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

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

Open Access
|Dec 2016

References

  1. Bartlett, J. D., O’Connor, F., Pitchford, N., Torres-Ronda, L., & Robertson, S. J. (2016). Relationships Between Internal and External Training Load in Team Sport Athletes: Evidence for an Individualised Approach. International Journal of Sports Physiology and Performance. doi: 10.1123/ijspp.2015-0791
  2. Borresen, J., & Lambert, M. I. (2008). Quantifying training load: a comparison of subjective and objective methods. International Journal of Sports Physiology and Performance, 3(1), 16.10.1123/ijspp.3.1.1619193951
  3. Boyd, L. J., Ball, K., & Aughey, R. J. (2011). The reliability of MinimaxX accelerometers for measuring physical activity in Australian football. International Journal of Sports Physiology and Performance, 6(3), 311-321.10.1123/ijspp.6.3.31121911857
  4. Clarke, N., Farthing, J. P., Norris, S. R., Arnold, B. E., & Lanovaz, J. L. (2013). Quantification of training load in Canadian football: application of session-RPE in collision-based team sports. The Journal of Strength & Conditioning Research, 27(8), 2198-2205.10.1519/JSC.0b013e31827e133423222076
  5. 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, 43(10), 1025-1042.10.1007/s40279-013-0069-223812857
  6. Edwards, S. (1993). High performance training and racing. The Heart Rate Monitor Book, pp. 113-123.
  7. Foster, C., Florhaug, J. A., Franklin, J., Gottschall, L., Hrovatin, L. A., Parker, S., . . . Dodge, C. (2001). A new approach to monitoring exercise training. The Journal of Strength & Conditioning Research, 15(1), 109-115.
  8. Gabbett, T. J. (2010). The development and application of an injury prediction model for noncontact, soft-tissue injuries in elite collision sport athletes. The Journal of Strength & Conditioning Research, 24(10), 2593-2603.10.1519/JSC.0b013e3181f19da420847703
  9. Gabbett, T. J., & Jenkins, D. G. (2011). Relationship between training load and injury in professional rugby league players. Journal of Science and Medicine in Sport, 14(3), 204-209.10.1016/j.jsams.2010.12.00221256078
  10. Gallo, T., Cormack, S., Gabbett, T., Williams, M., & Lorenzen, C. (2015). Characteristics impacting on session rating of perceived exertion training load in Australian footballers. Journal of Sports Sciences, 33(5), 467-475.10.1080/02640414.2014.94731125113820
  11. Gallo, T. F., Cormack, S. J., Gabbett, T. J., & Lorenzen, C. H. (2016). Pre-training perceived wellness impacts training output in Australian football players. Journal of Sports Sciences, 34(15), 1445-1451.10.1080/02640414.2015.111929526637525
  12. Gaudino, P., Iaia, F., Strudwick, A., Hawkins, R., Alberti, G., Atkinson, G., & Gregson, W. (2015). Factors Influencing Perception of Effort (Session-RPE) During Elite Soccer Training. International Journal of Sports Physiology and Performance, 10(7), 860-864.10.1123/ijspp.2014-051825671338
  13. Hawkins, D. M. (2004). The problem of overfitting. Journal of Chemical Information and Computer Sciences, 44(1), 1-12.10.1021/ci034247214741005
  14. Impellizzeri, F. M., Rampinini, E., Coutts, A. J., Sassi, A., & Marcora, S. M. (2004). Use of RPE-based training load in soccer. Medicine and Science in Sports and Exercise, 36(6), 1042-1047.10.1249/01.MSS.0000128199.23901.2F
  15. James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112). New York: Springer.10.1007/978-1-4614-7138-7
  16. Jennings, D., Cormack, S., Coutts, A. J., Boyd, L., & Aughey, R. J. (2010). The validity and reliability of GPS units for measuring distance in team sport specific running patterns. International Journal of Sports Physiology and Performance, 5(3), 328-341.10.1123/ijspp.5.3.32820861523
  17. Karatzoglou, A., Smola, A., Hornik, K., & Zeileis, A. (2004). kernlab - An S4 Package for Kernel Methods in R. Journal of Statistical Software, 11(9), 1-20.10.18637/jss.v011.i09
  18. Kelly, D. M., Strudwick, A. J., Atkinson, G., Drust, B., & Gregson, W. (2016). The within participant correlation between perception of effort and heart rate-based estimations of training load in elite soccer players. Journal of Sports Sciences, 34(14), 1328-1332.10.1080/02640414.2016.114266926852624
  19. Kuhn, M. (2008). Caret package. Journal of Statistical Software, 28(5).
  20. Kuhn, M., & Johnson, K. (2013). Applied predictive modeling: Springer.10.1007/978-1-4614-6849-3
  21. Kuhn, M., Weston, S., Coulter, N., & Quinlan, R. (2014). C50: C5. 0 decision trees and rulebased models. R package version 0.1. 0-21, URL http://CRAN.R-project.org/package_C.50.
  22. Liaw, A., & Wiener, M. (2002). Classification and Regression by randomForest. R News, 2(3), 18-22.
  23. Lovell, T. W., Sirotic, A. C., Impellizzeri, F. M., & Coutts, A. J. (2013). Factors affecting perception of effort (session rating of perceived exertion) during rugby league training. International Journal of Sports Physiology and Performance, 8(1), 62-69.10.1123/ijspp.8.1.6223302138
  24. Milborrow, S. (2012). earth: Multivariate Adaptive Regression Splines. R package version, 4(0).
  25. Nicolò, A., Marcora, S. M., & Sacchetti, M. (2015). Respiratory frequency is strongly associated with perceived exertion during time trials of different duration. Journal of Sports Sciences, 34(13), 1-8.
  26. R Core Team. (2014). R: A Language and Environment for Statistical Computing. Vienna, Austria.
  27. Rampinini, E., Alberti, G., Fiorenza, M., Riggio, M., Sassi, R., Borges, T. O., & Coutts, A. J. (2015). Accuracy of GPS devices for measuring high-intensity running in field-based team sports. International Journal of Sports Medicine, 36(1), 49-53.
  28. Ritchie, D., Hopkins, W., Buchheit, M., Cordy, J., & Bartlett, J. (2015). Quantification of Training and Competition Load Across a Season in an Elite Australian Football Club. International Journal of Sports Physiology and Performance, 11(4), 474-479.10.1123/ijspp.2015-029426355304
  29. Rogalski, B., Dawson, B., Heasman, J., & Gabbett, T. J. (2013). Training and game loads and injury risk in elite Australian footballers. Journal of Science and Medicine in Sport, 16(6), 499-503.10.1016/j.jsams.2012.12.00423333045
  30. Saw, A. E., Main, L. C., & Gastin, P. B. (2016). Monitoring the athlete training response: subjective self-reported measures trump commonly used objective measures: a systematic review. British Journal of Sports Medicine, 50, 281-291.10.1136/bjsports-2015-094758478970826423706
  31. Scott, B. R., Lockie, R. G., Knight, T. J., Clark, A. C., & Janse de Jonge, X. (2013). A comparison of methods to quantify the in-season training load of professional soccer players. International Journal of Sports Physiology and Performance, 8(2), 195-202.10.1123/ijspp.8.2.19523428492
  32. Varley, M. C., Fairweather, I. H., & Aughey1, Robert J. (2012). Validity and reliability of GPS for measuring instantaneous velocity during acceleration, deceleration, and constant motion. Journal of Sports Sciences, 30(2), 121-127.10.1080/02640414.2011.62794122122431
  33. Varma, S., & Simon, R. (2006). Bias in error estimation when using cross-validation for model selection. BMC Bioinformatics, 7(1), 91.10.1186/1471-2105-7-91139787316504092
  34. Venables, W. N., & Ripley, B. D. (2002). Modern Applied Statistics with S. New York: Springer.10.1007/978-0-387-21706-2
  35. Weihs, C., Ligges, U., Luebke, K., & Raabe, N. (2005). klaR Analyzing German Business Cycles Data Analysis and Decision Support (pp. 335-343). Berlin: Springer-Verlag.
Language: English
Page range: 64 - 77
Published on: Dec 17, 2016
Published by: International Association of Computer Science in Sport
In partnership with: Paradigm Publishing Services
Publication frequency: 2 issues per year

© 2016 D. L. Carey, K. Ong, M. E. Morris, J. Crow, K. M. Crossley, published by International Association of Computer Science in Sport
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.