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Cricket ODI World Cup 2023 Prediction Using TOPSIS Methodology
  • +1
  • Broti Mondal Bonya,
  • Bushra Jamil,
  • Shawon Shikdar,
  • Sharmin Sultana
Broti Mondal Bonya
Master of Development and Policy Studies, Khulna University
Bushra Jamil
Master of Development and Policy Studies, Khulna University

Corresponding Author:[email protected]

Author Profile
Shawon Shikdar
Department of Computer Science and Engineering, North Western University
Sharmin Sultana
Master of Development and Policy Studies, Khulna University


Current research uses TOPSIS to evaluate 14 Cricket World Cup 2023 teams. Data from the Espn Cricinfo website was used in this analysis. A comprehensive set of criteria (P1 to P11) was used to evaluate each squad, encompassing various game aspects. A numerical labeling system (A1 to A14) and parameter system (P1 to P11) were used to idenMfy team names and qualiMes more efficiently. The research calculates the normalized matrix and weighted matrix, then finds the best and worst values using TOPSIS. A normalized matrix creates a consistent and uniform framework for evaluaMng and comparing factors, ensuring imparMality and jusMficaMon. In contrast, the weighted matrix integrates each criterion's proporMonal importance into the evaluaMon process. For each criterion, the ideal best and ideal worst values indicate the best and worst performance. The TOPSIS analysis placed Australia first, Bangladesh second, and New Zealand third. In fourth and fiXh place were India and Sri Lanka. Afghanistan, West Indies, England, South Africa, and Pakistan rated sixth to tenth. Nepal was tenth, Ireland, the US, and Zimbabwe fourteenth.To understand team performance, the TOPSIS technique must be accepted. It is important to acknowledge that the Cricket World Cup 2023 results may vary owing to many factors. This study provides a systematic and comprehensive approach to team performance, making it a useful resource for cricket fans and experts interested in the event's competitive dynamics.
24 Feb 2024Submitted to TechRxiv
27 Feb 2024Published in TechRxiv