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README.md
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks](#supported-tasks)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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### Dataset Summary
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This dataset contains highly detailed information on each of the 51 matches in the UEFA Euro 2020 tournament composed and aggregated from 6 original csv files. Each row represents the information for each match and the columns constitute a wide range of variables on basic match information, referee information and statistics, match events in different phases of a match, team line-up and squad information, team statistics and player statistics on different areas of the game, and player-based pre-match information.
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## Citation
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Mikhail Zhilkin @cervus (2021). "UEFA Euro 2020." Hosted by [data.world]. Available at: “https://data.world/cervus/uefa-euro-2020".
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Data Processing](#data-processing)
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- [Supported Tasks](#supported-tasks)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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### Dataset Summary
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This dataset contains highly detailed information on each of the 51 matches in the UEFA Euro 2020 tournament composed and aggregated from 6 original csv files. Each row represents the information for each match and the columns constitute a wide range of variables on basic match information, referee information and statistics, match events in different phases of a match, team line-up and squad information, team statistics and player statistics on different areas of the game, and player-based pre-match information.
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### Data Processing
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Please see the 'uefa_euro2020_processing.py' file for detailed processing code and procedures.
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### Supported Tasks
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The dataset preserves most of the supported tasks of the original source data. The new structure of the data also enables performing other tasks especially in terms of investigating the relationships between different level (individual player, team, match, match event, etc.) by composing and aggregating the original data. Some examples include:
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- Extract, Visualize, and analyze statistics for players, teams, referees, and other participants within and across matches.
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## Citation
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Mikhail Zhilkin @cervus (2021). "UEFA Euro 2020." Hosted by [data.world]. Available at: “https://data.world/cervus/uefa-euro-2020".
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