Public Race Data
Enhanced athlete results built from publicly available data.
Race managed by
Chicago Event Management
Megan Goril
Bib: 2838 •F •Age: 35
Westmont, 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 | 07:49:05 | 27:50 | 8:58 | 27:50 | 8:58 | - |
8K | 4.97 mi | 08:06:15 | 45:00 | 9:04 | 17:10 | 9:13 | +0:15 |
10K | 6.21 mi | 08:17:38 | 56:23 | 9:05 | 11:23 | 9:10 | -0:03 |
15K | 9.32 mi | 08:51:50 | 1:30:35 | 9:44 | 34:12 | 11:01 | +1:51 |
FINISH | 13.11 mi | 09:34:30 | 2:13:15 | 10:10 | 42:40 | 11:16 | +0:15 |
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
8:58 /mi
Average Pace
10:10 /mi
Slowest Pace
11:16 /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
0:00
0% of race
Time at Steady Pace
56:23
42% of race
Time at Slower Pace
1:16:52
58% of race
Average Pace: 10:10 /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 | 07:49:05 | 27:50 | 8:58 | 27:50 | 8:58 | #2090 | |
8K | 4.97 mi | 08:06:15 | 45:00 | 9:04 | 17:10 | 9:13 | #2108 | |
10K | 6.21 mi | 08:17:38 | 56:23 | 9:05 | 11:23 | 9:10 | #2174 | |
15K | 9.32 mi | 08:51:50 | 1:30:35 | 9:44 | 34:12 | 11:01 | #2741 | |
FINISH | 13.11 mi | 09:34:30 | 2:13:15 | 10:10 | 42:40 | 11:16 | #3088 |
Rankings
Your position at each checkpoint and how you ranked in each segment
Checkpoint and Segment Rankings
| Checkpoint | Distance | Seg. Dist | Overall | Females | F35-39 | Seg. Overall | Seg. Females | Seg. F35-39 |
|---|---|---|---|---|---|---|---|---|
| 5K | 3.11 mi | 3.11 mi | 2090 | 601 | 84 | 3717(Top 57%) | 1446(Top 44%) | 213(Top 47%) |
| 8K | 4.97 mi | 1.86 mi | 2108-18 | 619-18 | 93-9 | 2188(Top 34%) | 644(Top 20%) | 98(Top 22%) |
| 10K | 6.21 mi | 1.24 mi | 2174-66 | 652-33 | 97-4 | 2440(Top 38%) | 759(Top 23%) | 121(Top 27%) |
| 15K | 9.32 mi | 3.11 mi | 2741-567 | 898-246 | 134-37 | 3717(Top 57%) | 1446(Top 44%) | 213(Top 47%) |
| FINISH | 13.11 mi | 3.79 mi | 3088-347 | 1102-204 | 161-27 | 3781(Top 58%) | 1565(Top 48%) | 228(Top 50%) |
Segment Performance Analysis
10K→15K
0.0 - 3.1 mi
Overall
3717
Females
1446
F35-39
213
5K→8K
3.1 - 5.0 mi
Overall
2188
Females
644
F35-39
98
8K→10K
5.0 - 6.2 mi
Overall
2440
Females
759
F35-39
121
10K→15K
6.2 - 9.3 mi
Overall
3717
Females
1446
F35-39
213
15K→FINISH
9.3 - 13.1 mi
Overall
3781
Females
1565
F35-39
228
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 | - | - | - | - | #2090 |
| 5K → 8K | 73 | 91 | -18 | #2090 | #2108 |
| 8K → 10K | 22 | 88 | -66 | #2108 | #2174 |
| 10K → 15K | 13 | 200 | -567 | #2174 | #2741 |
| 15K → FINISH | 31 | 200 | -347 | #2741 | #3088 |
| TOTALS | 139 | 579 | -998 |
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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