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US Soccer – Applying analytics to influence performance and selection

By: Stats Perform

“There’s a new guard coming in; when they played the game or started coaching, analytics was already here so they’re much more comfortable and familiar with the approach.”

Ross Moses, U.S. Soccer’s Director of Analytics and Research, shares insight on how the federation applies data and analytics to influence performance and selection.

The soccer analytics field has made many strides in the last few years and continues to evolve as it becomes a more accepted and important part the game. U.S. Soccer represents one of the country’s leaders when it comes to innovation and using data analytics across various initiatives.

It is this strive for innovation that led to U.S. Soccer organising the country’s first soccer-focused hackathon. A two-day event that took place in Chicago over the weekend of the 2018 World Cup final, the U.S. Soccer hackathon brought together 140 people who had two things in common– a love of data, and a love of soccer.

The event tasked participants across both commercial and performance data tracks. As U.S. Soccer’s official Live Match Data Provider, a vast breadth of Opta performance data across both domestic and international competition was made available.

Speaking at the event itself, Ross Moses, Director of Analytics and Research at U.S. Soccer said: “This is about developing and sharing new ideas to challenge how we measure and present what happens on and off the field. There’s a lot of undiscovered territory in soccer analytics, obviously more so than sports like baseball and basketball. So, we’re going to democratise the data for 24 hours and let those smart folks try to hack some ideas and problems in and around the sport.”

One of the key goals for U.S. Soccer here was to expand and progress the thinking within this industry as a whole and how it applies data to address on-field questions. With other North American sports further along their analytics journey, this has been a significant stepping stone in this process for not only U.S. Soccer, but the wider soccer analytics community.

More information on the hackathon can be found here.

The hackathon provided a great opportunity for U.S. Soccer to go beyond the traditional soccer bubble, and engage new minds to work with this vast quantity of data.

Commitment to a long term strategy

U.S. Soccer has undergone significant change in the recent past. While those on the outside may not have an appreciation for the volume and quality of work that goes on behind the scenes, U.S. Soccer’s work beyond the pitch demonstrates a long-term commitment to not only fielding the strongest teams, but to also ensure there’s a validated, considered process in the selection and development of the country’s wide range of players.

At the start of this process is the U.S. Soccer Development Academy (DA). Across the country, over 2,000 boys and girls’ matches are being captured at youth level. For the first time, U.S. Soccer can quantify what is happening on the pitch.

This innovation better connects U.S. Soccer with player performance across the country, providing fresh, objective insights on how the game is played at this level.

Discussing this initiative, Moses said: “Providing data up and down the country gives us not only a better understanding of how the game is played at this level, but also creates a feedback loop back to scouts and the clubs, which can inform coaching decisions.”

As well as near-immediate player development, the initiative will also inform U.S. Soccer’s player pathway strategy.

“In the long term we’re excited about this coming to life. We’ll be looking at national team players and understanding what a typical national team player looks like and what they can do at a positional level. Here’s what they tend to look like at 15, 16, 17, and we can build out a literal profile of players we should be looking at within this age group. It will have significant payoff in terms of our scouting efficiency given the size of the youth soccer population in the U.S.”

“There is an emphasis on centralising and integrating data across the entirety of U.S. Soccer, as this informs how we holistically analyse soccer.”

Creating an analytics culture

The integration of analytical processes and structures within an organisation is adamant to extracting the most value from raw data.

Having undertaken such a large-scale project, there is even more of an importance and emphasis to ensure all systems and structures are in place to facilitate objectives within U.S. Soccer.

“There is an emphasis on centralising and integrating data across the entirety of U.S. Soccer (covering both the business and performance side) as this informs how we holistically analyse soccer,” added Moses.

“We have data architects and engineers focused on warehousing the data. This will include Opta data as well as other sources such as GPS. Proactively modeling all of our data allows us to reduce our data prep time and create engaging front end applications that can meet the specific needs of the federation, meaning the team can maximise the time spent on actual analysis.”

The process of data collection across so many levels and the work behind this central storage space has allowed the growing data science team at U.S. Soccer to focus on detailed analysis. They’ve become more integrated with the technical staff, both from a talent ID and coaching perspective.

On the performance side, there is a combination of delivering reports, along with reactive requests from coaches that is balanced by innovative, proactive work from Moses’ team.

“Different coaches want different things. Some want complexity reduced to a minimum, but others are more engaged in the methodology behind it and also like to think in this way.

“Coaches, in general, don’t get a lot of credit for this, and I think things are changing pretty quickly. There’s a new guard coming in; when they played the game or started coaching, analytics was already here so they’re much more comfortable and familiar with the approach. As this group rises, analytics becomes more integrated within the process. We’re at a really positive point in the analytics transformation where organization and prioritization is absolutely critical in order to keep up with the technical staffs’ and leadership’s appetite for more objective insights.”

Integrating qualitative and quantitative data

Despite a recent emphasis on the analytical approach to analysing the game, this hasn’t come at the expense of traditional scouting. In fact, the synergy between the two is what leads to an optimised holistic decision-making strategy around the game. U.S. Soccer has recently paved the way for a more centralised solution for its extensive scouting network, allowing the federation to align subjective reports and expert information alongside Opta data.

Discussing this side of things, Moses states that, “Analytics and traditional scouting work in tandem to lend missing context to one another, so you have to use all of this information together.

“Metrics and models should mostly line-up with our eyes, but there should be a small percentage showing us something new, and this is the same in reverse. We can use data to evaluate scouting, by going back and looking at player development. The players we identify early, how are these players progressing in their careers? Are we missing things? Do we need to change the things we are looking for? This new process allows us to address these questions.”

U.S. Soccer faces the same challenges as others around the world – both at club and international level. Their unique, innovative and proactive approach has, in the short term, created a solid foundation for the future. The OptaPro partnership, from youth to senior data collection, and the tools provided for data analysts and performance scouts alike, has supported a structure that will nurture player performance across the region and optimize selection of the country’s best players.