Evaluating the effectiveness of different player rating systems in predicting the results of professional snooker matches

计算机科学 优势和劣势 计量经济学 运筹学 人工智能 机器学习 会计 心理学 数学 经济 社会心理学
作者
James A.P. Collingwood,M. B. Wright,Roger J. Brooks
出处
期刊:European Journal of Operational Research [Elsevier]
卷期号:296 (3): 1025-1035 被引量:4
标识
DOI:10.1016/j.ejor.2021.04.056
摘要

This paper is the first to consider different methods for rating professional snooker players based on their past performance. The official World Rankings (based on prize money earned) and a player's win percentage are considered, along with paired comparison approaches in the form of Bradley-Terry and Elo models. The models are assessed through their ability to predict the results of subsequent matches, with relatively little to choose between them. Subsets of matches are then analysed to identify relative strengths and weaknesses of the models and potential improvements. The models tended to under-estimate the performance of ‘new’ players and this is the main limitation of using the World Rankings to predict performance. Accounting for the strength of opposition faced by the highest-ranked players is shown to be relevant; although this is less true for lower-ranked players. Models based on two years of results out-perform those based on a single year but there is some indication that accounting for a recent improvement in form may be beneficial.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
lydy1993完成签到,获得积分10
1秒前
2秒前
滴滴哒哒完成签到 ,获得积分10
2秒前
SciGPT应助波波玛奇朵采纳,获得10
4秒前
戏言121完成签到,获得积分10
4秒前
迷人的映雁完成签到,获得积分10
5秒前
5秒前
美丽的之双完成签到,获得积分10
6秒前
阿会完成签到,获得积分10
6秒前
wqm完成签到,获得积分10
7秒前
戏言121发布了新的文献求助10
8秒前
8秒前
9秒前
优雅的流沙完成签到 ,获得积分10
10秒前
猫的海完成签到,获得积分10
10秒前
10秒前
Eason Liu完成签到,获得积分0
11秒前
Wendy1204完成签到,获得积分20
11秒前
Hello应助654采纳,获得10
11秒前
咩咩羊完成签到,获得积分10
11秒前
15秒前
lianqing完成签到,获得积分10
15秒前
汉堡包应助科研通管家采纳,获得10
15秒前
领导范儿应助科研通管家采纳,获得10
16秒前
RC_Wang应助科研通管家采纳,获得10
16秒前
科研通AI5应助科研通管家采纳,获得10
16秒前
所所应助科研通管家采纳,获得10
16秒前
FashionBoy应助科研通管家采纳,获得10
16秒前
赘婿应助科研通管家采纳,获得10
16秒前
hh应助科研通管家采纳,获得10
16秒前
所所应助科研通管家采纳,获得10
16秒前
丘比特应助科研通管家采纳,获得10
16秒前
搜集达人应助科研通管家采纳,获得30
16秒前
16秒前
Leif应助科研通管家采纳,获得20
16秒前
16秒前
17秒前
17秒前
18秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
Luis Lacasa - Sobre esto y aquello 700
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527990
求助须知:如何正确求助?哪些是违规求助? 3108173
关于积分的说明 9287913
捐赠科研通 2805882
什么是DOI,文献DOI怎么找? 1540119
邀请新用户注册赠送积分活动 716941
科研通“疑难数据库(出版商)”最低求助积分说明 709824