It's a Python wrapper for the website Understat, which provides revolutionary football metrics multiple leagues. An example of this is expected goals (xG), which is the main new revolutionary football metric, and allows you to evaluate team and player performance. In a low-scoring game such as football, the final score does not really provide a clear picture of the teams' performances, and this is why more and more sports analytics turn to the advanced models like xG, which is a statistical measure of the quality of chances created and conceded. Understat's goal was to create the most precise method for shot quality evaluation. They did this by training neural network prediction algorithms with a large dataset (>100,000 shots, over 10 parameters for each), and have now made this data available for the public!
In the last update I added quite a lot of functions. Today I was writing the documentation for it, and realised I had missed some data, and so in this update I've added these as well. The update is a bit smaller than last time, but I wanted to make sure everything that is available on https://understat.com/ is also available in the package, so I still felt it was pretty important to add these.
https://github.com/amosbastian/understat/pull/2
The pull request also includes all the documentation stuff, so I'm sorry for that. You can find the changes relevant to this update in the .py files (apart from conf.py). Here's what changed:
Add new functions and tests:
* `get_team_stats()`
* `get_team_results()`
* `get_team_fixtures()`
* `get_team_players()`
Rename:
* `get_players()` -> `get_league_players()`
* `get_results()` -> `get_league_results()`
* `get_fixtures()` -> `get_league_fixtures()`
Before this update to get a specific team's stats you would need to get the stats of the league the team plays in, and then filter the result by team name. Obviously this is pretty tedious, and so with this function you can get a team's stats directly. Basically, it returns all the information you can find in the screenshot below
and an example showing how to use can be found below
Getting the results and fixtures of a team was very similar to getting the stats of a team. You'd have to get a specific league's fixtures, and then filter by team. This was even more annoying in this case, because instead of passing something like team_name="Manchester United" and side="h" as a keyword arguments, you'd have to pass a dictionary like this for example:
{
"h": {
"id": "89",
"title": "Manchester United",
"short_title": "MUN"
}
}
which is obviously very difficult to remember. With this new function you can simply do the following
This is equivalent to the fixtures you can find on a team's page, as seen in the screenshot below
Same thing as the stats really, except with players. It's much easier to use this function to get a team's players, because, for one, you don't need to remember the league anymore, and secondly, you don't need to remember which key value pair to filter by.
An example showing how to get all Manchester United players who have played in the forward position in this season is shown below:
I've also completed the documentation for Understat, which I will be posting about tomorrow. Because of this I will also post about the package as a whole on Reddit, and hopefully get some more people interested in it, who will also hopefully come up with some suggestions, and maybe even help!
The recommended way to install understat is via pip.
pip install understat
To install it directly from GitHub you can do the following:
git clone git://github.com/amosbastian/understat.git
You can also install a .tar file
or .zip file
$ curl -OL https://github.com/amosbastian/understat/tarball/master
$ curl -OL https://github.com/amosbastian/understat/zipball/master # Windows
Once it has been downloaded you can easily install it using pip::
$ cd understat
$ pip install .
Import Understat and call its functions like so:
import asyncio
import json
import aiohttp
from understat import Understat
async def main():
async with aiohttp.ClientSession() as session:
understat = Understat(session)
data = await understat.get_league_players("epl", 2018, {"team_title": "Manchester United"})
print(json.dumps(data))
if __name__ == "__main__":
loop = asyncio.get_event_loop()
loop.run_until_complete(main())
pytest tests/ to confirm they all pass on your system.pytest tests/ to confirm that everythingmaster branch.Documentation and examples for understat can be found at http://understat.readthedocs.io/en/latest/.