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Title: 網球雙打選手的技能評分模型探討
A Study on Skill-Rating Models for Doubles Tennis Players
Authors: 林澤慶
Lin, Tse-Ching
Contributors: 翁久幸
Weng, Chiu-Hsing
Lin, Tse-Ching
Keywords: 技能評分系統
Skill-rating System
Professional Tennis Doubles
Date: 2021
Issue Date: 2021-09-02 15:41:20 (UTC+8)
Abstract: 技能評分系統是根據參賽隊伍的比賽戰績與其他相關資料,以評估隊伍實力與預測獲勝機率的一套計算方法。以職業網球比賽為例,選手的實力發揮往往受到比賽場地因素的影響,近年有學者針對網球單打提出一個將場地因素納入考量的模型,研究結果顯示納入場地因素的模型可以更準確地預測獲勝機率。本論文參考文獻中的相關討論,將此模型推廣至職業網球雙打比賽。本研究結果顯示納入場地因素於雙打比賽可以提高預測準確率,此外更新技能變數的變異程度也可提高預測準確率。
A skill-rating system is a system that evaluates players’ skills and predict the winning probability based on competition records and relevant information. Take Association of Tennis Professionals as an example. Player’s performance is often affected by the surfaces. In recent years, some researchers have proposed models that take surfaces into consideration for tennis singles. Research results show that models incorporating surfaces can more accurately predict the probability of winning. The present thesis aims to extend this model to tennis doubles matches. The experimental results show that the inclusion of surfaces in doubles matches can improve the accuracy of prediction.
Reference: Bradley, R. A. and Terry, M. E. (1952). Rank analysis of incomplete block designs: I. the method of paired comparisons. Biometrika, 39(3/4):324–345.
Elo, A. E. (1978). The rating of chessplayers, past and present. Arco Pub., New York.
Glickman, M. E. (1999). Parameter estimation in large dynamic paired comparison experiments. Journal of the Royal Statistical Society: Series C (Applied Statistics), 48(3):377–394.
Glickman, M. E., Hennessy, J., and Bent, A. (2018). A comparison of rating systems for competitive women’s beach volleyball. Statistica ApplicataItalian Journal of Applied Statistics, 30(2):233–254.
Ingram, M. (2021). How to extend elo: a bayesian perspective. Journal of Quantitative Analysis in Sports.
Kovalchik, S. (2020). Extension of the elo rating system to margin of victory. International Journal of Forecasting, 36(4):1329–1341.
Nelder, J. A. and Mead, R. (1965). A simplex method for function minimization. The Computer Journal, 7(4):308–313.
Thurstone, L. (1927). A law of comparative judgment. Psychological Review, 34(4):273–286.
Weng, R. C. and Lin, C.-J. (2011). A bayesian approximation method for online ranking. Journal of Machine Learning Research, 12(9):267–300.
Description: 碩士
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Data Type: thesis
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