A change point approach to analysing the match activity profiles of team-sport athletes

References

• Al-Abood, S. A., Davids, K., & Bennett, S. J. (2001). Specificity of task constraints and effects of visual demonstrations and verbal instructions in directing learners’ search during skill acquisition. Journal of Motor Behavior, 33(3), 295–305.
   PubMed Web of Science ®Google Scholar
• Atchison, A., Berardi, C., Best, N., Stevens, E., & Linstead, E. (2017). A time series analysis of travistorrent builds: To everything there is a season (pp. 463). Buenos Aires: IEEE.
   Google Scholar
• Aughey, R. J. (2010). Australian football player work rate: Evidence of fatigue and pacing? International Journal of Sports Physiology and Performance, 5(3), 394–405.
   PubMed Web of Science ®Google Scholar
• Aughey, R. J. (2011). Increased high-intensity activity in elite Australian football finals matches. International Journal of Sports Physiology and Performance, 6(3), 367–379.
   PubMed Web of Science ®Google Scholar
• Corbett, D. M., Sweeting, A. J., & Robertson, S. (2017). Weak relationships between stint duration, physical and skilled match performance in Australian Football. Frontiers in Physiology, 8(820). doi:10.3389/fphys.2017.00820
   Google Scholar
• Coutts, A. J., & Duffield, R. (2010). Validity and reliability of GPS devices for measuring movement demands of team sports. Journal of Science and Medicine in Sport, 1, 133.
   Google Scholar
• Cryer, J. D., & Chan, K.-S. (2008). “Fundamental Concepts.” Chap. 2. InTime series analysis: With applications in R, 2nd ed, 16. New York: Springer.
   Google Scholar
• Cummins, C., Orr, R., O’Connor, H., & West, C. (2013). Global positioning systems (GPS) and microtechnology sensors in team sports: A systematic review. Sports Medicine (Auckland, N.Z.), 43(10), 1025–1042.
   PubMed Web of Science ®Google Scholar
• Delaney, J. A., Scott, T. J., Thornton, H. R., Bennett, K. J. M., Gay, D., Duthie, G. M., & Dascombe, B. J. (2015). Establishing duration-specific running intensities from match-play analysis in rugby league. International Journal of Sports Physiology and Performance, 10(6), 725–731.
   PubMed Web of Science ®Google Scholar
• Dillon, P. A., Kempton, T., Ryan, S., Hocking, J., & Coutts, A. (2017). Interchange rotation factors and player characteristics influence physical and technical performance in professional Australian rules football. Journal of Science and Medicine in Sport / Sports Medicine Australia, 21(3), 317–321.
   PubMed Web of Science ®Google Scholar
• Fransz, D. P., Huurnink, A., de Boode, V. A., Kingma, I., & van Dieën, J. H. (2016). Time series of ground reaction forces following a single leg drop jump landing in elite youth soccer players consist of four distinct phases. Gait & Posture, 50, 137–144.
   PubMed Web of Science ®Google Scholar
• Gréhaigne, J.-F., Godbout, P., & Bouthier, D. (2001). The teaching and learning of decision making in team sports. Quest, 53(1), 59–76.
   Web of Science ®Google Scholar
• Kelly, V. G., & Coutts, A. J. (2007). Planning and monitoring training loads during the competition phase in team sports. Strength and Conditioning Journal, 29(4), 32–37.
   Web of Science ®Google Scholar
• Killick, R., & Eckley, I. (2014). changepoint: An R package for changepoint analysis. Journal of Statistical Software, 58(3), 1–19.
   Web of Science ®Google Scholar
• Liaw, A., & Wiener, M. (2002). Classification and regression by randomforest. R News, 2(3), 18–22.
   Google Scholar
• Luteberget, L. S., Spencer, M., & Gilgien, M. (2018). Validity of the Catapult ClearSky T6 local positioning system for team sports specific drills, in indoor conditions. Frontiers in Physiology, 9, 115.
   PubMed Web of Science ®Google Scholar
• Ofoghi, B., Zeleznikow, J., MacMahon, C., & Raab, M. (2013). Data mining in elite sports: A review and a framework. Measurement in Physical Education and Exercise Science, 17(3), 171–186.
   Google Scholar
• Piotr, F., & Haeran, C. (2014). Multiple change-point detection for high-dimensional time series via sparsified binary segmentation. Journal of the Royal Statistical Society. Series B, Statistical Methodology, 77(2), 475–507.
   Web of Science ®Google Scholar
• Ryan, S. J., Coutts, A. J., Hocking, J., & Kempton, T. (2017). Factors affecting match running performance in professional australian football. International Journal of Sports Physiology and Performance, 1(19), 1–19.
   Google Scholar
• Sueur, J., Aubin, T., & Simonis, C. (2008). Seewave, a free modular tool for sound analysis and synthesis. Bioacoustics, 18(2), 213-226.
   Web of Science ®Google Scholar
• Sullivan, C., Bilsborough, J. C., Cianciosi, M., Hocking, J., Cordy, J. T., & Coutts, A. J. (2014). Factors affecting match performance in professional Australian football. International Journal of Sports Physiology and Performance, 9(3), 561–566.
   PubMed Web of Science ®Google Scholar
• Sweeting, A., Cormack, S. J., Morgan, S., & Aughey, R. (2017). When is a sprint a sprint? A review of the analysis of team-sport athlete activity profile. Frontiers in Physiology, 8, 432.
   Google Scholar
• Tanaka, K. (2017). Time series analysis: Nonstationary and noninvertible distribution theory (2nd edn ed.). Hoboken, NJ: John Wiley & Sons, Inc..
   Google Scholar
• Varley, M. C., Fairweather, I. H., & Aughey, R. J. (2012). Validity and reliability of GPS for measuring instantaneous velocity during acceleration, deceleration, and constant motion. Journal of Sports Sciences, 30(2), 121–127.
   PubMed Web of Science ®Google Scholar
• Woods, C. T., Robertson, S., & Collier, N. F. (2017). Evolution of game-play in the Australian Football League from 2001 to 2015. Journal of Sports Sciences, 35(19), 1879–1887.
   PubMed Web of Science ®Google Scholar
• Wundersitz, D., Josman, C., Gupta, R., Netto, K., Gastin, P. B., & Robertson, S. (2015). Classification of team sport activities using a single wearable tracking device. Journal of Biomechanics, 48(15), 3875–3881.
   Web of Science ®Google Scholar