Analyzing race data is one of the most effective ways to improve performance, but it can be incredibly time-consuming—especially for teams with large rosters. Instead of spending hours reviewing every swimmer’s race, coaches can crowdsource the effort, allowing swimmers to take an active role in their own improvement.
Not only does this lighten the workload, but swimmers who analyze their own races gain a deeper understanding of race strategy, technique, and performance optimization. This guide outlines how to implement a team-wide approach to race analysis using Swimcloud.
Step 1: Set Clear Expectations for Race Analysis
Before assigning swimmers to analyze their own (or each other’s) races, establish the why and how:
- Why it matters: Swimmers will learn more by seeing their races broken down frame by frame.
- How it helps: Athletes will be able to identify trends, compare past performances, and make informed adjustments to their strategy.
- What to focus on: Emphasize key elements such as underwater velocity, surface speed, stroke efficiency, and turn transitions rather than getting lost in too many details.
Step 2: Assign Responsibility in a Structured Way
Instead of reviewing every race yourself, assign swimmers to analyze their own races or work in small groups to analyze each other’s races. Here are a few different models:
1. Self-Analysis Model
- Each swimmer is responsible for analyzing their own race using Swimcloud.
- Coaches provide a checklist of key takeaways to focus on.
- Swimmers submit a brief summary of what they learned.
2. Buddy System Model
- Swimmers pair up and analyze each other’s races.
- This allows for a second set of eyes to confirm accuracy and provide additional insights.
3. Group Analysis Model
- Small groups (3–5 swimmers) analyze a race together and present their findings.
- Works well as a team-building exercise while reinforcing race strategies.
4. Leadership Model
- Upperclassmen or captains take on the responsibility of helping younger swimmers analyze their races.
- This encourages mentorship and reinforces technical understanding.
Step 3: Provide a Simple & Repeatable Process
Swimcloud makes race analysis efficient, but swimmers need guidance on how to approach it effectively. Instead of overwhelming them with technical steps, focus on identifying key race moments and summarizing takeaways.
- Swimmers should not just press buttons and move on—they should look at trends.
- Encourage them to think critically:
- Did I maintain my underwater speed throughout the race?
- Did my stroke rate slow down too much in the second half?
- Was my turn transition time consistent?
- Keeping the focus on a few key improvements per race will help prevent information overload.
Step 4: Build Race Analysis into Practice Culture
For this method to work, race analysis needs to become a habit, not an occasional task. Here’s how to integrate it into team culture:
- Set a deadline for swimmers to analyze their race after each meet (e.g., by the next practice).
- Use practice time for discussion—review key takeaways as a team.
- Reward participation—acknowledge those who actively engage in analysis and apply what they learn.
- Make it a competition—who improves their turn transitions the most? Who finds the best balance between stroke rate and distance per cycle?
Step 5: Monitor & Provide Feedback Efficiently
Coaches don’t need to review every race—just spot-check a few to ensure accuracy and provide general feedback. A few ways to do this efficiently:
- Highlight strong examples of good analysis for others to learn from.
- Ask swimmers to submit one key takeaway rather than a detailed report.
- Rotate focus areas—one week, analyze turns; the next, focus on stroke rate.
The Bottom Line: Swimmers Learn More by Doing
By involving swimmers in the race analysis process, you save time while also helping them develop a deeper understanding of their races. Rather than just being told what to fix, they learn to identify problems, recognize trends, and take ownership of their own development.
The more swimmers engage in their own analysis, the more they will improve—both in knowledge and performance.