Usingin-depth performance metrics to unlock individual efficiency in elite rowing
When it comes to winning races, milliseconds matter and every stroke counts. For rowing coaches, one of the most difficult tactical challenges is determining the optimal stroke rate across each segment of a race. Too high, and athletes risk burning out before the finish line. Too low, and they leave valuable speed untapped.
Traditionally, these decisions have been made using gut instinct, stopwatch splits, and visual observation. But even the best coach can't spot the exact moment where a higher stroke rate stops delivering more speed. That's where data comes in. We partnered with a top-level rowing team to analyze the stroke efficiency of a U23 single sculler preparing for the national championship.
The Problem: When is a higher stroke rate actually hurting speed?
The athlete had strong physical capacity and technical skills, yet race results didn't match training performance. The coaching staff suspected pacing issues, either starting too fast or failing to find the most efficient cadence mid-race.
They wanted answers to a few key questions:
- At what stroke rate does the athlete generate the most boat speed per effort?
- Is the stroke rate in the middle 1,000 meters sustainable and effective, or inefficient?
- Could a different rate strategy lead to better performance with the same energy output?
The Setup: Capturing a full picture of rowing performance
We equipped the athlete's boat with our performance sensor suite, capturing high-resolution data for every stroke. Metrics included:
- Stroke rate (spm)
- Boat speed (m/s)
- Distance per stroke
- eWPS (effective Work Per Stroke)
- Drive vs. recovery time ratio
- Acceleration and deceleration curves per stroke
- Boat check (deceleration after the drive phase)
- Steering deviation
- Live video with synchronized overlays
Two full 2000-meter race simulations were recorded. One followed a baseline race strategy targeting a steady mid-race cadence of 35 spm. The second used an adjusted plan with a slightly lower mid-race rate and a controlled sprint finish.
The Analysis: Where stroke rate and efficiency started to diverge
Once we visualized the data, a clear pattern emerged. In the baseline race, the athlete began to lose efficiency shortly after the first 500 meters.
Key observations
- At 35 spm, boat speed plateaued at approximately 4.5 m/s
- Distance per stroke dropped after 800 meters, signaling reduced effectiveness
- The drive-to-recovery ratio shifted toward shorter recovery, indicating fatigue
- eWPS began to decline during the mid-race phase, meaning the strokes became less effective and thus slowing the boat down
- Acceleration curves showed uneven force application, especially under fatigue
- Boat check increased, confirming energy was being lost between strokes
The data confirmed what the coach suspected. The athlete was working harder but getting less out of each stroke.
The Solution: Lowering stroke rate to optimize for eWPS
With this insight, the coaching team revised the race plan:
- Start Phase (0 to 500m): Aggressive build of speed. Stroke rate peaking at 40 spm, unchanged
- Mid Phase (500 to 1500m): Controlled rate at 32 spm with a focus on distance per stroke and a balanced drive/recovery rhythm
- Sprint Phase (last 500m): Raise to 38 spm with targeted acceleration and technical control
In the adjusted race piece
- Boat speed in the mid-race increased by approximately 0.15 m/s despite the lower stroke rate
- Boat speed could be held at a steady level throughout the race
- Distance per stroke increased by 13 percent
- eWPS increased by 20 percent, indicating each stroke was more effective
- Acceleration profiles were more consistent, showing smoother power transfer
- Boat check was reduced, contributing to better glide between strokes
- The athlete reported lower perceived effort and maintained energy for a stronger final sprint
Data-driven feedback makes technical coaching more impactful
Using the synchronized video with real-time overlays, the coach and athlete reviewed each phase of the race side-by-side. Seeing the link between lower stroke rate and improved eWPS helped the athlete understand the value of strategic pacing. Beyond the strategy change, data revealed technical opportunities as well. Inconsistencies in drive-to-recovery timing and fluctuating deceleration curves became specific coaching points for the next training cycle.
What this means for coaches
This case study illustrates a key lesson. More strokes per minute do not always lead to more speed. With objective data, coaches can move beyond assumptions and:
- Tailor pacing strategies to an individual athlete's physiology and technique
- Spot early signs of fatigue-related breakdowns in stroke mechanics
- Train athletes to focus on work quality over stroke quantity
- Use data to build athlete trust and reinforce strategic changes
Every race is made of strokes. Make each one count with the power of data.
Interested in optimizing your team's performance? Contact us to schedule a demo.
