{"id":10152,"date":"2025-04-04T10:34:03","date_gmt":"2025-04-04T08:34:03","guid":{"rendered":"https:\/\/sites.hslu.ch\/applied-data-science\/?p=10152"},"modified":"2025-07-23T15:08:42","modified_gmt":"2025-07-23T13:08:42","slug":"tactics-meet-ai-when-algorithms-play-a-part-in-sport","status":"publish","type":"post","link":"https:\/\/sites.hslu.ch\/applied-data-science\/tactics-meet-ai-when-algorithms-play-a-part-in-sport\/","title":{"rendered":"Tactics Meet AI \u2013 When Algorithms Play a Part in Sport"},"content":{"rendered":"\n

Podcast: <\/strong>Applied Data Science UNBOXED<\/a>
Episode 7: <\/strong>Tactics meet AI – When Algorithms Play a Part in Sport<\/a> (German only)
Host:<\/strong> Fabio Sandmeier<\/a>
Guests:<\/strong> Martin Rumo<\/a> and Beat Suter, scoreTec<\/a><\/p>\n\n\n\n

Shortcuts:
Positioning<\/a> | Pressing<\/a> | Playmakers<\/a> | Tactics<\/a> | Translation<\/a> | Takeaway<\/a><\/p>\n\n\n\n

Host Fabio Sandmeier<\/strong> visits the small yet powerful sports analytics company scoreTec<\/strong>, run by Martin Rumo<\/strong> and Beat Suter<\/strong>, to learn how raw data becomes tactical intelligence. The answer? Not just clever algorithms, but also lots of coffee chats, flipcharts, and a deep understanding of the game.<\/p>\n\n\n\n

01:16 \u2013 XY Coordinates & Position Data: How Algorithms Read the Game<\/strong><\/h2>\n\n\n\n

At the heart of sport analytics lies tracking data: XY coordinates that pinpoint the position of each player and the ball on the field. However, scoreTec\u2019s work begins with this data, not for the numbers alone, but rather to understand the context behind them. <\/p>\n\n\n\n

That\u2019s why their workspace looks more like a strategy lab than a tech hub. Flipcharts, sketches, and printed match visuals dominate the room. A setup which reflects their core approach, translating game understanding into data structures.<\/p>\n\n\n\n

Listen to this part (01:16)<\/a><\/p>\n\n\n\n

03:09 \u2013 Pressing in Football: The Data Behind Pressure on the Ball<\/strong><\/h2>\n\n\n\n

One of the episode’s standout stories involves defining pressing. Coaches intuitively understand when and how pressure is applied during a match. However, translating that into data took time. A spontaneous coffee conversation finally brought clarity: pressing involves identifying the 2\u20133 nearest players and their speed toward the ball.<\/p>\n\n\n\n

This insight led to the development of a Pressing Index \u2013 a way to quantify pressure moments using tracking data and linear algebra. And most importantly, it helped answer a recurring question from coaches: Under how much pressure was a pass made?<\/em><\/p>\n\n\n\n

Listen to this part (03:09)<\/a><\/p>\n\n\n\n

06:13 \u2013 Playmakers in Ice Hockey: What Makes a True Playmaker?<\/strong><\/h2>\n\n\n\n

In another project, scoreTec worked with HC Davos to analyze the role of the playmaker in ice hockey. But what does be a playmaker actually mean?<\/p>\n\n\n\n

As a result of close collaboration, they defined a playmaker as someone who passes the puck into a better situation. Closer to the goal, with more speed and less defensive pressure. Using positional and performance data, they created metrics to identify these players and presented their findings at the Spengler Cup.<\/p>\n\n\n\n

Listen to this part (06:13)<\/a><\/p>\n\n\n\n

08:08 \u2013 From Game Philosophy to Data Pipeline: Making Tactics Measurable<\/strong><\/h2>\n\n\n\n

The Swiss Football Association provides a simple yet powerful framework: divide the game into four phases (in possession, losing possession, out of possession, regaining possession) and three zones (defensive third, midfield, attacking third). scoreTec uses this logic to structure their analytics pipeline.<\/p>\n\n\n\n

While the starting point is raw tracking data, they extract higher-value event data such as ball recoveries, passes, and transitions. These are visualized and made available to analysts, sometimes even live during the match, enabling coaches to make better decisions without spending sleepless nights with Excel.<\/p>\n\n\n\n

Listen to this part (08:08)<\/a><\/p>\n\n\n\n

12:20 \u2013 Analytics Translation in the IDS Master\u2019s Program: From Data to Answers<\/strong><\/h2>\n\n\n\n

These same methods are part of the curriculum in the MSc in Applied Information and Data Science (IDS) at Lucerne University of Applied Sciences and Arts. Martin Rumo teaches students how to build data pipelines, extract meaningful events, and above all ask the right questions.<\/p>\n\n\n\n

Moreover, in practical modules, students work with real experts like strength and conditioning coaches. Their task? To translate raw data into actionable insight. The secret is good listening, clear communication, and iterative co-creation.<\/p>\n\n\n\n

Listen to this part (12:20)<\/a><\/p>\n\n\n\n

Get the details for the Master’s programme “MSc in Applied Information and Data Science”<\/a><\/div>\n\n\n\n

<\/p>\n\n\n\n

Key Takeaway: Data Is Just the Beginning<\/strong><\/h2>\n\n\n\n

Ultimately, if this episode makes one thing clear: Data is not the goal, insight is. Great sports data analytics doesn\u2019t start with algorithms \u2013 it starts with the right question. And when tactics, data, and a touch of creativity come together, that\u2019s when the real magic happens.<\/p>\n\n\n\n

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