An R package providing comprehensive historical soccer match datasets and analysis functions for European and MLS leagues.
engsoccerdata is an R package that provides extensive historical soccer match datasets, covering European leagues, MLS, and cup competitions from the 19th century to the present. It solves the problem of fragmented and hard-to-access historical soccer data by offering a centralized, curated repository with built-in analysis functions.
Data analysts, researchers, and soccer enthusiasts who use R for sports analytics, historical research, or performance modeling. It's particularly useful for academics, journalists, and hobbyists analyzing long-term trends in soccer.
Developers choose engsoccerdata for its unparalleled historical depth, ease of use within the R ecosystem, and the inclusion of ready-to-use analysis functions that simplify common tasks like table generation and head-to-head summaries.
English and European soccer results 1871-2022
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Includes match results from as early as 1871 for English leagues, providing unparalleled longitudinal data for trend analysis and academic research.
Offers ready-to-use functions like `maketable` for league tables and `games_between_sum` for head-to-head records, saving significant development time for common analytics tasks.
Dates are consistently stored as YYYY-MM-DD strings and team names are modernized, ensuring cross-source compatibility and easier data manipulation.
Open to contributions for extending datasets, as highlighted in the 'Help Needed' section, which helps improve data completeness and accuracy over time through collaborative efforts.
As admitted in the README, MLS and cup data are only up to 2017, and some European leagues may lag behind current seasons, limiting analyses of recent trends.
Users may encounter SSL certificate errors during installation, requiring additional configuration with `httr` and `RCurl` packages, which adds complexity for beginners.
Missing data for European competitions, lower league cups, and promotion/relegation playoffs, as noted in the 'Help Needed' section, reducing utility for comprehensive studies.
Relies heavily on community contributions for updates and verification, which can lead to inconsistencies, delays, and potential errors in data accuracy without formal oversight.