Comparative Analysis of Machine Learning Techniques for Predicting IPL Scores

Predicting cricket scores in dynamic formats, especially in India's Premier League (IPL), is a complex challenge for sports analysis. This study uses mechanical learning techniques to predict IPL reviews based on matching data such as over, run, and gate. Models such as linear regression, decision trees, random forests, and AdaBoost are implemented and evaluated with the help of metrics such as Mean absolute error (MAE) and root mean squared error (RMSE) .

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-14
DOI
https://doi.org/10.5281/zenodo.14871884
Primary Topic
Catalysis for Biomass Conversion
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparative Analysis of Machine Learning Techniques for Predicting IPL Scores

Zenodo (CERN European Organization for Nuclear Research)
Catalysis for Biomass Conversion
article

Comparative Analysis of Machine Learning Techniques for Predicting IPL Scores

article en

Abstract

Predicting cricket scores in dynamic formats, especially in India's Premier League (IPL), is a complex challenge for sports analysis. This study uses mechanical learning techniques to predict IPL reviews based on matching data such as over, run, and gate. Models such as linear regression, decision trees, random forests, and AdaBoost are implemented and evaluated with the help of metrics such as Mean absolute error (MAE) and root mean squared error (RMSE) .

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 54%
Catalysis for Biomass Conversion
DOIOpen Access PDFOpenAlex
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Comparative Analysis of Machine Learning Techniques for Predicting IPL Scores · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS