No better time to start your analysis journey in football with the start of the new season
And SoccerViz Library is a 3-in-1 Python package allowing you to scrape, filter, and plot insightful visuals, making it easier for you to start with analysis with a few lines of code
👨💻 How to get started: Head over to the GitHub repository I published, and give a read on the ReadMe file for instructions and a tutorial on how to use the package!
Link to Github: []
@afcjxmes
Arsenal and City control the ball most of the time and their field tilt is significantly greater than Liverpool, hence fewer tackles, fewer blocks, fewer every defensive action lol😂
I would like to give credits to
@mplsoccer_dev
for the amazing package and most importantly
@mckayjohns
as his tutorials have helped me immensely in my football analytics journey.
Enjoy and please do reach out if you have any queries or feedback.
Attached image is an output eg.
🔍 What it does: My package targets football enthusiasts, analysts, and data lovers. Currently, it can effortlessly plot pass networks and showcase progressive passes on the field, providing a deeper insight into the game's dynamics. 📊🏆
I am very excited to announce that I have completed the FA Intro to Coaching Football (FA Level 1 Course), my first step towards becoming a Premier League manager, in sha Allah.
Can A Number Nine Fix Arsenal? 🚨
💬"Does a new number 9 fix all the cracks that have appeared after these stints of games? or are these cracks significant enough for Arteta to address?".
✏️
@athalakbar13
🌟 Features:
Scrapes event data for the popular leagues around the world
Pass Networks: Visualize the intricate passing patterns in your favorite football matches.
Progressive Passes: Analyze and highlight those game-changing, forward-moving passes
@nonewthing
I hope we see more of him in the box, look at McTominay EtH has started using him as the extra man in the box, because of his physical presence
Just made my first GitHub repository public, a code that'll help you guys assess midfielders by percentile rank comparing them to the midfielders in the top 5 leagues.
Do check out the repo here:
[]
Here's a product of the code🔽
@EBL2017
I think their recruitment has also been very smart, and if they keep it that way, they can stay here for a decent time, next season will tell if they have what it takes
@billycarpy
Maybe Palhinha is actually a signing to either play as a CB, or cover for Rice when he plays CB, if we have an injury to one of our thin defending profiles in the squad
@nonewthing
I agree a number 6 should be conservative every “big” team had one, Busquets in Barca, Fabinho in the Liverpool side, Casemiro for the Galacticos the list would go on….
🔮 What's Next: This is just the beginning! I'm already buzzing with ideas for future additions to the package. 🚀 Stay tuned for updates as I plan to expand its capabilities to cover even more aspects of football data analysis. 📈⚙️
@billycarpy
Like im nobody but I feel like throw ins are the time where opposition are unsettled and out of position and quick ones can help exploit that
Players ranked according to their Shot Creating Actions and Expected Assists, and the bigger the circle the more Goal Creating Actions by the player.
Take notes for your
#FPL
teams on which midfielders/defenders to choose
Players with a 40% success in take-on attempted.
The Green Box is a great place to be for good dribblers, calculated by taking an average for progressive passes received and take-ons attempted.
Assessed dataset of
#EPL
23/24 only
credits: opta via fbref
#football
#EPL23
@AFTVMedia
I think Saka should be rested, as the next game against City is very important, in psychological terms, so Saka should be at a 100% against them