Including the Past: Performance Modeling Using a Preload Concept by Means of the Fitness-Fatigue Model

Banister, E., Calvert, T., Savage, M., & Bach, T. (1975). A systems model of training for athletic performance. Aust J Sports Med, 7(3), 57–61.Search in Google Scholar

Busso, T. (2003). Variable dose-response relationship between exercise training and performance. Medicine and science in sports and exercise, 35(7), 1188–1195.10.1249/01.MSS.0000074465.13621.3712840641Search in Google Scholar

Busso, T., Candau, R., & Lacour, J.-R. (1994). Fatigue and fitness modelled from the effects of training on performance. European journal of applied physiology and occupational physiology, 69(1), 50–54.10.1007/BF008679277957156Search in Google Scholar

Busso, T., Carasso, C., & Lacour, J.-R. (1991). Adequacy of a systems structure in the modeling of training effects on performance. Journal of applied physiology, 71(5), 2044–9.10.1152/jappl.1991.71.5.20441761506Search in Google Scholar

Busso, T., Denis, C., Bonnefoy, R., Geyssant, A., & Lacour, J.-R. (1997). Modeling of adaptations to physical training by using a recursive least squares algorithm. Journal of applied physiology, 82(5), 1685–1693.10.1152/jappl.1997.82.5.16859134920Search in Google Scholar

Busso, T., & Thomas, L. (2006). Using mathematical modeling in training planning. International journal of sports physiology and performance, 1(4), 400–405.10.1123/ijspp.1.4.40019124896Search in Google Scholar

Chalencon, S., Pichot, V., Roche, F., Lacour, J.-R., Garet, M., Connes, P., ... Busso, T. (2015). Modeling of performance and ans activity for predicting future responses to training. European journal of applied physiology, 115(3), 589–596.10.1007/s00421-014-3035-225359446Search in Google Scholar

Chiu, L. Z., & Barnes, J. L. (2003). The fitness-fatigue model revisited: Implications for planning short-and long-term training. Strength & Conditioning Journal, 25(6), 42–51.10.1519/00126548-200312000-00007Search in Google Scholar

Clarke, D. C., & Skiba, P. F. (2013). Rationale and resources for teaching the mathematical modeling of athletic training and performance. Advances in physiology education, 37(2), 134–152.10.1152/advan.00078.201123728131Search in Google Scholar

Hellard, P., Avalos, M., Lacoste, L., Barale, F., Chatard, J.-C., & Millet, G. P. (2006). Assessing the limitations of the banister model in monitoring training. Journal of sports sciences, 24(05), 509–520.10.1080/02640410500244697197489916608765Search in Google Scholar

Hellard, P., Avalos, M., Millet, G., Lacoste, L., Barale, F., & Chatard, J.-C. (2005). Modeling the residual effects and threshold saturation of training: a case study of olympic swimmers. Journal of Strength and Conditioning Research, 19(1), 67.10.1519/14853.1535282815705048Search in Google Scholar

Kolossa, D., Bin Azhar, M., Rasche, C., Endler, S., Hanakam, F., Ferrauti, A., ... Pfeiffer, M. (2017). Performance estimation using the fitness-fatigue model with kalman filter feedback. International Journal of Computer Science in Sport, 16(2), 117–129.10.1515/ijcss-2017-0010Search in Google Scholar

Ludwig, M., & Asteroth, A. (2016). Predicting performance from outdoor cycling training with the fitness-fatigue model. In A. Artiga Gonzalez, R. Bertschinger, T. Dahmen, M. Gratkowski, S. Wolf, & D. Saupe (Eds.), Proceedings dvs-workshop modelling in endurance sports, University of Konstanz, Sept. 9–11, 2016 (pp. 3–6). KOPS – The Institutional Repository of the University of Konstanz.Search in Google Scholar

Ludwig, M., Hoffmann, K., Endler, S., Asteroth, A., & Wiemeyer, J. (2018). Measurement, prediction, and control of individual heart rate responses to exercise - basics and options for wearable devices. Front. Physiol., 9(778).10.3389/fphys.2018.00778602688429988588Search in Google Scholar

Passfield, L., & Hopker, J. G. (2016). A mine of information: can sports analytics provide wisdom from your data? International journal of sports physiology and performance, 1–17.Search in Google Scholar

Perl, J. (2001). Perpot: A metamodel for simulation of load performance interaction. European Journal of Sport Science, 1(2), 1–13.10.1080/17461390100071202Search in Google Scholar

Perl, J., & Pfeiffer, M. (2011). Perpot domo: Antagonistic meta-model processing two concurrent load flows. International Journal of Computer Science in Sport (International Association of Computer Science in Sport), 10(2).Search in Google Scholar

Pfeiffer, M. (2008). Modeling the relationship between training and performance-a comparison of two antagonistic concepts. International journal of computer science in sport, 7(2), 13–32.Search in Google Scholar

Rasche, C., & Pfeiffer, M. (2018). Training. In A. Baca & J. Perl (Eds.), Modelling and simulation in sport and exercise (1st ed., p. 187—207). Routledge.10.4324/9781315163291-10Search in Google Scholar

Taha, T., & Thomas, S. G. (2003). Systems modelling of the relationship between training and performance. Sports Medicine, 33(14), 1061–1073.10.2165/00007256-200333140-0000314599233Search in Google Scholar

Thomas, L., Mujika, I., & Busso, T. (2008). A model study of optimal training reduction during pre-event taper in elite swimmers. Journal of sports sciences, 26(6), 643–652.10.1080/0264041070171678218344135Search in Google Scholar

Thomas, L., Mujika, I., & Busso, T. (2009). Computer simulations assessing the potential performance benefit of a final increase in training during pre-event taper. The Journal of Strength & Conditioning Research, 23(6), 1729–1736.10.1519/JSC.0b013e3181b3dfa119675490Search in Google Scholar

Turner, J. D., Mazzoleni, M. J., Little, J. A., Sequeira, D., & Mann, B. P. (2017). A nonlinear model for the characterization and optimization of athletic training and performance. Biomedical Human Kinetics, 9(1), 82–93.10.1515/bhk-2017-0013Search in Google Scholar

Wood, R. E., Hayter, S., Rowbottom, D., & Stewart, I. (2005). Applying a mathematical model to training adaptation in a distance runner. European journal of applied physiology, 94(3), 310–316.10.1007/s00421-005-1319-215765236Search in Google Scholar