Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics
With an emphasis on the upcoming ICC Champions Trophy 2025, which will be staged in Pakistan, our research paper examines the complex relationship between weather and cricket. Correct forecasting of the weather is crucial for outdoor sporting events to avoid cancellations and guarantee peak athlete...
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| Format: | Article |
| Language: | English |
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Institute of Business Management
2025-07-01
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| Series: | Pakistan Journal of Engineering Technology & Science |
| Subjects: | |
| Online Access: | https://journals.iobm.edu.pk/index.php/pjets/article/view/1227 |
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| author | Syeda Faiza Nasim Umm-e-Kulsoom Syeda Alishba Fatima Salka Naushad |
| author_facet | Syeda Faiza Nasim Umm-e-Kulsoom Syeda Alishba Fatima Salka Naushad |
| author_sort | Syeda Faiza Nasim |
| collection | DOAJ |
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With an emphasis on the upcoming ICC Champions Trophy 2025, which will be staged in Pakistan, our research paper examines the complex relationship between weather and cricket. Correct forecasting of the weather is crucial for outdoor sporting events to avoid cancellations and guarantee peak athlete performance since climate change has an increasing impact on weather patterns. Pakistan's varied terrain, which encompasses plains, hilly areas, and coastal regions, contributes to the country's notable variety in climate. It is vital for event planners to comprehend local climate dynamics since this variability causes unpredictable weather patterns, such as monsoon rains, intense heat waves, and droughts. Our approach comprised combining real-time analytics with historical weather data from Open-Meteo, as well as using Python tools and the Machine Learning algorithm to predict rain during a game. Power BI is used to show the results, giving a thorough understanding of the climatic trends in three important cities: Karachi, Lahore, and Rawalpindi. The research highlights the significance of data-driven decision-making for event planners, as it empowers them to execute efficient backup plans The main objective of this research is to improve the sports environment for both players and spectators while tackling the urgent problems caused by climate variability.
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| format | Article |
| id | doaj-art-3c4193e321844592b7f1c9d4584379f3 |
| institution | Kabale University |
| issn | 2222-9930 2224-2333 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Institute of Business Management |
| record_format | Article |
| series | Pakistan Journal of Engineering Technology & Science |
| spelling | doaj-art-3c4193e321844592b7f1c9d4584379f32025-08-26T03:35:14ZengInstitute of Business ManagementPakistan Journal of Engineering Technology & Science2222-99302224-23332025-07-0113110.22555/pjets.v13i1.1227Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data AnalyticsSyeda Faiza NasimUmm-e-KulsoomSyeda Alishba FatimaSalka Naushad With an emphasis on the upcoming ICC Champions Trophy 2025, which will be staged in Pakistan, our research paper examines the complex relationship between weather and cricket. Correct forecasting of the weather is crucial for outdoor sporting events to avoid cancellations and guarantee peak athlete performance since climate change has an increasing impact on weather patterns. Pakistan's varied terrain, which encompasses plains, hilly areas, and coastal regions, contributes to the country's notable variety in climate. It is vital for event planners to comprehend local climate dynamics since this variability causes unpredictable weather patterns, such as monsoon rains, intense heat waves, and droughts. Our approach comprised combining real-time analytics with historical weather data from Open-Meteo, as well as using Python tools and the Machine Learning algorithm to predict rain during a game. Power BI is used to show the results, giving a thorough understanding of the climatic trends in three important cities: Karachi, Lahore, and Rawalpindi. The research highlights the significance of data-driven decision-making for event planners, as it empowers them to execute efficient backup plans The main objective of this research is to improve the sports environment for both players and spectators while tackling the urgent problems caused by climate variability. https://journals.iobm.edu.pk/index.php/pjets/article/view/1227Climatic Variability in Pakistan, Data Analytics, Machine Learning, Open-Meteo Stat, Rain Prediction |
| spellingShingle | Syeda Faiza Nasim Umm-e-Kulsoom Syeda Alishba Fatima Salka Naushad Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics Pakistan Journal of Engineering Technology & Science Climatic Variability in Pakistan, Data Analytics, Machine Learning, Open-Meteo Stat, Rain Prediction |
| title | Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics |
| title_full | Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics |
| title_fullStr | Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics |
| title_full_unstemmed | Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics |
| title_short | Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics |
| title_sort | predicting weather disruptions for the icc champions trophy 2025 in pakistan using machine learning and data analytics |
| topic | Climatic Variability in Pakistan, Data Analytics, Machine Learning, Open-Meteo Stat, Rain Prediction |
| url | https://journals.iobm.edu.pk/index.php/pjets/article/view/1227 |
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