understatr
worldfootballR
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| understatr | worldfootballR | |
|---|---|---|
| 2 | 7 | |
| 81 | 408 | |
| - | - | |
| 0.0 | 9.0 | |
| over 2 years ago | 3 months ago | |
| R | R | |
| MIT License | - |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
understatr
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[OC] Visualising shot-creating actions in football - all Arsenal players with over 5 shot-creating actions in PL 2020/21
Additional credit: understatr package, https://github.com/ewenme/understatr
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How Aston Villa went from surviving to thriving in the Premier League
Thanks! Understat.com has great xG data and allows you to pull it into R very easily (like this)[https://github.com/ewenme/understatr]. There were also a couple random pieces of information that I found at whoscored.com. Thanks for reading!
worldfootballR
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[OC] Attacking Productivity: Who is Over-performing this Season and Who has been Lucky?
I found this the other day though, where there is an R package with what looks like a good amount of data. So, when I'm ready I might explore this as this might be the best approach to pull in a lot more players more easily.
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Daily Discussion
https://jaseziv.github.io/worldfootballR/ works really well with publicly available data and does most of the data scraping for you, but if you wanted to access paid stuff then you’ll need something else.
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[OC] A Data Dive into Spurs (lack of) Sub Usage (2nd Least Sub Minutes in League Play)
Data is from FotMob and grabbed via worldfootballR. Highly recommend to anyone looking to play around with soccer data, it's super well documented (as is everything in SportsDataverse). It doesn't have player location and all the advanced stuff but has a lot of rich shot data + match stats/events. worldfootballR has a bunch of fb-ref, understat, and transfermarket data as well.
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data sets about Scottish football
There’s an R package called worldfootballR that can be used to extract data from FBref, Transfermarkt, Understat and FotMob. Most of those sites don’t carry much data about Scottish football but FotMob have some really useful shot location data with xG and xGOT values. Here’s the link to the package: https://github.com/JaseZiv/worldfootballR
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[Q] Looking for downloadable football (soccer) statistics
The worldfootballr R package can help you download from some of the big ones.
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[OC] Liverpool and Real Madrid's paths through the knock out stages to the Champions League final
Source:WorldfootballR package
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[OC] Liverpool Substitutions Using worldfootballR and GT
Data extracted using worldfootballR
What are some alternatives?
ggshakeR - An analysis and visualization R package that works with publicly available soccer data
dplyr - dplyr: A grammar of data manipulation
football_analytics - 📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
blogdown - Create Blogs and Websites with R Markdown
engsoccerdata - English and European soccer results 1871-2022
ggplot2 - An implementation of the Grammar of Graphics in R
echarts4r - 🐳 ECharts 5 for R
wesanderson - A Wes Anderson color palette for R
epanet2toolkit - An R package for calling the Epanet software for simulation of piping networks.
soccerdata - ⛏⚽ Scrape soccer data from Club Elo, ESPN, FBref, FiveThirtyEight, Football-Data.co.uk, FotMob, Sofascore, SoFIFA, Understat and WhoScored.
DontBlameTheData - Repository for the backend of dontblamethedata.com
osrm - Interface between R and the OpenStreetMap-based routing service OSRM