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Rider Self-Testing Case Study: Anna Kiesenhofer

Rider Self-Testing Case Study: Anna Kiesenhofer

Posted on February 19, 2026


Anna Kiesenhofer — Olympic gold medallist in the Tokyo 2020 road race and a mathematician by training — is no stranger to the pursuit of marginal gains. In October 2025, she took delivery of a Streamlines aerodynamic testing system at her base in Switzerland's Rhône valley, aiming to optimise her time trial setup ahead of the 2026 season.

The equipment arrived on 22 October: a Streamlines Forma body position sensor and Altostratus wind probe, along with a custom carbon mounting plate. Anna rides a Pinarello Bolide time trial bike, and the first challenge was finding a clean way to fix the sensor beneath the aerobars. Over a couple of days of back-and-forth with the Streamlines team — mounting options, laser alignment, data field checks on her Garmin — she had the unit dialled in and ready to go.

Her testing course ran along a straight valley road flanked by vineyards and orchards, with autumn colours on the hillsides and snow-capped Alps in the distance. The course measured roughly 1 km between gates with just 1.3 m of elevation change — close to flat, but a real road with real traffic, real weather, and none of the controlled calm conditions of a wind tunnel.

That last point mattered. Anna's first session on 24 October had mild wind of about 7 km/h, with yaw angles around 3–4 degrees. It had been raining in the days before, and the roads were only just drying out. Despite the conditions, the system delivered. Comparing her baseline wheel against a second front wheel option, it measured a CdA difference of 0.004 — equivalent to roughly 4 watts at 45 kph. The repeats were conclusive: the standard deviation across traverse pairs was just 0.0018, giving a coefficient of variation of 1.09%.

Her second session on 28 October tested three configurations — baseline, an alternative front wheel, and a DT Swiss 62 — again in breezy conditions with wind up to 7 km/h. The results were even tighter: a CV of 1.03% with the same standard deviation of 0.0018. The system was able to distinguish differences as small as 1 watt between wheel setups.

Over the following weeks, Anna ran a total of eight testing sessions, exploring not just wheel choices but also helmet comparisons, body position variations, and even the effect of cadence on her aerodynamic drag. Across all sessions, the pooled standard deviation was 0.0017 and the pooled typical error just 0.0012 — remarkable consistency for outdoor testing, especially as a first timer.

What stood out was how naturally the testing slotted into her routine. Anna set up the equipment herself with remote support via WhatsApp, ran sessions solo on a public road with occasional traffic, and uploaded results in real time via her phone's hotspot. There were the usual small adventures — figuring out the logging button, sorting out a data SIM, adjusting the Forma angle to properly track her head position — but the learning curve was short.

As Anna herself noted, the system let her test positions she had always struggled to replicate in a wind tunnel. In the tunnel you hold a position for a few seconds at a time; on the road with Streamlines, she could ride naturally over repeated kilometre-long efforts and see which positions genuinely held up over distance. 

By mid-November, with winter closing in on the valley, Anna wrapped up testing for the year. She shipped the aero probe back and kept a Forma body position sensor to continue monitoring her position through the off-season. Her verdict: incredibly insightful, and she is keen to pick up testing again in spring.

Aero Reports:

https://html.streamlinesaero.com/Report_Anna_-_24-10-2025.html

https://html.streamlinesaero.com/Report_Anna_-_28-10-2025.html

Combined Statistics Report:

https://html.streamlinesaero.com/anna-kiesenhofer-statistics-report.html

Aero Sensor Aerodynamics Anna Kiesenhofer Cycling Cycling technology FORMA performance pro cycling

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