Editorial illustration for US and Germany use data to map bobsled tracks and fix performance gaps
AI Transforms Olympic Speedskating Performance Tactics
US and Germany use data to map bobsled tracks and fix performance gaps
Winter sport isn’t just about raw power; it’s about precision down a curve measured in milliseconds. While sleds slice through ice at 90 km/h, athletes and engineers spend months dissecting every turn, looking for the slimmest edge. That’s why data has become a quiet competitor in the race for medals.
Nations such as Canada and Japan have already rolled out sensor suites and video analytics to fine‑tune their runs, yet a handful of programs are pushing the envelope further. In the weeks leading up to the Beijing Games, the United States and Germany turned to cloud‑based platforms to turn raw telemetry into actionable insight. Their goal?
To translate split‑second variations into concrete adjustments that close the gap between a podium finish and a mid‑field result. The US Bobsleigh and Skeleton Federation’s recent collaboration with Snowflake exemplifies this shift, aiming to map each track segment and pinpoint performance weaknesses before athletes ever step onto the ice.
The US and Germany are also ahead of the curve when it comes to their focus on leveraging data to help athletes map their tracks and remedy weaknesses in their performance. Prior to this year's Games, the US Bobsleigh and Skeleton Federation partnered with a company called Snowflake to leverage the company's AI tools to analyze data and make changes to bobbers' movements on the track. Snowflake's AI allowed coaches to identify which push pairings worked best for two- and four-person crews. It also analyzed performance inefficiencies with a focus on any bumping between athletes during the jump phase--the moment in which team members board the bobsled after the push.
Will the data‑driven approach narrow the margins that have long defined bobsleigh? The United States and Germany have turned to analytics, mapping every curve and straightaway with a level of detail previously reserved for motorsports. Partnering with Snowflake, the US Bobsleigh and Skeleton Federation has begun aggregating sensor feeds, video, and telemetry to pinpoint where athletes lose time.
Germany follows a similar path, though the specifics of its data pipeline remain less public. At the 2026 Milano‑Cortina Games, teams will also experiment with AI‑guided footwear and braking systems, each tweak promising incremental gains. Yet the sport still hinges on raw power and split‑second decisions; whether these digital tools translate into podium finishes is still unclear.
The focus on data reflects a broader shift toward quantifying performance, but the ultimate test will be on the ice, where gravity and g‑forces still dominate. Only the results from the upcoming races will reveal how much the numbers improve the human element.
Further Reading
- Honda Documentary Offers Behind-the-Scenes Look at Innovative Partnership with USA Bobsled/Skeleton During Olympic Winter Games Milano Cortina 2026 - PR Newswire
- Greater safety in bobsleigh: ducking your head and holding on tight ... - Allianz
- 2026 Winter Olympics live updates: Mikaela Shiffrin aims for a return ... - NBC Olympics
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Common Questions Answered
How is the Slippery Fish AI app helping U.S. speedskaters improve their performance?
The Slippery Fish app allows coaches to upload images of athletes on the ice and create digital avatars to simulate how different postures affect airflow and drag. This technology enables the team to quickly test and validate potential position changes that previously would have taken weeks to assess, essentially creating a 'wind tunnel in your pocket' for speedskating aerodynamics.
What AI partnership did USA Bobsled/Skeleton recently establish?
USA Bobsled/Skeleton partnered with Snowflake, an AI data cloud company, to leverage advanced data intelligence for performance optimization. The partnership aims to use AI to support athletes, optimize sled technology, and enhance strategic decision-making by analyzing push combinations and deconstructing start motions with sophisticated data analytics.
How has AI changed the traditional approach to gathering aerodynamic data in speedskating?
Previously, athletes would have to fly across the country to wind tunnels and maintain static positions to gather aerodynamic data, which was time-consuming and expensive. With the new AI-powered Slippery Fish app, coaches can now upload images and quickly simulate different postures, reducing the process from weeks to just a single day of analysis and validation.