melt
worldfootballR
| melt | worldfootballR | |
|---|---|---|
| 1 | 7 | |
| 11 | 411 | |
| - | - | |
| 7.8 | 9.0 | |
| 23 days ago | 4 months ago | |
| R | R | |
| GNU General Public License v3.0 only | - |
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melt
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Peer-Reviewing Statistical R Packages
melt: Multiple Empirical Likelihood Tests by Eunseop Kim, reviewed by Alex Stringer and Pierre Chausse, edited by Paula Moraga
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?
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