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11. soccerdata (scrape data)

Looking for places to publish #sportsanalytics research? We’ve put together a list: dtai.cs.kuleuven.be/sports/venues/

Our projections are back! 🔮 We have simulated #euro2024. Our model rates France as the strong favorite with a 26% chance of winning, followed by Germany, England, Portugal, and Spain. w/Pieter Robberechts Jesse Davis dtai.cs.kuleuven.be/sports/blog/pr…

A key challenge in developing sports analytics metrics is how to evaluate them. I shared some insights on this topic at the PySport meetup a few months ago, covering various approaches and lessons learned. A recording of the talk is now available online.

🏟️ With 51 matches ahead, our computer model has a standout #euro2024 favorite—France🇫🇷 at 26%. Other top contenders include: 🇩🇪16%, 🏴󠁧󠁢󠁥󠁮󠁧󠁿15%, 🇵🇹11%, 🇪🇸10%. Our interactive visualization provides detailed odds for each team👇(\w Deniz Can Jesse Davis ) dtai.cs.kuleuven.be/sports/euro202…

Curious about the favorites for #CopaAmèrica2024? our projections are below with home advantage for the US. w/Pieter Robberechts

Where do you normally store large assets required for automated tests? Should it be part of the repository? Those assets can be several GB so don’t want to download those on every single run. Oh, and the assets are private and access should require some sort of authentication.

Part of Kloppy 3.15.0 is the 𝘢𝘨𝘨𝘳𝘦𝘨𝘢𝘵𝘦 method. This allows you to go from dataset to aggregation in a single line. The first one implemented is 𝘮𝘪𝘯𝘶𝘵𝘦𝘴_𝘱𝘭𝘢𝘺𝘦𝘥. It returns the time a player was on the pitch (including start- and end timestamps).

At long last, we have a (fingers crossed) bug-free implementation of orientation and pitch dimension transforms in Kloppy!🚀✨

Attending ECML PKDD and interested in sports ⚽🏀🏈? Don’t miss our tutorial on Team Sports Analytics tomorrow! Our goal is to provide an accessible overview of existing work on the use of machine learning in sports. Check out the details here 👉dtai.cs.kuleuven.be/tutorials/spor…

Has soccer gone too far in its obsession with keeping possession?⚽️ A few weeks ago I presented our latest research paper “Boot It: A Pragmatic Alternative to Build-Up Play” at the #StatsBombConference. 📽️ youtube.com/watch?v=OuiQBt… 📝statsbomb.com/wp-content/upl… [1/3]

Nothing quite like a 'quick update' turning into a two-day saga of dependency chaos. But hey, 𝗱𝟯-𝘀𝗼𝗰𝗰𝗲𝗿 is updated for the first time in 4 years! 🚀 github.com/probberechts/d…

I promise there will be some great insights into this blog post series.

Part 2 in our series on possession value models design decisions🔍: How the definition of "near future" has interesting effects on player ratings. It's not about 'better,' but about understanding the nuances. w/ Pieter Robberechts Jesse Davis Lode Van Tente dtai.cs.kuleuven.be/sports/blog/an…

🎄 𝐤𝐥𝐨𝐩𝐩𝐲==𝟑.𝟏𝟔.𝟎 Happy Holidays to the Sports Analytics Community! This release contains some exciting updates, you can find the highlights in this thread. But first, we're really excited that Pieter Robberechts has officially joined as a maintainer! 💙

One of my hobbies is doing some light data science for soccer. Best package in the game is SoccerData. Makes it easy to pull down dataframes of match and season data from the major soccer providers.

🚨The third and final blog post in our series on possession value models design decisions🔍: Can the features chosen to represent the game state inadvertently bias player ratings? w/ Pieter Robberechts Jesse Davis Lode Van Tente dtai.cs.kuleuven.be/sports/blog/an…