org/10.1007/s40279-017-0694-2.
Article
Google Scholar
Drew MK, Raysmith BP, Charlton PC. Injuries impair the chance of successful performance by sportspeople: a systematic review. Br J Sports Med. 2017;51(16):1209–14. https://doi.org/10.1136/bjsports-2016-096731.
Article
PubMed
Google Scholar
Raysmith BP, Drew MK. Performance success or failure is influenced by weeks lost to injury and illness in elite Australian track and field athletes: a 5-year prospective study. J Sci Med Sport. 2016;19(10):778–83. https://doi.org/10.1016/j.jsams.2015.12.515.
Article
PubMed
Google Scholar
Carleton EL, Barling J, Christie AM, Trivisonno M, Tulloch K, Beauchamp MR. Scarred for the rest of my career? Career-long effects of abusive leadership on professional athlete aggression and task performance. J Sport Exerc Psychol. 2016;38(4):409–22. https://doi.org/10.1123/jsep.2015-0333.
Article
PubMed
Google Scholar
Davis L, Appleby R, Davis P, Wetherell M, Gustafsson H. The role of coach-athlete relationship quality in team sport athletes’ psychophysiological exhaustion: implications for physical and cognitive performance. J Sports Sci. 2018:1–8. https://doi.org/10.1080/02640414.2018.1429176.
Weaving D, Jones B, Till K, Abt G, Beggs C. The case for adopting a multivariate approach to optimize training load quantification in team sports. Front Physiol. 2017;8:1024. https://doi.org/10.3389/fphys.2017.01024.
Article
PubMed
PubMed Central
Google Scholar
Kiely J. Periodization theory: confronting an inconvenient truth. Sports Med. 2018;48(4):753–64. https://doi.org/10.1007/s40279-017-0823-y.
Article
PubMed
Google Scholar
Le Mansec Y, Pageaux B, Nordez A, Dorel S, Jubeau M. Mental fatigue alters the speed and the accuracy of the ball in table tennis. J Sports Sci. 2017:1–9. https://doi.org/10.1080/02640414.2017.1418647.
Smith MR, Coutts AJ, Merlini M, Deprez D, Lenoir M, Marcora SM. Mental fatigue impairs soccer-specific physical and technical performance. Med Sci Sports Exerc. 2016;48(2):267–76. https://doi.org/10.1249/mss.0000000000000762.
Article
PubMed
Google Scholar
Marcora SM, Staiano W, Manning V. Mental fatigue impairs physical performance in humans. J Appl Physiol. 2009;106(3):857–64. https://doi.org/10.1152/japplphysiol.91324.2008.
Article
PubMed
Google Scholar
Stults-Kolehmainen MA, Bartholomew JB, Sinha R. Chronic psychological stress impairs recovery of muscular function and somatic sensations over a 96-hour period. J Strength Con Res. 2014;28(7):2007–17. https://doi.org/10.1519/jsc.0000000000000335.
Article
Google Scholar
Di Russo F, Bultrini A, Brunelli S, Delussu AS, Polidori L, Taddei F, et al. Benefits of sports participation for executive function in disabled athletes. J Neurotrauma. 2010;27(12):2309–19. https://doi.org/10.1089/neu.2010.1501.
Article
PubMed
PubMed Central
Google Scholar
Wang C-H, Chang C-C, Liang Y-M, Shih C-M, Chiu W-S, Tseng P, et al. Open vs. closed skill sports and the modulation of inhibitory control. PLoS One. 2013;8(2):e55773. https://doi.org/10.1371/journal.pone.0055773.
Article
CAS
PubMed
PubMed Central
Google Scholar
Mann DT, Williams AM, Ward P, Janelle CM. Perceptual-cognitive expertise in sport: a meta-analysis. J Sport Exerc Psychol. 2007;29(4):457–78.
Article
Google Scholar
Yarrow K, Brown P, Krakauer JW. Inside the brain of an elite athlete: the neural processes that support high achievement in sports. Nat Rev Neurosci. 2009;10(8):585–96. https://doi.org/10.1038/nrn2672.
Article
CAS
PubMed
Google Scholar
Nakata H, Yoshie M, Miura A, Kudo K. Characteristics of the athletes’ brain: evidence from neurophysiology and neuroimaging. Brain Res Rev. 2010;62(2):197–211. https://doi.org/10.1016/j.brainresrev.2009.11.006.
Article
PubMed
Google Scholar
Overney LS, Blanke O, Herzog MH. Enhanced temporal but not attentional processing in expert tennis players. PLoS One. 2008;3(6):e2380. https://doi.org/10.1371/journal.pone.0002380.
Article
CAS
PubMed
PubMed Central
Google Scholar
Cunanan AJ, DeWeese BH, Wagle JP, Carroll KM, Sausaman R, Hornsby WG, et al. The general adaptation syndrome: a foundation for the concept of periodization. Sports Med. 2018;48(4):787–97. https://doi.org/10.1007/s40279-017-0855-3.
Article
PubMed
Google Scholar
Wilson TD, Gilbert DT. Explaining away: a model of affective adaptation. Perspect Psychol Sci. 2008;3(5):370–86. https://doi.org/10.1111/j.1745-6924.2008.00085.x.
Article
PubMed
Google Scholar
Delaney JA, Duthie GM, Thornton HR, Pyne DB. Quantifying the relationship between internal and external work in team sports: development of a novel training efficiency index. Sci Med Football. 2018:1–8. https://doi.org/10.1080/24733938.2018.1432885.
Graham SR, Cormack S, Parfitt G, Eston R. Relationships between model predicted and actual match performance in professional Australian footballers during an in-season training macrocycle. Int J Sports Physiol Perform. 2017:1–25. https://doi.org/10.1123/ijspp.2017-0026.
Barrett S, McLaren S, Spears I, Ward P, Weston M. The influence of playing position and contextual factors on soccer players’ match differential ratings of perceived exertion: a preliminary investigation. Sports. 2018;6(1):13.
Article
Google Scholar
Weston M, Siegler J, Bahnert A, McBrien J, Lovell R. The application of differential ratings of perceived exertion to Australian football league matches. J Sci Med Sport. 2015;18(6):704–8. https://doi.org/10.1016/j.jsams.2014.09.001.
Article
PubMed
Google Scholar
Wallace LK, Slattery KM, Coutts AJ. A comparison of methods for quantifying training load: relationships between modelled and actual training responses. Eur J Appl Physiol. 2014;114(1):11–20. https://doi.org/10.1007/s00421-013-2745-1.
Article
CAS
PubMed
Google Scholar
Jaspers A, Beéck TOD, Brink MS, Frencken WGP, Staes F, Davis JJ, et al. Relationships between the external and internal training load in professional soccer: what can we learn from machine learning? Int J Sports Physiol Perform. 2018;13(5):625–30. https://doi.org/10.1123/ijspp.2017-0299.
Article
PubMed
Google Scholar
Sullivan C, Bilsborough JC, Cianciosi M, Hocking J, Cordy JT, Coutts AJ. Factors affecting match performance in professional Australian football. Int J Sports Physiol Perform. 2014;9(3):561–6. https://doi.org/10.1123/ijspp.2013-0183.
Article
PubMed
Google Scholar
Fox JL, Stanton R, Sargent C, Wintour S-A, Scanlan AT. The association between training load and performance in team sports: a systematic review. Sports Med. 2018;48(12):2743–74. https://doi.org/10.1007/s40279-018-0982-5.
Article
PubMed
Google Scholar
Aughey RJ, Elias GP, Esmaeili A, Lazarus B, Stewart AM. Does the recent internal load and strain on players affect match outcome in elite Australian football? J Sci Med Sport. 2016;19(2):182–6. https://doi.org/10.1016/j.jsams.2015.02.005.
Article
PubMed
Google Scholar
McCaskie CJ, Young WB, Fahrner BB, Sim M. Association between pre-season training and performance in elite Australian football. Int J Sports Physiol Perform. 0(0):1–25. https://doi.org/10.1123/ijspp.2018-0076.
Crowcroft S, McCleave E, Slattery K, Coutts AJ. Assessing the measurement sensitivity and diagnostic characteristics of athlete monitoring tools in national swimmers. Int J Sports Physiol Perform. 2016:1–21. https://doi.org/10.1123/ijspp.2016-0406.
Wood RE, Hayter S, Rowbottom D, Stewart I. Applying a mathematical model to training adaptation in a distance runner. Eur J Appl Physiol. 2005;94(3):310–6. https://doi.org/10.1007/s00421-005-1319-2.
Article
PubMed
Google Scholar
Hagglund M, Walden M, Magnusson H, Kristenson K, Bengtsson H, Ekstrand J. Injuries affect team performance negatively in professional football: an 11-year follow-up of the UEFA champions league injury study. Br J Sports Med. 2013;47(12):738–42. https://doi.org/10.1136/bjsports-2013-092215.
Article
PubMed
Google Scholar
Haddad M, Stylianides G, Djaoui L, Dellal A, Chamari K. Session-RPE method for training load monitoring: validity, ecological usefulness, and influencing factors. Frontiers in Neuroscience. 2017;11:612. https://doi.org/10.3389/fnins.2017.00612.
Article
PubMed
PubMed Central
Google Scholar
Fanchini M, Ferraresi I, Modena R, Schena F, Coutts AJ, Impellizzeri FM. Use of CR100 scale for session rating of perceived exertion in soccer and its interchangeability with the CR10. Int J Sports Physiol Perform. 2016;11(3):388–92. https://doi.org/10.1123/ijspp.2015-0273.
Article
PubMed
Google Scholar
Scott TJ, Black CR, Quinn J, Coutts AJ. Validity and reliability of the session-RPE method for quantifying training in Australian football: a comparison of the CR10 and CR100 scales. J Strength Con Res. 2013;27(1):270–6. https://doi.org/10.1519/JSC.0b013e3182541d2e.
Article
Google Scholar
Borg E, Borg G. A comparison of AME and CR100 for scaling perceived exertion. Acta Psychol. 2002;109(2):157–75.
Article
Google Scholar
McLaren SJ, Smith A, Spears IR, Weston M. A detailed quantification of differential ratings of perceived exertion during team-sport training. J Sci Med Sport. 2017;20(3):290–5 doi:https://doi.org/10.1016/j.jsams.2016.06.011.
Article
Google Scholar
Vanrenterghem J, Nedergaard NJ, Robinson MA, Drust B. Training load monitoring in team sports: a novel framework separating physiological and biomechanical load-adaptation pathways. Sports Med. 2017;47(11):2135–42. https://doi.org/10.1007/s40279-017-0714-2.
Article
PubMed
Google Scholar
McLaren SJ, Graham M, Spears IR, Weston M. The sensitivity of differential ratings of perceived exertion as measures of internal load. Int J Sports Physiol Perform. 2016;11(3):404–6.
Article
Google Scholar
Carey DL, Blanch P, Ong K-L, Crossley KM, Crow J, Morris ME. Training loads and injury risk in Australian football—differing acute: chronic workload ratios influence match injury risk. Br J Sports Med. 2016;51(16):1215–20. https://doi.org/10.1136/bjsports-2016-096309.
Article
PubMed
PubMed Central
Google Scholar
Lolli L, Batterham AM, Hawkins R, Kelly DM, Strudwick AJ, Thorpe R, et al. Mathematical coupling causes spurious correlation within the conventional acute-to-chronic workload ratio calculations. Br J Sports Med. 2017. https://doi.org/10.1136/bjsports-2017-098110.
Menaspà P. Are rolling averages a good way to assess training load for injury prevention? Br J Sports Med. 2017;51(7):618–9. https://doi.org/10.1136/bjsports-2016-096131.
Article
PubMed
Google Scholar
Williams S, West S, Cross MJ, Stokes KA. Better way to determine the acute:chronic workload ratio? Br J Sports Med. 2016;51(3):209. https://doi.org/10.1136/bjsports-2016-096589.
Article
PubMed
Google Scholar
Murray NB, Gabbett TJ, Townshend AD, Blanch P. Calculating acute:chronic workload ratios using exponentially weighted moving averages provides a more sensitive indicator of injury likelihood than rolling averages. Br J Sports Med. 2016;51(9):749. https://doi.org/10.1136/bjsports-2016-097152.
Article
PubMed
Google Scholar
Williams S, West S, Howells D, Kemp SPT, Flatt AA, Stokes K. Modelling the HRV response to training loads in elite rugby sevens players. J Sports Sci Med. 2018;17(3):402–8.
PubMed
PubMed Central
Google Scholar
Delaney JA, McKay BA, Thornton HR, Murray A, Duthie GM. Training efficiency and athlete wellness in collegiate female soccer. Sports Perform Sci Rep. 2018;1(19):1–3.
Google Scholar
Coleman J. The best strategic leaders balance agility and consistency. Harvard Business Review; 2017.
Google Scholar
Isenberg D. The tactics of strategic opportunism. Harvard Business Review; 1987.
Google Scholar
Thorpe RT, Atkinson G, Drust B, Gregson W. Monitoring fatigue status in elite team sport athletes: implications for practice. Int J Sports Physiol Perform. 2017:1–25. https://doi.org/10.1123/ijspp.2016-0434.