An Analysis of Best Player Selection Key Performance Indicator: The Case of Indian Premier League (IPL)

Khandelwal, Mayank; Prakash, Jayant; Pradhan, Tribikram

doi:10.1007/978-3-319-23036-8_16

Cited by 1 publication

(1 citation statement)

References 4 publications

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“…Mayank et al [12] devised the notion of Most Valuable Player (MVP) and found that it made a significant impact on the match results. He used Genetic Algorithms to create a recommendation system for the team captain in choosing his players and their positions.…”

Section: B Machine Learning In Cricket Analyticsmentioning

confidence: 99%

Analysing Long Short Term Memory Models for Cricket Match Outcome Prediction

Chakwate¹

2020

IJRASET

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As the technology advances, an ample amount of data is collected in sports with the help of advanced sensors. Sports Analytics is the study of this data to provide a constructive advantage to the team and its players. The game of international cricket is popular all across the globe. Recently, various machine learning techniques have been used to analyse the cricket match data and predict the match outcome as win or lose. Generally these models make use of the overall match level statistics such as teams, venue, average run rate, win margin, etc to predict the match results before the beginning of the match. However, very few works provide insights based on the ball-by-ball level statistics. Here we propose a novel Recurrent Neural Network model which can predict the win probability of a match at regular intervals given the ball-by-ball statistics. The Long Short Term Memory (LSTM) Model takes as input the ball wise features as well as the match level details available from the training dataset. It gives a prediction of winning the match at any time stamp during the match. This level of insight will help the team to predict the probability of them winning the match after every ball and help them determine the critical in-game changes they should make in their game strategies. 1

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Section: B Machine Learning In Cricket Analyticsmentioning

confidence: 99%

Analysing Long Short Term Memory Models for Cricket Match Outcome Prediction

Chakwate¹

2020

IJRASET

View full text Add to dashboard Cite

show abstract

An Analysis of Best Player Selection Key Performance Indicator: The Case of Indian Premier League (IPL)

Cited by 1 publication

References 4 publications

Analysing Long Short Term Memory Models for Cricket Match Outcome Prediction

Analysing Long Short Term Memory Models for Cricket Match Outcome Prediction

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