Data-Driven Probabilistic S for Batsman Performance Prediction in a Cricket Match  

作　　者：Fawad Nasim Muhammad Adnan Yousaf Sohail Masood Arfan Jaffar Muhammad Rashid 

机构地区：[1]Superior University,Lahore,54000,Pakistan [2]Intelligent Data Visual Computing Research(IDVCR),Lahore,Pakistan [3]National University of Technology,Islamabad,44000,Pakistan

出　　处：《Intelligent Automation & Soft Computing》2023年第6期2865-2877,共13页智能自动化与软计算（英文）

摘　　要：Batsmen are the backbone of any cricket team and their selection is very critical to the team’s success.A good batsman not only scores run but also provides stability to the team’s innings.The most important factor in selecting a batsman is their ability to score runs.It is a generally accepted notion that the future performance of a batsman can be predicted by observing and analyzing their past record.This hypothesis is based on the fact that a player’s batting aver-age is generally considered to be a good indicator of their future performance.We proposed a data-driven probabilistic system for batsman performance prediction in the game of cricket.It captures the dependencies between the runs scored by a batsman in consecutive balls.The system is evaluated using a dataset extracted from the Cricinfo website.The system is based on a Hidden Markov model(HMM).HMM is used to generate the prediction model to foresee players’upcoming performances.The first-order Markov chain assumes that the probabil-ity of a batsman scoring runs in the next ball is only dependent on how many runs he scored in the current ball.We use a data-driven approach to learn the para-meters of the HMM from data.A probabilistic matrix is made that predicts what scores the batter can do on the upcoming balls.The results show that the system can accurately predict the runs scored by a batsman in a ball.

关 键 词：Probabilistic matrix hidden markov model batsman performance prediction 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]