[thom]

If anyone's interested in doing similar analysis, my company StatsBomb makes a lot of event data available on GitHub, including the last World Cup, lots of Champions League finals, NWSL and FAWSL etc:

https://github.com/statsbomb/open-data/

[bgrnwd]

StatsBomb has been great for open football data, which is hard to come by. I always enjoy the Statsbomb panels at Sloan too.

If anyone is interested in getting started with soccer/football analytics, this is a good place to start: https://github.com/devinpleuler/analytics-handbook

[rjtavares]

Highly recommend this and the "Friends of Tracking" youtube channel.

Also, follow Thom on twitter, he is one of the smartest and most knowledgeable person in this space.

[thom]

Yeah, the Metrica data used in a lot of the FoT stuff is also an awesome place to start:

https://github.com/metrica-sports/sample-data

[levidxyz]

Are you able to share how StatsBomb collects event data? I'd love to build something to capture stats for local club teams but probably not if it involves computer vision. Thanks!

[torvaney]

If you're interested in collecting small-scale/simple event-data, I put something together for my own use here: https://torvaney.github.io/projects/tracker.html

[thom]

We do use a combination of humans and computer vision, and some providers (especially of full tracking data) have wholly automated pipelines, but analysts all over the world are collecting stuff manually every day. Really depends what sort of stuff you want to collect - you can use something like SportsCode to match any sort of events to video segments, and if you're a coach or scout you'll know what performance indicators you think are most important. If you just want some sort of team performance metrics you could start collecting shot data (coordinates, defensive pressure, type of assist etc) and build a simple xG model. Nothing you can't do in a spreadsheet or even on paper.