Kyong Do Pang
Bib: 1204 •M •Age: 70
Chicago, IL
Race Timeline and Course Information
Your journey through the course with elevation, pacing, and checkpoint details
⏱️ 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 | 07:44:09 | 32:17 | 10:24 | 32:17 | 10:24 | - |
8K | 4.97 mi | 08:03:03 | 51:11 | 10:18 | 18:54 | 10:09 | -0:15 |
10K | 6.21 mi | 08:15:45 | 1:03:53 | 10:17 | 12:42 | 10:14 | +0:05 |
15K | 9.32 mi | 08:47:38 | 1:35:46 | 10:17 | 31:53 | 10:16 | +0:02 |
FINISH | 13.11 mi | 09:25:55 | 2:14:03 | 10:14 | 38:17 | 10:07 | -0:09 |
Checkpoint Splits Visualizations
Explore your race data through different visual perspectives. Scroll to discover each visualization.
📈Pace 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
10:07 /mi
Average Pace
10:14 /mi
Slowest Pace
10:24 /mi
📊Segments
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
2:14:03
100% of race
Time at Steady Pace
0:00
0% of race
Time at Slower Pace
0:00
0% of race
Average Pace: 10:14 /mi
🎨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
✨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 | 07:44:09 | 32:17 | 10:24 | 32:17 | 10:24 | #4909 | |
8K | 4.97 mi | 08:03:03 | 51:11 | 10:18 | 18:54 | 10:09 | #4729 | |
10K | 6.21 mi | 08:15:45 | 1:03:53 | 10:17 | 12:42 | 10:14 | #4612 | |
15K | 9.32 mi | 08:47:38 | 1:35:46 | 10:17 | 31:53 | 10:16 | #4347 | |
FINISH | 13.11 mi | 09:25:55 | 2:14:03 | 10:14 | 38:17 | 10:07 | #4086 |
Rankings
Your position at each checkpoint and how you ranked in each segment
Checkpoint and Segment Rankings
| Checkpoint | Distance | Seg. Dist | Overall | Males | M70-74 | Seg. Overall | Seg. Males | Seg. M70-74 |
|---|---|---|---|---|---|---|---|---|
| 5K | 3.11 mi | 3.11 mi | 4909 | 3018 | 7 | 3975(Top 50%) | 2596(Top 65%) | 6(Top 40%) |
| 8K | 4.97 mi | 1.86 mi | 4729+180 | 2956+62 | 7 | 4497(Top 57%) | 2862(Top 72%) | 6(Top 40%) |
| 10K | 6.21 mi | 1.24 mi | 4612+117 | 2918+38 | 7 | 4280(Top 54%) | 2780(Top 70%) | 6(Top 40%) |
| 15K | 9.32 mi | 3.11 mi | 4347+265 | 2798+120 | 6+1 | 3975(Top 50%) | 2596(Top 65%) | 6(Top 40%) |
| FINISH | 13.11 mi | 3.79 mi | 4086+261 | 2645+153 | 6 | 3577(Top 45%) | 2344(Top 59%) | 5(Top 33%) |
Segment Performance Analysis
10K→15K
0.0 - 3.1 mi
Overall
3975
Males
2596
M70-74
6
5K→8K
3.1 - 5.0 mi
Overall
4497
Males
2862
M70-74
6
8K→10K
5.0 - 6.2 mi
Overall
4280
Males
2780
M70-74
6
10K→15K
6.2 - 9.3 mi
Overall
3975
Males
2596
M70-74
6
15K→FINISH
9.3 - 13.1 mi
Overall
3577
Males
2344
M70-74
5
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 → 5K | - | - | - | - | #4909 |
| 5K → 8K | 214* | 34 | +180 | #4909 | #4729 |
| 8K → 10K | 141 | 24 | +117 | #4729 | #4612 |
| 10K → 15K | 304* | 39 | +265 | #4612 | #4347 |
| 15K → FINISH | 305* | 44 | +261 | #4347 | #4086 |
| TOTALS | 964* | 141 | +823 |
* Includes athletes who did not complete a segment (DNF/DNQ).
Passing Analysis Visualizations
Explore your passing analysis through 5 different visualizations. Scroll to discover each one.
📈Position Graph
🎨Heatmap Timeline
🔄Passing Circle
🌊Position Flow
🏃Race Lanes
Activity Data
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Export & Support
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Questions or issues regarding timing data?
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