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Wu, G. (2021). Monitoring system of key technical features of male tennis players based on internet of things security technology. Wireless Communications and Mobile Computing.Search in Google Scholar
Zhang, S., & Mao, H. (2021). Optimization analysis of tennis players’ physical fitness index based on data mining and mobile computing. Wireless Communications and Mobile Computing, 2021(11), 1-11.Search in Google Scholar
Tang, K., & Huo, L. J. (2021). Optimizing synchronization of tennis professional league live broadcast based on wireless network planning. Mobile Information Systems, 2021(7), 1-9.Search in Google Scholar
Hubacek, O., & Sir, G. (2023). Beating the market with a bad predictive model. International journal of forecasting.Search in Google Scholar
Dai, Y. K. S. (2021). The wisdom of the crowd and prediction markets. Journal of Econometrics, 222(1Pta2).Search in Google Scholar
Garrett S., B., Patrick, W., Franco M., I., Stefan, K., Tom, H., & Paula, D., et al. (2023). The trade secret taboo: open science methods are required to improve prediction models in sports medicine and performance. Sports medicine(10), 53.Search in Google Scholar
Flavell, J. C., Beebe, N. B., Buckley, J. G., Harris, J. M., Scally, A. J., & Bennett, S. J., et al. (2017). Performance in prediction motion: the effects of colliding targets and no influence of sports participation. Perception(2), 46.Search in Google Scholar
Holt, A. C., Siegel, R., Ball, K., Hopkins, W. G., & Aughey, R. (2022). Prediction of 2000‐m on‐water rowing performance with measures derived from instrumented boats. Scandinavian journal of medicine & science in sports.(4), 32.Search in Google Scholar
Dietl, H. M. N. C. (2017). Momentum in tennis: controlling the match. International journal of sport psychology, 48(4).Search in Google Scholar
Ioannis, N., Vasilis, P., & Sotiris, D. (2021). Bayesian models for prediction of the set-difference in volleyball. IMA Journal of Management Mathematics(4), 4.Search in Google Scholar
David, F., & Mchale, I. G. (2019). Using statistics to detect match fixing in sport. IMA Journal of Management Mathematics(4), 4.Search in Google Scholar
Filipcic, A., Leskosek, B., Crespo, M., & Filipcic, T. (2021). Matchplay characteristics and performance indicators of male junior and entry professional tennis players:. International Journal of Sports Science & Coaching, 16(3), 768-776.Search in Google Scholar
Alejandro Sánchez-Pay, José Antonio Ortega-Soto, & Bernardino J. Sánchez-Alcaraz. (2021). Notational analysis in female grand slam tennis competitions. Kinesiology, 53(1), 154-161.Search in Google Scholar
Filipcic, A., Leskosek, B., & Filipcic, T. (2017). Split-step timing of professional and junior tennis players. Journal of Human Kinetics, 55(1), 97-105.Search in Google Scholar
Song, K., Shi, J., Slowinski, R., Artalejo, J., Billaut, J. C., & Dyson, R., et al. (2020). A gamma process based in-play prediction model for national basketball association games. European Journal of Operational Research, 283(2).Search in Google Scholar
Brown, A., & Yang, F. (2018). The wisdom of large and small crowds: evidence from repeated natural experiments in sports betting. International Journal of Forecasting, 35.Search in Google Scholar