Calculate expected points (xPts) in Python

[@lilianconvers866]

From a French guy, your prononciation of Poisson is perfect 😉

[@umtcanncubukcu.]

Loved the video.Will try in Turkish League

[@jakobriegler9324]

I‘m curious if the results would change if you consider each shot xG separately. A team who has only 1 shot which is worth 0.9 is surely more likely to win than a team who has 20 shots each worth 0.045 or not? At least it was explained like that in „the Expected goals philosophy“ book i read recently I‘m currently working on creating my own xG/xP Modell for the Academy of an Austrian Bundesliga Club as there is no data available for the youth teams, your videos really help me out on the programming side, looking forward for more of your videos :)

[@CleberCS]

Hello there, Do you have any video exploring corners?

[@Oxymoron_i]

I really like your videos about sports analytics. I want to focus on Baseball and F1 specifically though cuz those are the ones I follow closely and they are rich in usage of analytics and how much data they make available. Any great suggestions for getting into those?

[@McKayJohns]

I would check out sabermetrics for baseball. I'm not 100% sure on f1 i've never done anything with it

[@Oxymoron_i]

@@McKayJohns yeah for both sports there are python packages available. pybaseball for baseball and fastf1 for f1. fastf1 specially makes a lot of data available. it's a massive open source project. Just replying for anyone that was looking for info.