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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
林澤慶
Lin, Tse-Ching |
| Keywords: | 技能評分系統
職業網球雙打
場地
Skill-rating System
Professional Tennis Doubles
Surfaces |
| 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. |
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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
國立政治大學
統計學系
108354015 |
| Source URI: | http://thesis.lib.nccu.edu.tw/record/#G0108354015 |
| Data Type: | thesis |
| DOI: | 10.6814/NCCU202101154 |
| Appears in Collections: | [統計學系] 學位論文
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| 401501.pdf | | 2084Kb | Adobe PDF2 | 79 | View/Open |
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