StatsBomb Case Study: Atlético Mineiro, Brazilian Série A Champions 2021
Atlético Mineiro have enjoyed a fantastic year. In early December they wrapped up their first Brazilian league title in 50 years, eventually finishing a full 13 points clear of Flamengo in second place, and just last week they added to that by winning the Copa do Brasil to complete a domestic double -- the first in their history.
Atlético signed on to use StatsBomb’s industry-leading data and analysis software in May 2021, in the process becoming our first Brazilian customer. With their newly created analytics department, headed by Rodrigo Picchioni, they demonstrated their commitment to becoming a standard bearer in the region in the intelligent use of data to make better decisions.
We talked with Pedro Picchioni, Head of Scouting Analytics, about how data has helped the club find a key edge over their domestic rivals in what has arguably been their most successful season ever.
StatsBomb (SB): Firstly Pedro, congratulations for an amazing year. To kick off, can we go back in time to your decision to partner with StatsBomb. What was the challenge that you wanted to solve by using StatsBomb’s services?
Pedro Picchioni (PP): As a recently created department, we essentially needed a reliable data source to get underway on our task of providing objective insights for the decision-making processes at the club.
The main reason we decided to work with StatsBomb was the reliability and level of detail in the data collection process. For sure we made the right decision. By providing a reliable, fast and powerful database, StatsBomb’s services are currently crucial in the operations of the department.
SB: What types of goals or tasks are you using the product to accomplish?
PP: We currently assist other departments in the club by providing data-driven analysis of players and teams.
SB: What is the feature of our StatsBomb IQ analysis platform that you or your team use most frequently, and why?
PP: StatsBomb IQ is a really powerful platform that is constantly used in many ways in our processes, but our most used tool has to be IQ Tactics. We are able to really dive deep on player and team actions in the smallest detail. This tool helps us find specific patterns that are sometimes hard to find in an aggregated analysis.
There was a situation where a player was flagged as being a complete outlier in terms of deep progressions (passes and dribbles/carries into the opposition final third), which definitely caught our eye. However, when we dived into his passes in IQ Tactics, we were able to see that most of them were diagonal passes to wide areas which didn’t necessarily progress the team forward that much, and this was later confirmed on video.
SB: Have any of our metrics or models proved particularly useful in your work?
PP: StatsBomb's Expected Goals (xG) model is by far the best and most detailled on the market, as it considers the position of all players in the video frame as well as the effect that the impact height has on the probability of the shot being converted.
Additionally, the newly released On-Ball Value (OBV) metric has been a great asset to us, both in the process of player identification and in terms of understanding the strengths and weaknesses of teams.
For example, we were looking at where an specific opponent conceded OBV from passes and carries in comparison to the league average and noticed that their central corridor was a particularly weak link in their system, which was something that we could take advantage of.
SB: What has been the impact of using StatsBomb's services?
PP: StatsBomb's services have had a great impact on our work, as they are crucial in the process of providing important insights to the decision makers at the club.
This case study is also available in Portuguese.
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