Uwe Schmidt
Bib: 32830 β’M β’Age: 67
Rostock, Mecklenburg-Vorpommern

Race Timeline and Course Information
Your journey through the course with elevation, pacing, and checkpoint details
β±οΈ Race Timeline
Watch your race unfold from start to finish
Splits & Pacing
Detailed breakdown of your race performance at each timing point
Checkpoint Splits
| Checkpoint | Distance | Time of Day | Time | Avg Pace | Segment Time | Segment Pace | Diff |
|---|---|---|---|---|---|---|---|
5K | 3.11 mi | 07:33:17 | 33:17 | 10:43 | 33:17 | 10:43 | - |
10K | 6.21 mi | 08:07:03 | 1:07:03 | 10:48 | 33:46 | 10:53 | +0:10 |
15K | 9.32 mi | 08:41:44 | 1:41:44 | 10:55 | 34:41 | 11:10 | +0:17 |
20K | 12.43 mi | 09:18:40 | 2:18:40 | 11:10 | 36:56 | 11:54 | +0:44 |
FINISH | 13.11 mi | 10:45:27 | 3:45:27 | 17:12 | 1:26:47 | 127:19 | +115:25 |
Checkpoint Splits Visualizations
Explore your race data through different visual perspectives. Scroll to discover each visualization.
πPace Line
Pace Progression
Track your pace changes throughout the race. Dot colors mark your quickest to easiest segments, relative to your own pace.
Fastest Pace
10:43 /mi
Average Pace
17:12 /mi
Slowest Pace
127:19 /mi
πSegments
Segment Time Comparison
Bar length shows time spent in each segment. Colors mark your faster to slower segments, relative to your own pace.
Time at Faster Pace
0:00
0% of race
Time at Steady Pace
2:18:40
62% of race
Time at Slower Pace
1:26:47
38% of race
Average Pace: 17:12 /mi
π¨Heatmap
Pace Heatmap
Where you sped up and eased off relative to your own pace across the race. Colors are relative to your own range, not to other runners.
Click or hover over segments to see details
β¨Sparklines
Checkpoint Splits with Pace Trends
Enhanced split table showing pace trends through mini sparkline visualizations.
Overall Pace Trend
| Checkpoint | Distance | Time of Day | Time | Avg Pace | Segment | Pace | Trend | Rank |
|---|---|---|---|---|---|---|---|---|
5K | 3.11 mi | 07:33:17 | 33:17 | 10:43 | 33:17 | 10:43 | #22260 | |
10K | 6.21 mi | 08:07:03 | 1:07:03 | 10:48 | 33:46 | 10:53 | #22296 | |
15K | 9.32 mi | 08:41:44 | 1:41:44 | 10:55 | 34:41 | 11:10 | #22595 | |
20K | 12.43 mi | 09:18:40 | 2:18:40 | 11:10 | 36:56 | 11:54 | #23209 | |
FINISH | 13.11 mi | 10:45:27 | 3:45:27 | 17:12 | 1:26:47 | 127:19 | #23469 |
Rankings
Your position at each checkpoint and how you ranked in each segment
Checkpoint and Segment Rankings
| Checkpoint | Distance | Seg. Dist | Overall | Males | M65-69 | Seg. Overall | Seg. Males | Seg. M65-69 |
|---|---|---|---|---|---|---|---|---|
| 5K | 3.11 mi | 3.11 mi | 22260 | 12555 | 149 | 23208(Top 77%) | 12689(Top 85%) | 151(Top 64%) |
| 10K | 6.21 mi | 3.10 mi | 22296-36 | 12491+64 | 144+5 | 22384(Top 74%) | 12440(Top 84%) | 144(Top 61%) |
| 15K | 9.32 mi | 3.11 mi | 22595-299 | 12545-54 | 146-2 | 23208(Top 77%) | 12689(Top 85%) | 151(Top 64%) |
| 20K | 12.43 mi | 3.11 mi | 23209-614 | 12722-177 | 153-7 | 24499(Top 81%) | 13036(Top 88%) | 159(Top 67%) |
| FINISH | 13.11 mi | 0.68 mi | 23469-260 | 12904-182 | 163-10 | 22901(Top 76%) | 12585(Top 85%) | 182(Top 77%) |
Segment Performance Analysis
10Kβ15K
0.0 - 3.1 mi
Overall
23208
Males
12689
M65-69
151
5Kβ10K
3.1 - 6.2 mi
Overall
22384
Males
12440
M65-69
144
10Kβ15K
6.2 - 9.3 mi
Overall
23208
Males
12689
M65-69
151
15Kβ20K
9.3 - 12.4 mi
Overall
24499
Males
13036
M65-69
159
20KβFINISH
12.4 - 13.1 mi
Overall
22901
Males
12585
M65-69
182
Passing
Athletes you passed and who passed you throughout the race
Passing Analysis
| Segment | Athletes Passed | Passed By | Net Change | Start Rank | End Rank |
|---|---|---|---|---|---|
| Start β 5K | - | - | - | - | #22260 |
| 5K β 10K | 200 | 200 | -36 | #22260 | #22296 |
| 10K β 15K | 200 | 200 | -299 | #22296 | #22595 |
| 15K β 20K | 106 | 200 | -614 | #22595 | #23209 |
| 20K β FINISH | 200 | 200 | -260 | #23209 | #23469 |
| TOTALS | 706 | 800 | -1209 |
Passing Analysis Visualizations
Explore your passing analysis through 5 different visualizations. Scroll to discover each one.
πPosition Graph
π¨Heatmap Timeline
πPassing Circle
πPosition Flow
πRace Lanes
AI Key Insights
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