Turning Garmin running data into coaching insight with Claude

My friend is a competitive runner who wears a Garmin watch for every session. Each run produces a spreadsheet's worth of data: pace, heart rate, cadence, ground contact time, vertical oscillation, and power, broken down lap by lap. Garmin Connect shows the numbers but can't explain them. It can't tell him whether a late pace drop came from fatigue, wind, or a hill, or whether his fitness is really improving. I built Stride to add that meaning for runners who already have the data. 1. Export a CSV from Garmin and drop it into Stride. 2. Stride runs sports-science style analysis. Aerobic fitness tracks heart rate within each pace band week over week, so a lower heart rate at the same pace signals improving fitness. 3. It monitors training load ratio for signs that volume is rising too quickly. 4. It builds a running economy score from form metrics. 5. It watches left/right ground contact balance, since a steady drift away from 50/50 can be an early warning sign. 6. The Environment layer adds weather and elevation, so a slow lap into a headwind is judged fairly. 7. AI Coach sends a structured 30-day summary to Claude, which returns a plain-English brief on trends, environmental factors, and things to watch. 8. What-If answers questions grounded in his own data, such as his likely 5K time on a flat, windless course or what pace to target if race day hits 25 degrees C. The result is less time staring at numbers and more time running with purpose. Stride stops short of medical advice or prescribed training plans. It delivers the insight, and the runner and his coach make the decisions. Note: the screenshots use a 60-day synthetic demo profile, so all numbers are illustrative.