Road Race Stats - Marathons & Other Running Races

Monday, October 10, 2005

Chicago Marathon Stats

I've put together the stats for the top 2000 runners in yesterday's Chicago Marathon. The top 3 men and top 2 women finished close and made it an exciting race. Here are excerpts from Reuters:


Kenyan Felix Limo won the Chicago Marathon on Sunday in his debut appearance on the course, beating defending champion and compatriot Evans Rutto.

The 25-year-old Limo, who led a Kenyan clean sweep in a time of 2:07:04, won marathons in Rotterdam and Berlin in 2004.

Benjamin Maiyo was second in 2:07:11, three seconds ahead of Daniel Njenga. Rutto, who won the Chicago race in the last two years, was fourth in 2:07:30.

...

American Deena Kastor, 32, an Olympic bronze medallist, won the women's race, finishing in 2:21:24 for her first major marathon victory.

Defending champion Constantina Tomescu-Dita, of Romania, placed second, at 2:21:29, and Masako Chiba of Japan was third in 2:25:59.

More extensive race results are available at Chicago Sun-Times. This Chicago Sun-Times article also has some additional race highlights. It includes some of the celebrities who run including Kristin Armstrong, the ex-wife of Lance Armstrong, who finished in 3:37:53. The former San Francisco 49er Roger Craig finished in 3:51:08. Finally, Jennifer Wilbanks, the "Runaway Bride" was reported to have entered. As you might expect, she was a no-show. She didn't appear in the results.

Except for the wind, the weather seemed good for a marathon. At 7:53am, the temperature was 52° F with winds of 9mph and mostly cloudy skies. The temperature remained cool. At 10:53am it was still 56° F with 14mph winds and scattered clouds.

For the statistics, I had wanted to include more than the top 2000 runners, but the web database didn't make this easy. You can tell this is one of the world's top marathons by the number of fast times. There were 623 men and 47 women who ran under 3:00. Most marathons don't even have this many runners in the entire race.

The fastest age group was the 20s for the men and the 30s for the women. The 20s men were over 5 minutes faster than the 30s men. This seems larger than I've noticed in other marathons. Perhaps, this is due to only having the top 2000 runners. The 30s women were almost 3 minutes faster than the 20s women. I wonder why 20s women aren't the fastest age group like the men.

As you would expect for a major marathon, it attracted runners from around the country and the world. Out of the top 2000 runners, 89% were from outside Chicago and 75% outside Illinois, and 15% of the runners were from outside the US.

The fastest state was Massachusetts which had 71 runners with an average time of 2:55:53. The fastest city was Boulder Colorado with 22 runners with an average time of 2:43:42. However, it should be noted that many of the top runners from Kenya and elsewhere must use Coloroda and Massachusetts for training. Many of the top runners list Concord Massachusetts and Boulder Colorado as their city and state.

The below stats are based on results listed at the Lasalle Bank Chicago Marathon 2005 searchable results page.

Total Runners by Times

under 2:302:30 to 2:452:45 to 3:00over 3:00
55 (3%)147 (7%)468 (23%)1330 (67%)


Male Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.

Agesunder 2:302:30 to 2:452:45 to 3:00over 3:00
-under 200 (0%)0 (0%)2 (11%)16 (89%)
20s33 (6%)60 (12%)148 (29%)270 (53%)
30s14 (2%)52 (7%)162 (23%)481 (68%)
40s0 (0%)28 (6%)111 (24%)324 (70%)
50s0 (0%)0 (0%)10 (12%)71 (88%)
60s0 (0%)0 (0%)1 (20%)4 (80%)
unknown2 (100%)0 (0%)0 (0%)0 (0%)
Total49 (3%)140 (8%)434 (24%)1166 (65%)


Female Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.

Agesunder 2:302:30 to 2:452:45 to 3:00over 3:00
-under 200 (0%)0 (0%)0 (0%)1 (100%)
20s2 (2%)2 (2%)10 (11%)74 (84%)
30s3 (3%)5 (5%)19 (19%)74 (73%)
40s1 (5%)0 (0%)5 (25%)14 (70%)
50s0 (0%)0 (0%)0 (0%)1 (100%)
Total6 (3%)7 (3%)34 (16%)164 (78%)


Average/Best Times By Age Groups (Male and Female)

AgesNumberPercentMean TimeBest Time
-under 20191%3:07:432:49:14
20s59930%2:59:192:07:02
30s81041%3:03:122:10:53
40s48324%3:04:532:28:40
50s824%3:08:472:48:01
60s50%3:06:412:59:07
unknown20%2:18:242:12:44
Total2000100%3:02:412:07:02
Fastest Ages (by average)
20s59930%2:59:192:07:02


Average/Best Times By Male Age Groups

AgesNumberPercentMean TimeBest Time
-under 20181%3:07:212:49:14
20s51129%2:57:572:07:02
30s70940%3:03:012:10:53
40s46326%3:04:522:31:23
50s815%3:08:402:48:01
60s50%3:06:412:59:07
unknown20%2:18:242:12:44
Total1789100%3:02:192:07:02
Fastest Ages (by average)
20s51129%2:57:572:07:02


Average/Best Times By Female Age Groups

AgesNumberPercentMean TimeBest Time
-under 2010%3:14:223:14:22
20s8842%3:07:152:26:00
30s10148%3:04:292:21:25
40s209%3:05:162:28:40
50s10%3:17:123:17:12
Total211100%3:05:492:21:25
Fastest Ages (by average)
30s10148%3:04:292:21:25


Average/Best Times By Cities (cutoff=10)

CityNumberPercentMean TimeBest Time
ATLANTA, GA131%3:04:252:46:02
AUSTIN, TX161%3:05:262:55:40
BOULDER, CO221%2:43:422:07:14
CHICAGO, IL21211%3:04:192:26:45
CINCINNATI, OH111%2:55:502:27:28
DENVER, CO111%3:08:592:48:56
EVANSTON, IL121%3:02:492:33:12
INDIANAPOLIS, IN141%3:06:392:43:49
LONDON231%3:06:172:36:58
MADISON, WI111%3:08:082:49:12
MEXICO CITY241%3:08:142:37:04
MINNEAPOLIS, MN211%3:03:282:32:20
NAPERVILLE, IL141%3:05:052:27:40
NEW YORK, NY452%3:02:312:31:18
OMAHA, NE111%3:07:042:50:00
SAINT LOUIS, MO211%3:02:182:35:47
SAN DIEGO, CA121%3:00:332:39:54
SAN FRANCISCO, CA121%3:04:122:39:29
TORONTO151%3:02:342:39:39
WASHINGTON, DC131%3:01:172:36:43
Below Cutoff146773%3:02:252:07:02
Total2000100%3:02:412:07:02
Fastest City (by average)
BOULDER, CO221%2:43:422:07:14


Average/Best Times By State (cutoff=20)

StateNumberPercentMean TimeBest Time
CA834%3:02:072:21:25
CO623%2:57:002:07:14
FL422%3:03:492:12:44
GA342%3:03:192:34:03
IA402%3:03:492:31:30
IL49625%3:04:202:26:45
IN774%3:06:162:34:52
MA714%2:55:532:07:09
MD271%2:58:122:28:50
MI925%2:59:082:19:28
MN623%3:03:072:32:20
MO583%3:03:202:32:57
NC241%3:03:112:27:41
NJ231%3:04:482:26:55
NY905%3:03:072:31:18
OH583%3:02:442:27:28
PA312%3:01:352:36:48
TX422%3:03:592:39:41
VA251%3:01:142:34:01
WI683%3:02:522:32:27
other29815%3:02:012:07:02
Below Cutoff19710%3:03:272:20:19
Total2000100%3:02:412:07:02
Fastest State (by average)
MA714%2:55:532:07:09


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