Next up in mplsoccer... animations using @kubamichalczyk.bsky.social line tracking method ๐
Andy Rowlinson
@numberstorm.bsky.social
Data insights and creator of mplsoccer, a Python library for football viz.
๐ mplsoccer v1.8.0 Adds custom heatmaps and sonars. Now you can plot on any tiling of rectangles you want.
๐ I just pushed a new mplsoccer version: 1.7.1. It adds curved parameter labels to Radar charts and Pizza charts. Thanks to Palash Gupta for collaborating on this release.
Reading someone's blog and saw this "distinction matters" tell tale Claude and just gave up. Is it worth reading stuff when you don't know the author might not have done any thinking?
One quarter down.. some reflections a) the new models are so good and fast, even for analysis. b) meetings have gone from context switch problems, to oh fuck I could have done so much in that half an hour/hour c) it's hard to turn off the PC at the end of the day, you can get loads done in 15 mins
New year, new resolution. I hand craft a lot of data insights and datasets. Hoping to use agents more to help. Thinking of writing a skill.md for each database schema (dataset) so an agent knows how to join views and tables, the main filters to use, and the key columns. #databs
Claude Opus loves to say "good instinct" and then completely burn your idea to the ground ๐ฅ๐ฅ๐ฅ
"As his post goes on, his language gets older. 100 years older with each jump. The spelling changes. The grammar changes. Words you know are replaced by unfamiliar words" Fascinating. So how far back in time can YOU go?
How far back in time can you understand English?
An experiment in language change
deadlanguagesociety.com
I released an update to mplsoccer that should make it easier to add other sports.
I can confirm this works and looks ace. I may be able to finally release a Statsbomb football data parser with no dependencies apart from duckdb.
We've open sourced QuackStore - a block-based caching extension for DuckDB! ๐ฆ QuackStore dramatically speeds up queries on remote data by intelligently caching only the blocks you need. Now available as a DuckDB community extension: github.com/coginiti-dev...
We've open sourced QuackStore - a block-based caching extension for DuckDB! ๐ฆ QuackStore dramatically speeds up queries on remote data by intelligently caching only the blocks you need. Now available as a DuckDB community extension: github.com/coginiti-dev...
GitHub - coginiti-dev/QuackStore
Contribute to coginiti-dev/QuackStore development by creating an account on GitHub.
github.com
I herby restart my campaign for my modest proposal to reduce the size of the penalty area to 30m wide. It might be more palatable to fans than Ted's arc from this pod.
New podcast! @patrickbvs.bsky.social and @mixedknuts.bsky.social talk about: โข Arsenal finding their best lineup for knockout football โข Spain running Yamal into the ground โข Aston Villa looking terrible so far โข The madness of Juve 4-3 Inter www.youtube.com/watch?v=KcNZ...
Dev and deploy require of diff skills. @getdbt.com bridges the gap for #data pipelines, but what about MLOps? I explored how @posit.co {orbital} + dbt delivers "good enough" zero-infra MLOps for batch model scoring in database from python or #rstats models www.emilyriederer.com/post/orbital... 1/
MLOrbs?: MLOps in the database with orbital and dbt | Emily Riederer
Playing with the potential, perils, and design principles of deploying ML models into the analytical database using orbitalโs sklearn-to-sql translation, sqlglot, and dbt
emilyriederer.com
I have finally published my post about Moneyball, as promised (a long time ago). If you're interested in baseball, numbers, or movies, please take a look. I'd love to know what you think. cc @matsonj.com @alexnoonan.bsky.social djpardis.medium.com/revisiting-m...
Revisiting Moneyball
Data, sports, payrolls, and memes
djpardis.medium.com
๐ mplsoccer 1.5.1 released @dmitry.mclachbot.com adds the capability to use custom slice labels in the pizza charts
๐ ๐๐ ๐๐: ๐๐ฅ๐๐ฌ๐ญ๐ข๐ ๐ ๐จ๐ซ๐ฆ๐๐ญ๐ข๐จ๐ง ๐๐ง๐ ๐๐จ๐ฌ๐ข๐ญ๐ข๐จ๐ง ๐๐๐๐ง๐ญ๐ข๐๐ข๐๐๐ญ๐ข๐จ๐ง โฝ The newest release of the ๐๐๐๐๐๐๐๐๐๐๐๐๐ Python package (v1.1.0) now includes the functionality of my latest research paper. ๐https://tinyurl.com/unravel-efpi
Tried this out on mplsoccer. Definitely impressive deepwiki.com/andrewRowlin... But , I think the generated docs are more interesting for someone looking to contribute to the codebase, rather than users.
andrewRowlinson/mplsoccer | DeepWiki
mplsoccer is a Python library for plotting soccer/football charts in Matplotlib and loading StatsBomb open-data. This page provides a high-level overview of the library's architecture, components, and
deepwiki.com
Just came across DeepWiki. Autogenerated docs for GitHub projects. I took a look a SlateDB's and woah... It's excellent. Seriously considering ditching our human-written ones on our website. Can spend all our time on rustdocs and let DeepWiki translate that.
๐ @unravelsports.com added some new formations to mplsoccer for his formation detection work. Hopefully will see some results some day.
@unravelsports.com just seen your PR today. Of course adding extra formations is helpful and happy to add it in. I'll try and look at it soon ๐
Yamal is so good he pretty much broke my axes when I looked at young attacking outliers. Streets ahead.
Some possession value models thought Lamine Yamal had a *bad* game last night. What??? How does that make any sense? How that happens, and why he's so good that he defies the models. www.thetransferflow.com/p/lamine-yam...
It's early days, but seeing if I can adapt mplsoccer to other sports
I have successfully switched mplsoccer docs to install via uv rather than conda. It took a while to fix some install problems with lxml. I think Conda still wins is installing the complex C dependencies in some data science projects (e.g. PyMc), but worked around it here with apt install.
The margins between winning the Premier League and being runner up are incredibly tight, just seven points separates the teams on average.
If learning from survey data, how do you feed in the non-response weights? #databs
Musing about the dark patterns you could build into a stadium design to cement home advantage 1/ screens showing the opposition making mistakes or missing penalties around their dressing room