In this interview, we speak with Marc Prades, a seasoned handball coach and analyst working with Servesthand, an actor in handball data analysis. Marc shares insights into how Servesthand’s innovative approach is transforming team performance and player development through advanced statistical tools. Here, he explains the impact of data-driven strategies on the future of handball.
Can you introduce yourself and Servesthand?
My name is Marc Prades, and I am a handball coach and analyst based in Barcelona, with over seven years of experience on the bench. Since last year, I have also been collaborating with Servesthand, a company specialized in the application of statistical analysis in handball. In addition to my coaching background, I hold a degree in physics, which has given me a strong foundation in statistics and data analysis.
Servesthand is a young company founded by Joan Ramon Riqué and Anna Samà, both experts in data analysis. Joan Ramon is a mathematician with a master’s degree in sports big data, and Anna holds a PhD in mathematics, focusing her research on big data as well. Together, they have established a company that offers comprehensive statistical services for handball clubs at all levels, from youth teams to professional leagues. Although Servesthand's main goal is to foster athletic growth through the use of statistical analysis in handball, we also position ourselves as a tool for identifying issues during adolescence, using the same statistical data within handball to detect potential problems and challenges young athletes may face.
What services does Servesthand offer, and what is your approach?
At Servesthand, we provide a wide range of services designed to meet the statistical and analytical needs of any handball club. Our goal is to offer tools and solutions that enable clubs to enhance their performance and identify key areas for improvement, both technically and in terms of youth player development.
Some of our key services include:
Recording matches for in-depth analysis.
Collecting statistics using specialized software such as Steazzi.
Detailed analysis of teams and players, assessing performance and improvement areas.
Rival analysis to identify strengths and weaknesses.
Sponsorship assistance, helping clubs secure financial support by showcasing their data-driven growth.
Our philosophy revolves around helping clubs grow through professional, data-based decision-making. We believe that statistical analysis provides a crucial competitive edge, allowing teams to make informed choices that enhance both individual player development and collective team success.
How does Steazzi fit into your workflow, and what value does it bring to you?
Steazzi is the primary tool we use for data collection during matches. It allows us to gather a wide range of statistics on both team and player performance in real time. However, the true power of our analysis comes after this initial data collection. Once we have the raw data from Steazzi, we process it using our proprietary calculation engine, which employs advanced statistical metrics to conduct a deeper analysis.
In addition, we have built an extensive database of shots and other key actions, which further enriches our analysis. This database allows us to compare and benchmark individual and team performance against historical data, leading to even more precise and insightful reports.
These detailed reports provide a comprehensive view of both individual performance and team dynamics, offering coaches valuable insights into strengths, weaknesses, and areas for improvement. By leveraging this in-depth data, we help clubs make informed decisions that drive development and enhance competitive performance at every level.
Could you share examples of data you provide for advanced analysis (e.g., Performance Index)?
In the reports we generate, some of the key metrics we provide include the Performance Index, as well as advanced metrics like G-xG and xGoT-G.
What is the G-xG metric?
G-xG stands for Goals minus Expected Goals, which measures the difference between the goals a player has actually scored and the goals they were expected to score based on the type of shot. For example, a G-xG of 3.45 means that the player has scored 3 to 4 more goals than expected, whereas a G-xG of -4.34 indicates that the player should have scored 4 or 5 more goals based on the opportunities they had.
What is the xGoT-G metric?
xGoT-G stands for Expected Goals on Target minus Goals, and it measures the difference between the goals a goalkeeper has conceded and the goals they were expected to concede based on the type of shots they faced. For instance, an xGoT-G of 3.45 means that the goalkeeper prevented 3 to 4 more goals than expected, while a score of -4.34 indicates that the goalkeeper conceded 4 to 5 more goals than they should have, given the data-based difficulty of the shots.
What is the HSQ Performance Index?
Our Handball Skill Qualifier (HSQ) is a comprehensive performance index we’ve developed to evaluate player actions throughout the game. We track every action a player is involved in and calculate how each one impacts on the probability of scoring or conceding a goal, both in attack and defense. The player accumulates or loses points based on these actions, and ultimately, we generate an overall performance score, which we scale from 0 to 100.
The HSQ index is divided into four sub-index:
Defense: This accounts for all defensive actions, such as recoveries, offensive fouls, free throws and penalties and two-minute suspensions caused.
Attack: This sub-index evaluates offensive actions, including turnovers, offensive fouls committed, penalties caused, assists, successful 1-on-1s, and two-minute suspensions caused by the player.
Shooting: This measures shot quality based on the data-based difficulty. For example, it’s harder to score from the wing than from 6 meters at the center of the area, so scoring from the wing adds more points, while missing from an easier position deducts more. This is similar to the G-xG metric.
Global: This combines all the actions from the match, encompassing the previous three sub-index to provide an overall evaluation of the player's contribution to the game.
To further illustrate the explanation, we have attached part a real match report from the 2024/25 Champions League, specifically from Round 2 between FC Barcelona and PICK Szeged.
This is just a small part of what Servesthand can offer in terms of individual and team reports. For example, our reports always include accumulated data from the entire season, allowing us to track how the performance of the team or each player evolves over time, both in general and in specific aspects of the game. Attached is part of a report from a U-18 women's team. For confidentiality and data protection reasons, certain information has been redacted.
When it comes to goalkeeper reports, they are very comprehensive, including shot maps with their corresponding xGoT-G metrics by zone, as well as the evolution of their performance in different areas. Additionally, we provide a wide range of accumulated season data. For these reports, we use Steazzi's goal template as the foundation, since it is our primary tool for collecting this data. Attached is part of a goalkeeper report for a player in the U-18 category. For confidentiality and data protection reasons, certain information has been censored.
Finally, we will provide a small sample of what a rival analysis report created by Servesthand looks like. First, our team of analysts reviews key matches played by the opponent, and from there, they generate a detailed report. The example we will see corresponds to the analysis of the German U-18 women's team from the 2024 U-18 Handball World Championship in China.
Is there anything else you'd like to highlight or add?
We are always working on new ways to improve our product and innovate. Right now, we are developing predictive models that we will start testing this season with some of the teams we work with. Additionally, we have many ideas for future implementations, such as using video analysis to monitor player workload in order to prevent injuries.
We are also working on optimizing goalkeeper performance by managing their minutes based on previous actions, making data-driven decisions about penalty takers based on their performance, or determining the potential effectiveness of playing 7 vs. 6 against certain opponents—all of this thanks to statistical analysis.
We would like to emphasize the importance of a tool like Steazzi in our project. Steazzi, with all of its features, constantly helps us in collecting data quickly, easily, and efficiently. This allows us to later combine that data with our own database to generate the detailed reports we offer.
Finally, we invite you to explore our product in more detail on our website (in spanish), sites.google.com/servesthand.com/servesthand-es/inicio, or by contacting us at contacte@servesthand.com. We would be happy to speak with you, whether you're seeking more information or looking to hire our services for your team.