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References

Designed by PhD statisticians and computer scientists, MatchMind is built on academic rigor and published research.

  • Angelini, G., Candila, V., & De Angelis, L. (2022). Weighted Elo rating for tennis match predictions. European Journal of Operational Research, 297(1), 120-132.

  • Clarke, S. R. (1988). Dynamic programming in one-day cricket-optimal scoring rates. Journal of the Operational Research Society, 39, 331-337.

  • Dewart, N., & Gillard, J. (2019). Using Bradley–Terry models to analyse test match cricket. IMA Journal of Management Mathematics, 30(2), 187-207.

  • Lalwani, A., Saraiya, A., Singh, A., Jain, A., & Dash, T. (2022). Machine learning in sports: A case study on using Explainable models for predicting outcomes of volleyball matches. arXiv preprint arXiv:2206.09258.

  • Maher, M. (2012, September). Stochastic modelling of sport. In 2012 Ninth International Conference on Quantitative Evaluation of Systems (pp. 207-208). IEEE.

  • Palayangoda, L. K., Senevirathne, H. W., & Manage, A. B. (2022). Modeling joint survival probabilities of runs scored and balls faced in limited overs cricket using copulas. Journal of Sports Analytics, 8(4), 277-289.

  • Sami, M., Taufiq, S., Agarwal, K., & Qureshi, R. (2021, December). An efficient rating system for players based on their position statistics. In 2021 15th International Conference on Open Source Systems and Technologies (ICOSST) (pp. 1-6). IEEE.

  • Sharma, S. K. (2013). A factor analysis approach in performance analysis of T-20 cricket. Journal of Reliability and Statistical Studies, 69-76.

  • Stern, S. E. (2016). The Duckworth-Lewis-Stern method: extending the Duckworth-Lewis methodology to deal with modern scoring rates. Journal of the Operational Research Society, 67(12), 1469-1480.

  • Veček, N., Črepinšek, M., Mernik, M., & Hrnčič, D. (2014, September). A comparison between different chess rating systems for ranking evolutionary algorithms. In 2014 Federated Conference on Computer Science and Information Systems (pp. 511-518). IEEE.

  • Yue, J. C., Chou, E. P., Hsieh, M. H., & Hsiao, L. C. (2022). A study of forecasting tennis matches via the Glicko model. Plos one, 17(4), e0266838.

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