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Sports Performance

A measure of the importance of moment for ball-strike counts in a baseball plate appearance

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Received 06 Nov 2023, Accepted 08 May 2024, Published online: 15 Jul 2024

References

  • Abt, G., Boreham, C., Davison, G., Jackson, R., Nevill, A., Wallace, E., & Williams, M. (2020). Power, precision, and sample size estimation in sport and exercise science research. Journal of Sports Sciences, 38(17), 1933–1935. https://doi.org/10.1080/02640414.2020.1776002
  • Bromley, J., Guyon, I., LeCun, Y., Säckinger, E., & Shah, R. (1993). Signature verification using a” siamese” time delay neural network. Advances in Neural Information Processing Systems, 6.
  • Bukiet, B., Harold, E. R., & Palacios, J. L. (1997). A Markov chain approach to baseball. Operations Research, 45(1), 14–23. https://doi.org/10.1287/opre.45.1.14
  • Cy Young Award Voting History. (2022). Cy young pitchers. Retrieved May 30, 2023, from https://cyyoungpitchers.com/voting-history/PaulSchale.(2020)
  • Doo, W., Kim, H., & Deng, Y. (2018). Modeling the probability of a batter/pitcher matchup event: A Bayesian approach. PLOS ONE, 13(10), e0204874. https://doi.org/10.1371/journal.pone.0204874
  • Fabian, W., & Daniel, M. (2021). Forecasting the outcomes of sports events: A review. European Journal of Sport Science, 21(7), 944–957. https://doi.org/10.1080/17461391.2020.1793002
  • Giles, B., Peeling, P., Kovalchik, S., & Reid, M. (2023). Differentiating movement styles in professional tennis: A machine learning and hierarchical clustering approach. European Journal of Sport Science, 23(1), 44–53. https://doi.org/10.1080/17461391.2021.2006800
  • Healey, G. (2015). Modeling the probability of a strikeout for a Batter/Pitcher matchup. IEEE Transactions on Knowledge and Data Engineering, 27(9), 2415–2423. https://doi.org/10.1109/TKDE.2015.2416735
  • Healey, G. (2016). Matchup models for the probability of a ground ball and a ground ball hit. Journal of Sports Analytics, 3(1), 21–35. https://doi.org/10.3233/jsa-160025
  • Hirotsu, N., & Wright, M. (2003). A Markov chain approach to optimal pinch hitting strategies in a designated hitter rule baseball game. Journal of the Operations Research Society of Japan, 46(3), 353–371. https://doi.org/10.15807/jorsj.46.353
  • James, B. (1981). The Bill James baseball abstract, 1981. Ballantine Books.
  • Kumar, G. (2013). Machine learning for soccer analytics. University of Leuven.
  • Morris, C. (1977). The most important points in tennis. Optimal Strategies in Sports, 131–140.
  • Mun, K., Cha, B., Lee, J., Kim, J., & Jo, H. (2023). CompeteNet: Siamese networks for predicting win-loss outcomes in baseball games. Proceedings - 2023 IEEE International Conference on Big Data and Smart Computing, BigComp 2023 (pp. 1–8). https://doi.org/10.1109/BigComp57234.2023.00010
  • Otremba, S. E. (2022). SmartPitch: Applied machine learning for professional baseball pitching strategy.
  • Shale, P. (2022). MLB Pitch Data 2015-2018. https://www.kaggle.com/datasets/pschale/mlb-pitch-data-20152018
  • Sidhu, G., & Caffo, B. (2014). Moneybarl: Exploiting pitcher decision-making using reinforcement learning. The Annals of Applied Statistics, 8(2). https://doi.org/10.1214/13-AOAS712
  • Silver, J. (2021). Baseball predictions and strategies using explainable AI.
  • Sim, M. K., & Choi, D. G. (2020). The winning probability of a game and the importance of points in tennis matches. Research Quarterly for Exercise and Sport, 91(3), 361–372. https://doi.org/10.1080/02701367.2019.1666203
  • Sophie, G., Gary, B., Nicholas, J. S., Will, A., & Adam, B. (2023). The effects of injury, contextual match factors and training load upon psychological wellbeing in English Premier League soccer players via season-long tracking. European Journal of Sport Science, 23(8), 1687–1695. https://doi.org/10.1080/17461391.2022.2125834
  • Soto-Valero, C., González-Castellanos, M., & Pérez-Morales, I. (2017). A predictive model for analysing the starting pitchers’ performance using time series classification methods. International Journal of Performance Analysis in Sport, 17(4), 492–509. https://doi.org/10.1080/24748668.2017.1354544

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