Asia Cup 2025: A Structured T20 Match-Level Dataset and Exploratory Analysis for Cricket Analytics
Kousar Raza, Faizan Ali
TL;DR
The paper introduces the Asia Cup 2025 Match-Level Dataset, a structured, open-access collection of 19 T20 matches with 61 attributes to enable reproducible cricket analytics. It details dataset construction, variable categories, and sources, and demonstrates value through exploratory analyses on toss impact, team batting performance, and boundary patterns. By releasing the dataset on Zenodo under CC-BY 4.0 and providing an open-access EDA repository, the work provides a practical benchmark for predictive modeling, strategic decision-making, and cross-study comparability in cricket analytics. This open-data approach supports reproducibility and accelerates research in sports analytics and data-driven cricket insights.
Abstract
This paper presents a structured and comprehensive dataset corresponding to the 2025 Asia Cup T20 cricket tournament, designed to facilitate data-driven research in sports analytics. The dataset comprises records from all 19 matches of the tournament and includes 61 variables covering team scores, wickets, powerplay statistics, boundary counts, toss decisions, venues, and player-specific highlights. To demonstrate its analytical value, we conduct an exploratory data analysis focusing on team performance indicators, boundary distributions, and scoring patterns. The dataset is publicly released through Zenodo under a CC-BY 4.0 license to support reproducibility and further research in cricket analytics, predictive modeling, and strategic decision-making. This work contributes an open, machine-readable benchmark dataset for advancing cricket analytics research.