Toronto Marathon Stats
The Scotiabank Toronto Waterfront Marathon was held last Sunday (9/25/05). Here's a piece of the race summary from the marathon's website:
The article mentioned the humid conditions so I checked weatherunderground, and the conditions from 8:00am through 9:44am were 66°F and 94% humidity. At least it wasn't in the seventies, but it was definitely not ideal marathon running weather.
I've downloaded last Sunday's results for both the full and half marathon, and put them through my stats program. One thing that complicated things was the race's early-start marathon that began at 6:15am rather than the standard 7:30am time. The intent was to allow runners expected to finish over 5:30 to start early. The results from these early-bird marathon runners were put into a separate list. At first I was going to exclude these runners, but after reviewing the results, I noticed it included many serious runners, 92 of whom finished in under 5 hours. Perhaps many were trying to finish ahead of the elite runners. So my marathon stats include both the early-bird runners and the runners in the standard race.
I excluded stats based on location. The results mixed cities and countries together making it difficult to group runners by city or country. And since it was in Canada, there was no state information.
For the full marathon there were a total of 2022 timed finishers: 1282 men and 738 women (37%). The half had over twice the runners (4738) with 2081 men and 2638 women (56%).
The fastest age group for the men was the 30s age group for both the full and half marathon. The next fastest group were those in the 40s for both races. It's interesting that the 40s group had a faster average time than those in their 20s.
The fastest age group for the women was the 20s age group for both the full and half marathon.
Full Marathon
Total Runners by Times
Male Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
Female Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
Average/Best Times By Age Groups (Male and Female)
Average/Best Times By Male Age Groups
Average/Best Times By Female Age Groups
Half Marathon
Total Runners by Times
Male Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
Female Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
Average/Best Times By Age Groups (Male and Female)
Average/Best Times By Male Age Groups
Average/Best Times By Female Age Groups
The above stats are based on results from the 2005 Scotiabank Toronto Waterfront Marathon results page.
Despite humid conditions, Kenyan Simon Bor ran 2:11:57 to win the Scotiabank Toronto Waterfront Marathon this morning, taking almost 3 minutes off the course record of 2:14:51, set last year in one of North America's most rapidly-growing new marathons.
Anastasia Ndereba took the women's title with a 2:36:29, ahead of Lucy Hasell of England in 2:38:09. Almost 10,000 runners from over 30 countries and 40 American states participated in the combined 42k, 21k, and 5k events. Nearly 25% of the marathon field of over 2,500 was made up of international runners.
The article mentioned the humid conditions so I checked weatherunderground, and the conditions from 8:00am through 9:44am were 66°F and 94% humidity. At least it wasn't in the seventies, but it was definitely not ideal marathon running weather.
I've downloaded last Sunday's results for both the full and half marathon, and put them through my stats program. One thing that complicated things was the race's early-start marathon that began at 6:15am rather than the standard 7:30am time. The intent was to allow runners expected to finish over 5:30 to start early. The results from these early-bird marathon runners were put into a separate list. At first I was going to exclude these runners, but after reviewing the results, I noticed it included many serious runners, 92 of whom finished in under 5 hours. Perhaps many were trying to finish ahead of the elite runners. So my marathon stats include both the early-bird runners and the runners in the standard race.
I excluded stats based on location. The results mixed cities and countries together making it difficult to group runners by city or country. And since it was in Canada, there was no state information.
For the full marathon there were a total of 2022 timed finishers: 1282 men and 738 women (37%). The half had over twice the runners (4738) with 2081 men and 2638 women (56%).
The fastest age group for the men was the 30s age group for both the full and half marathon. The next fastest group were those in the 40s for both races. It's interesting that the 40s group had a faster average time than those in their 20s.
The fastest age group for the women was the 20s age group for both the full and half marathon.
Full Marathon
Total Runners by Times
| under 3:00 | 3:00 to 4:00 | 4:00 to 5:00 | over 5:00 |
|---|---|---|---|
| 49 (2%) | 761 (38%) | 869 (43%) | 343 (17%) |
Male Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
| Ages | under 3:00 | 3:00 to 4:00 | 4:00 to 5:00 | over 5:00 |
|---|---|---|---|---|
| teens | 0 (0%) | 2 (40%) | 3 (60%) | 0 (0%) |
| twenties | 15 (10%) | 68 (43%) | 51 (32%) | 23 (15%) |
| thirties | 16 (4%) | 188 (51%) | 129 (35%) | 39 (10%) |
| forties | 12 (2%) | 242 (48%) | 202 (40%) | 45 (9%) |
| fifties | 1 (0%) | 72 (35%) | 98 (48%) | 32 (16%) |
| sixties | 0 (0%) | 8 (21%) | 16 (41%) | 15 (38%) |
| seventies | 0 (0%) | 2 (40%) | 0 (0%) | 3 (60%) |
| Total | 44 (3%) | 582 (45%) | 499 (39%) | 157 (12%) |
Female Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
| Ages | under 3:00 | 3:00 to 4:00 | 4:00 to 5:00 | over 5:00 |
|---|---|---|---|---|
| teens | 0 (0%) | 1 (100%) | 0 (0%) | 0 (0%) |
| twenties | 2 (1%) | 36 (24%) | 73 (50%) | 36 (24%) |
| thirties | 3 (1%) | 70 (26%) | 138 (51%) | 58 (22%) |
| forties | 0 (0%) | 60 (25%) | 123 (51%) | 59 (24%) |
| fifties | 0 (0%) | 11 (16%) | 33 (48%) | 25 (36%) |
| sixties | 0 (0%) | 1 (10%) | 3 (30%) | 6 (60%) |
| Total | 5 (1%) | 179 (24%) | 370 (50%) | 184 (25%) |
Average/Best Times By Age Groups (Male and Female)
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 6 | 0% | 4:07:19 | 3:33:54 |
| twenties | 304 | 15% | 4:17:39 | 2:12:16 |
| thirties | 641 | 32% | 4:13:28 | 2:11:55 |
| forties | 743 | 37% | 4:14:22 | 2:25:29 |
| fifties | 272 | 13% | 4:27:23 | 2:52:27 |
| sixties | 49 | 2% | 4:49:39 | 3:23:19 |
| seventies | 5 | 0% | 5:07:02 | 3:02:37 |
| unknown | 2 | 0% | 5:37:38 | 5:05:03 |
| Total | 2022 | 100% | 4:17:22 | 2:11:55 |
| Fastest Ages (by average) | ||||
| teens | 6 | 0% | 4:07:19 | 3:33:54 |
Average/Best Times By Male Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 5 | 0% | 4:08:53 | 3:33:54 |
| twenties | 157 | 12% | 4:06:13 | 2:12:16 |
| thirties | 372 | 29% | 4:00:41 | 2:11:55 |
| forties | 501 | 39% | 4:04:14 | 2:25:29 |
| fifties | 203 | 16% | 4:19:37 | 2:52:27 |
| sixties | 39 | 3% | 4:43:34 | 3:23:19 |
| seventies | 5 | 0% | 5:07:02 | 3:02:37 |
| Total | 1282 | 100% | 4:07:21 | 2:11:55 |
| Fastest Ages (by average) | ||||
| thirties | 372 | 29% | 4:00:41 | 2:11:55 |
Average/Best Times By Female Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 1 | 0% | 3:59:27 | 3:59:27 |
| twenties | 147 | 20% | 4:29:52 | 2:38:08 |
| thirties | 269 | 36% | 4:31:09 | 2:36:28 |
| forties | 242 | 33% | 4:35:20 | 3:03:23 |
| fifties | 69 | 9% | 4:50:12 | 3:33:18 |
| sixties | 10 | 1% | 5:13:25 | 3:55:36 |
| Total | 738 | 100% | 4:34:35 | 2:36:28 |
| Fastest Ages (by average) | ||||
| teens | 1 | 0% | 3:59:27 | 3:59:27 |
Half Marathon
Total Runners by Times
| under 1:30 | 1:30 to 2:00 | 2:00 to 2:30 | over 2:30 |
|---|---|---|---|
| 159 (3%) | 1869 (39%) | 1954 (41%) | 756 (16%) |
Male Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
| Ages | under 1:30 | 1:30 to 2:00 | 2:00 to 2:30 | over 2:30 |
|---|---|---|---|---|
| teens | 0 (0%) | 20 (74%) | 3 (11%) | 4 (15%) |
| twenties | 26 (9%) | 164 (58%) | 78 (27%) | 17 (6%) |
| thirties | 55 (8%) | 437 (62%) | 189 (27%) | 23 (3%) |
| forties | 41 (6%) | 415 (61%) | 200 (29%) | 25 (4%) |
| fifties | 17 (5%) | 137 (44%) | 119 (38%) | 37 (12%) |
| sixties | 0 (0%) | 14 (24%) | 29 (49%) | 16 (27%) |
| seventies | 0 (0%) | 1 (7%) | 9 (60%) | 5 (33%) |
| Total | 139 (7%) | 1188 (57%) | 627 (30%) | 127 (6%) |
Female Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
| Ages | under 1:30 | 1:30 to 2:00 | 2:00 to 2:30 | over 2:30 |
|---|---|---|---|---|
| teens | 0 (0%) | 7 (23%) | 15 (48%) | 9 (29%) |
| twenties | 3 (1%) | 196 (36%) | 287 (52%) | 63 (11%) |
| thirties | 12 (1%) | 256 (29%) | 467 (52%) | 159 (18%) |
| forties | 5 (1%) | 185 (22%) | 430 (52%) | 206 (25%) |
| fifties | 0 (0%) | 31 (11%) | 98 (35%) | 155 (55%) |
| sixties | 0 (0%) | 2 (4%) | 18 (37%) | 29 (59%) |
| seventies | 0 (0%) | 0 (0%) | 1 (20%) | 4 (80%) |
| Total | 20 (1%) | 677 (26%) | 1316 (50%) | 625 (24%) |
Average/Best Times By Age Groups (Male and Female)
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 58 | 1% | 2:09:47 | 1:33:31 |
| twenties | 834 | 18% | 2:03:59 | 1:04:33 |
| thirties | 1598 | 34% | 2:04:33 | 1:04:46 |
| forties | 1507 | 32% | 2:08:19 | 1:14:06 |
| fifties | 594 | 13% | 2:19:12 | 1:13:48 |
| sixties | 108 | 2% | 2:32:02 | 1:39:02 |
| seventies | 20 | 0% | 2:33:18 | 1:57:23 |
| unknown | 19 | 0% | 2:25:14 | 1:39:46 |
| Total | 4738 | 100% | 2:08:23 | 1:04:33 |
| Fastest Ages (by average) | ||||
| twenties | 834 | 18% | 2:03:59 | 1:04:33 |
Average/Best Times By Male Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 27 | 1% | 1:58:38 | 1:33:31 |
| twenties | 285 | 14% | 1:55:20 | 1:04:33 |
| thirties | 704 | 34% | 1:53:35 | 1:04:46 |
| forties | 681 | 33% | 1:55:08 | 1:14:06 |
| fifties | 310 | 15% | 2:03:29 | 1:13:48 |
| sixties | 59 | 3% | 2:18:59 | 1:39:02 |
| seventies | 15 | 1% | 2:24:51 | 1:57:23 |
| Total | 2081 | 100% | 1:56:49 | 1:04:33 |
| Fastest Ages (by average) | ||||
| thirties | 704 | 34% | 1:53:35 | 1:04:46 |
Average/Best Times By Female Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 31 | 1% | 2:19:29 | 1:46:51 |
| twenties | 549 | 21% | 2:08:29 | 1:29:23 |
| thirties | 894 | 34% | 2:13:11 | 1:15:07 |
| forties | 826 | 31% | 2:19:11 | 1:24:16 |
| fifties | 284 | 11% | 2:36:21 | 1:36:53 |
| sixties | 49 | 2% | 2:47:45 | 1:51:17 |
| seventies | 5 | 0% | 2:58:39 | 2:23:18 |
| Total | 2638 | 100% | 2:17:23 | 1:15:07 |
| Fastest Ages (by average) | ||||
| twenties | 549 | 21% | 2:08:29 | 1:29:23 |
The above stats are based on results from the 2005 Scotiabank Toronto Waterfront Marathon results page.
posted by Ken at
6:51 AM
2 Comments:
Did you hear about the Fox Cities Marathon? That would a skewed dataset.
By
Unknown, at 6:26 PM
I found some articles about the race. Looks like lots of runners were forced to end early. Not only would that skew the data but also the storms would probably skew it.
By
Ken, at 3:32 PM
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