Foot en Stats

2.4K posts

Foot en Stats banner
Foot en Stats

Foot en Stats

@FootEnStats

*Compte en hibernation*

เข้าร่วม Ağustos 2017
756 กำลังติดตาม1.6K ผู้ติดตาม
ทวีตที่ปักหมุด
Foot en Stats
Foot en Stats@FootEnStats·
Les Expected Goals ont-ils une relation quelconque avec la qualité des tirs comme le laisse entendre les définitions d'Opta ou d'Understat ? Je ne le pense pas. Lisez l'article et n'hésitez pas me challenger ! wordpress.com/post/footensta…
Français
4
1
13
0
Pranav
Pranav@pranav_m28·
🔴Introducing Tempo Control Profiles We often talk about tempo when talking about football. We talk about players who SET the tempo, players who CONTROL it or players who RAISE it. So I decided to quantify it, visualise the actions and develop a classification system using data. It divides the players into three main categories: 1. Tempo Catalyst - players who speed up the tempo 2. Tempo Conductor - players who maintain the tempo and have a right balance of slowing it down as well as increasing it 3. Tempo Settler - players who recycle more often, like to inject less The framework has two main aspects: Injections and Resets. In simple terms, I look at the time gap between actions, compare the action to the recent rhythm of the sequence, and then judge whether it speeds the move up or slows it down. From there, I add territorial context as well, so quicker actions that also move the ball into more dangerous zones carry more value than quick actions with little tactical impact. Here is Bruno's Tempo Control Profile. He falls under the Tempo Catalyst profile. Not surprising given how good he is at releasing quick incisive passes. Decent number of tempo increasing carries as well. You can request for similar maps, specific lists and even drop suggestions and methods of improvement. I will share more results and try to improve this over the coming days.
Pranav tweet media
Pranav@pranav_m28

Working on some Tempo based analysis. Idea is to have two different analysis methods: Action Maps and a Classification Model. Current framework is to use the delta T of preceding action(s) and looking at actions which speed up the passage of play. The actions are classified into 'Injections' and 'Resets'. Basically, an injection speeds up play, a reset slows it down.

English
47
43
250
61.1K
Pranav
Pranav@pranav_m28·
Premier League 2025-26 | Shooting Decision Speed vs Efficiency | Forwards -Woltemade, Haaland, Welbeck: quick and effective, headers, one touch shots etc -Mbeumo, Thiago, Barry a tier below them -Joao Pedro & CHO: slower but effective -Igor Jesus: quick but ineffective
Pranav tweet media
Pranav@pranav_m28

Shot-Map-Cards update should get pushed by tonight. Let me know if you guys would like to see something specific. Please don't say xG. Link: shot-map-cards.streamlit.app

English
3
6
25
45.8K
Penalty Kick Stat
Penalty Kick Stat@PenaltyKickStat·
@FootEnStats Incorrect. The historic data of all teams over 3y gives the baseline of different options. Given the game state, x,y etc the 25/26 teams’ individual decisions are compared against the best option for that context. xGs are compared - historic optimal vs chosen option.
English
1
0
0
66
Penalty Kick Stat
Penalty Kick Stat@PenaltyKickStat·
The DMI - Decision Making Index. How much xG do teams 'waste' for each decision, compared to the best option possible? ('Decisions' = x, y, pass direction and length, carries / take ons and shots.) -> Stronger teams make better decisions.
Penalty Kick Stat tweet media
English
2
0
4
959
Foot en Stats
Foot en Stats@FootEnStats·
@PenaltyKickStat So "best decision" is an assessment against what teams do in the 3 years span, not an assessment of each situation in their context? Is this correct?
English
1
0
0
33
Penalty Kick Stat
Penalty Kick Stat@PenaltyKickStat·
@FootEnStats Event data and it’s a model I built as described in the subsequent posts.
English
1
0
0
51
Foot en Stats
Foot en Stats@FootEnStats·
Vous saviez que Club Bruges est engagé dans une stratégie data mise en place par l'excellent @JanVanHaaren ? 👀
Français
0
0
1
165
Foot en Stats
Foot en Stats@FootEnStats·
On observe les mêmes phénomènes statistiques en Ligue 1 (et globalement dans le foot pro). Clermont, Brest sont des exemples récents de surperformances suivis par une régression à la moyenne la saison suivante.
Pythagoras In Boots ⚽️@pythaginboots

xG doesn't determine your league position but can it predict the future? We found that across 5 Premier League seasons, the bigger the gap between results and underlying performance, the harder teams regress the following season Walk with me [A THREAD] 🧵 ✍️ @sjatfkb

Français
0
1
3
565
Foot en Stats รีทวีตแล้ว
Julien Demeaux
Julien Demeaux@JuDems14·
@lequipe publie un article sur Bradley Barcola et ses préférences motrices. Si le constat sur de ses PM me paraît correct, en faire la cause principale de son manque d'efficacité face au but est un raccourci dangereux. J'essai d'y apporter des nuances. linkedin.com/pulse/donn%C3%…
Français
5
13
77
39.7K
Foot en Stats
Foot en Stats@FootEnStats·
@Stat_Ron Hey Ron, where can I find a link to the class? Thanks
English
0
0
0
64
Joe Mulberry
Joe Mulberry@theJoeMulberry·
Stuck in stand still traffic for over an hour and counting… Any questions to help me pass the time?
English
2
0
0
3.5K
Ben8t
Ben8t@Ben8t·
Quite impressed by how @kestra_io is used in a MLS club already. I would love to have this declarative semantic orchestration tool back when I was doing data in football :) @kestra-io/efficient-automated-football-data-analytics-in-mls-with-kestra-02545473206e" target="_blank" rel="nofollow noopener">medium.com/@kestra-io/eff…
English
1
4
9
1.6K
Foot en Stats รีทวีตแล้ว
Toulouse FC
Toulouse FC@ToulouseFC·
Elle tire sa force, son caractère et sa puissance des Pyrénées jusqu'à l'île du Ramier. Notre nouveau maillot warm-up @craftsportsfr 2023/2024 et @AurelSanchez_ lui rendent hommage. 𝙇𝙖 𝙂𝙖𝙧𝙤𝙣𝙣𝙚 𝙚𝙨𝙩 𝙑𝙞𝙤𝙡𝙖 💜 #DeboutToujours 😈
Français
25
78
628
83.2K
Foot en Stats รีทวีตแล้ว
Podcast Prolongation 🎙⚽
Podcast Prolongation 🎙⚽@prolongationpod·
🚨 Nouvel épisode ! Avec Julien Demeaux @JuDems14, responsable des données football au @ToulouseFC ⚽️ 🎙️ Son parcours atypique, la place et la pertinence de la data, l’utilisation pour scouting et équipe première, la vulgarisation… shows.acast.com/podcast-foot-p…
Français
1
12
39
10.5K
Foot en Stats รีทวีตแล้ว
Zelus Analytics
Zelus Analytics@ZelusAnalytics·
We'll be closing our data science and product roles on June 5th. Highly encourage those interested in joining our fully remote team to get their applications in while they can :)
Zelus Analytics@ZelusAnalytics

Join us! We're hiring for data science, product, operations, and engineering roles across various sports (🏒🏈⚾️⚽️🏀🏏🎾⛳️). Work remotely with our talented team at Zelus and help shape the future of sports analytics. Learn more on our careers page zelusanalytics.com

English
3
9
21
21.5K
Foot en Stats
Foot en Stats@FootEnStats·
@Vadeboncoeur_Al Team 1er degré (au cas où) : la taille du ballon est de 1 pied (1 foot), le nom du sport est donc dérivé de la taille de son ballon
Français
0
0
0
152
Doc Vadeboncoeur
Doc Vadeboncoeur@Vadeboncoeur_Al·
Question existentielle : pourquoi le football (américain) porte-t-il ce nom, alors que les pieds n'y jouent qu'un rôle mineur en comparaison avec les mains et touche fort peu au ballon? 🤔
Français
56
2
93
59.5K
Ted Knutson
Ted Knutson@mixedknuts·
It's here! A request line THREE YEARS in the making... Give me your COLLEGE FOOTBALL RADAR REQUESTS. I will leave the line open for the next hour. We'll start with your national champion... Stetson Bennett, UGA 22-23.
Ted Knutson tweet media
English
42
5
43
69.7K
Tapa
Tapa@onlytapa·
As you guys know, I build paid communities to $100k/month I just created a Notion with all my threads and auto dms showing how I do it This could be a full $500 course Like, Retweet and Comment 'done' and I'll DM it to you for free (must be following or I can't send)
Tapa tweet media
English
878
644
985
149.2K