JaviOnData Profile Banner
Javier Fernández Profile
Javier Fernández

@JaviOnData

Followers
13K
Following
1K
Media
95
Statuses
657

@ChelseaFC. Formerly @ZelusAnalytics, @FCBarcelona. Views are my own. At BlueSky as @javiondata.bsky.social

Joined November 2016
Don't wanna be here? Send us removal request.
@JaviOnData
Javier Fernández
4 years
I'm glad to share that I've successfully defended my Ph.D. thesis in Artificial Intelligence, under the inspiring direction of @LukeBornn and the support of @FCBarcelona coaches. Here's a thread with details of our quest for a comprehensive analysis framework (toolbox) in soccer
33
106
1K
@JaviOnData
Javier Fernández
9 months
🚨 We're hiring at Chelsea FC!🔵 🚨 This is a unique opportunity to join our analytics team and be at the heart of decision-making at a fantastic club. Full Stack Web Developer: https://t.co/wmUYL6m2yR Data Engineer: https://t.co/sbYJdPsVm2 Full post:
Tweet card summary image
linkedin.com
🚨 We're hiring at Chelsea FC!🔵 🚨 We’re looking for a Full Stack Web Developer and a Data Engineer to join our football analytics team. This is a unique opportunity to be at the heart of decision...
18
83
365
@JaviOnData
Javier Fernández
10 months
I’m joining BlueSky 🦋 as it seems the soccer analytics community is 🔥 there! For all of you who already transitioned, it would be great to connect. You can find me as @javiondata.bsky.social
3
0
28
@ripcityremix
Rip City Remix
1 year
We play for moments like this.
4
7
56
@Alumn_USB
AlumnUSB
1 year
¡No te pierdas el nuevo episodio de nuestro podcast "Conversando con Uesebistas"! Hoy, charlamos con Javier Fernández, Ingeniero en Computación (Cohorte 04), con un Máster en IA por la Universidad Politécnica de Catalunya y una impresionante carrera en el FC Barcelona. Javier
1
5
8
@WMoneyball
Wharton Moneyball
1 year
Today's show is available in Podcast Form NOW! 0:00 - Wimbledon | Comparing Eras | Willie Mays 28:00 - Motion Tracking Data w/Javier Fernandez Listen HERE: 👇👇👇 https://t.co/ede4wF8H5s
Tweet card summary image
podcasts.apple.com
Sports Podcast · Updated Weekly · Sports is a game of numbers. Wharton experts Eric Bradlow, Shane Jensen, Cade Massey, and Adi Wyner team up to tackle the world of sports, from current events to...
0
1
6
@JaviOnData
Javier Fernández
2 years
Con mucha ilusión de hablar hoy en el Aztec Sports ⚽️🇲🇽Data Summit ( https://t.co/YW2Fri0E2d). Repasaremos los grandes avances del soccer analytics y cómo ayudar a los tomadores de decisiones en un club. 💡Todavía hay tiempo de registrarse para asistir online.
0
2
29
@EstebanNG_
Esteban Navarro Garaiz
2 years
Estoy muy emocionado de ser parte de #AztecDS y compartir escenario con @JaviOnData, Gustavo y Enrique. Nos vemos el 8 de septiembre en @ITAM_mx👋🏼👨🏻‍💻⚾️ Se pueden registrar en https://t.co/z42akFuAzS, donde todavía les queda una semana para participar en el Hackathon 👀
@Landeros_p33
Pablo L. Landeros
2 years
🚨We’re incredibly excited to announce the speaker lineup for the 2023 Aztec Data Summit 🚨 Esteban, Javier, Enrique and Gustavo will be talking about how data-driven decisions can make an impact on or off the field. Sept 8th,2023. CDMX Registration is open!! 💻⚽️
0
4
14
@JaviOnData
Javier Fernández
2 years
Quick poll ⚽️📊 What’s the #1 soccer analytics topic you’re eager to master but haven’t found the right resources? Let me know why in the replies. Feel free to suggest additional topics too! #SoccerAnalytics
3
4
17
@JaviOnData
Javier Fernández
2 years
Quick poll ⚽️📊 What’s the #1 soccer analytics topic you’re eager to master but haven’t found the right resources? Let me know why in the replies. Feel free to suggest additional topics too! #SoccerAnalytics
3
4
17
@Landeros_p33
Pablo L. Landeros
2 years
Amable recordatorio de que la convocatoria para el Aztec Data Hackathon está abierta 🇲🇽💻 Los mejores 3 proyectos podrán presentar el 8 de septiembre en la conferencia donde contaremos con la presencia de directivos de equipos de Liga MX ⚽️ Anímense!
4
24
68
@JaviOnData
Javier Fernández
2 years
On the hunt for soccer match videos 🕵️⚽! Any public and open license sources for full World Cup, Eurocup, or Big 5 matches?
2
0
7
@arbues6
Adrià Arbués Sangüesa
3 years
Som-hi! Si voleu saber més sobre models predictius i aplicacions amb dades de tracking... 📊 I Congrés d'Analítica Aplicada al Bàsquet 📅 30 de juny i 1 de juliol 📍Manresa 🔗 https://t.co/0BQZaB7fUK
Tweet card summary image
basquetcatala.cat
L'esdeveniment es realitzarà el 30 de juny i l'1 de juliol i les inscripcions segueixen obertes.
@FCBQtecnic
FCBQtècnic
3 years
FORMACIÓ CONTINUADA | 💻 Adrià Arbués us espera al I Congrés d’analítica aplicada al bàsquet https://t.co/kTNlxfejEF 🏀
0
1
18
@JaviOnData
Javier Fernández
3 years
This was very fun and I hope it's useful for our community. Share your thoughts on other languages, frameworks, or proprietary solutions that you think could make soccer analytics work easier and better.
1
1
2
@JaviOnData
Javier Fernández
3 years
There are some fantastic public packages in both Python and R that can take you a long way pretty quickly. This makes a case for adopting a hybrid stack. Typically, available packages excel in: Py ➡️ engineering + modeling R ➡️ visualization + scraping
1
0
2
@JaviOnData
Javier Fernández
3 years
Intriguing suggestions: Julia, Rust & other robust frameworks! (h/t @mr_le_fox) Clubs aren't tech companies, sparking a debate on choosing the best tools for the job vs. tools that integrate smoothly into the organization 💼🔧.
1
0
0
@JaviOnData
Javier Fernández
3 years
4) R (eng.)/Py (modeling) got 6.1% -> 52 voters. A notable group of analysts prefers a non-standard & kinda surprising "inverse" stack 💡 I suspect that if we concentrate engineering tasks on data wrangling this would make good sense.
1
0
0
@JaviOnData
Javier Fernández
3 years
3) Programming Stack: Same language (79.1%) triumphs over hybrid (20.9%)! ⚽️ analysts love language consistency👩‍💻👨‍💻 This keeps things simpler, but I wonder how much of this choice is influenced by analysts' backgrounds (Eng + Comp Sci vs. Stats + Math + Physics) 🤔
1
0
0
@JaviOnData
Javier Fernández
3 years
2) Engineering & Wrangling Showdown: Python (65.9%) vs. R (34.1%)! Python rules data engineering tasks, while R's commendable performance is likely driven by its powerful data-wrangling libraries 📚. For pure backend tasks, Python's preference could be even higher!
1
0
0
@JaviOnData
Javier Fernández
3 years
1) Modeling: Python (57.2%) vs. R (42.8%) Soccer analysts show a strong affinity for R, well beyond its 15% adoption in Data Science (as per ChatGPT-4 😅) Yet, Python is still king 🐍👑
1
0
0