Public Race Data

Chicago Event Management

Chicago Event Management

Abdullah Kundi

Bib: 4264 β€’M β€’Age: 1

Chicago, IL

Chicago 13.1 logo
0:00
0:00
/ mi
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Overall
#0 / 3708
Gender (Male)
#0 / 1903
Age Group (M0-14)
#0 / 4
Race Day Weather
74Β°/64Β°F
scattered clouds

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

Start
0:00:00
Race begins
5K
34:40
3.11 mi
Rank: #3009
Start β†’ 5K
34:40 | 11:10/mi
8K
56:12
4.97 mi
Rank: #2972 (+37)
5K β†’ 8K
21:32 | 11:34/mi
10K
1:13:11
6.21 mi
Rank: #3159 (-187)
8K β†’ 10K
16:59 | 13:40/mi
15K
2:02:10
9.32 mi
Rank: #3349 (-190)
10K β†’ 15K
48:59 | 15:46/mi
FINISH
3:06:36
13.11 mi
Rank: #3545 (-196)
15K β†’ FINISH
1:04:26 | 17:01/mi

Splits & Pacing

Detailed breakdown of your race performance at each timing point

Checkpoint Splits

CheckpointDistanceTime of DayTimeAvg PaceSegment TimeSegment PaceDiff
5K
3.11 mi07:45:5634:4011:1034:40
11:10
-
8K
4.97 mi08:07:2856:1211:1921:32
11:34
+0:24
10K
6.21 mi08:24:271:13:1111:4716:59
13:40
+2:06
15K
9.32 mi09:13:262:02:1013:0748:59
15:46
+2:06
FINISH
13.11 mi10:17:523:06:3614:151:04:26
17:01
+1:15

Checkpoint Splits Visualizations

Explore your race data through different visual perspectives. Scroll to discover each visualization.

πŸ“ˆPace Line

Pace Progression

Track your pace changes throughout the race. Green = fastest, yellow = moderate, red = slowest segments.

Fastest Pace

11:10 /mi

Average Pace

13:23 /mi

Slowest Pace

17:01 /mi

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Fastest
Middle
Slowest
Average

πŸ“ŠSegments

Segment Time Comparison

Bar length shows time spent in each segment. Color indicates pace quality: green = fast pace, yellow = moderate, red = slow pace.

Time at Fast Pace

56:12

30% of race

Time at Moderate Pace

16:59

9% of race

Time at Slow Pace

1:53:25

61% of race

Average Pace: 14:14 /mi

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Fast pace (< avg)
Moderate pace (β‰ˆ avg)
Slow pace (> avg)

🎨Heatmap

Pace Heatmap

Visual intensity map of your pacing throughout the race. Green = fastest, yellow = moderate, red = slowest.

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0mi3.3mi6.6mi9.8mi13.1mi
Pace:
Fast
Moderate
Slow

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

CheckpointDistanceTime of DayTimeAvg PaceSegmentPaceTrendRank
5K
3.11 mi07:45:5634:4011:1034:40
11:10
#3009
8K
4.97 mi08:07:2856:1211:1921:32
11:34
#2972
10K
6.21 mi08:24:271:13:1111:4716:59
13:40
#3159
15K
9.32 mi09:13:262:02:1013:0748:59
15:46
#3349
FINISH
13.11 mi10:17:523:06:3614:151:04:26
17:01
#3545
Fast pace
Moderate pace
Slow pace

Rankings

Your position at each checkpoint and how you ranked in each segment

Checkpoint and Segment Rankings

CheckpointDistanceSeg. DistOverallMalesM0-14Seg. OverallSeg. MalesSeg. M0-14
5K3.11 mi3.11 mi3009169143512(Top 95%)1846(Top 97%)4(Top 100%)
8K4.97 mi1.86 mi2972+371673+1842944(Top 79%)1663(Top 87%)4(Top 100%)
10K6.21 mi1.24 mi3159-1871749-7643536(Top 95%)1864(Top 98%)4(Top 100%)
15K9.32 mi3.11 mi3349-1901803-5443512(Top 95%)1846(Top 97%)4(Top 100%)
FINISH13.11 mi3.79 mi3545-1961864-6143692(Top 100%)1900(Top 100%)4(Top 100%)

Passing

Athletes you passed and who passed you throughout the race

Passing Analysis

Category:
Athletes Passed
82
Passed By
618
Net Change
-536
SegmentAthletes PassedPassed ByNet ChangeStart RankEnd Rank
Start β†’ 5K----#3009
5K β†’ 8K7134+37#3009#2972
8K β†’ 10K0187-187#2972#3159
10K β†’ 15K10200-190#3159#3349
15K β†’ FINISH1197-196#3349#3545
TOTALS82618-536
πŸ“Š

Passing Analysis Visualizations

Explore your passing analysis through 5 different visualizations. Scroll to discover each one.

Time:
Category:

πŸ“ˆPosition Graph

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🎨Heatmap Timeline

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πŸ”„Passing Circle

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🌊Position Flow

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πŸƒRace Lanes

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Activity Data

Upload your GPX file to see detailed activity metrics

Upload your GPX file

Supports Garmin, Apple Watch, Polar, Suunto, COROS, Strava, and other apps

.gpx files up to 10MB

Export & Support

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Questions or issues regarding timing data?

If you notice any discrepancies in your timing data or have questions about your results, our support team can help.

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