Cleveland Marathon, Half, and 10K Stats
I've put together the stats for all of three of last Sunday's races. Below are some observations.
Women Slow Down More with Age?
The stats suggest women slow down with age more than men. There are likely other factors, but the stats are interesting. For the marathon the mean time of women in their twenties was 4:16:55. This increased to 4:32:40 for the thirties age group and 4:34:12 for the forties (slowdown of over 17 minutes)
For the men in their twenties, the mean time was 4:00:45. For those in their thirties it was 3:59:55, and for those in their forties it was 4:02:12 (slowdown of less than 2 minutes).
Similar results were seen in the half-marathon. For the men, the average time for the forties age group was actually 4 seconds faster than the twenties age group. For the women, the forties age group was over 17 minutes slower (very close to the marathon results coincidentally).
And this trend held up with the 10K.
Half-Marathons More Popular with Women
Men outnumbered the women in both the marathon (2.29 to 1) and the 10K (1.32 to 1). However, in the half-marathon, women outnumber men (1.13 to 1). As I've seen in previous half-marathons, women in their twenties greatly outnumber men (239 to 107). Even in the marathon, women in their twenties were a large number although not quite as much as the men (167 women to 171 men). Perhaps this is a factor in the observed slowdown-with-age for women.
Marathons Attract More Out-of-State Runners
I guess this is to be expected, the longer the race, the more out-of-state runners participated. 39% of the marathon runners were from outside of Ohio. For the half-marathon, this percentage dropped to 21%. And for the 10K it dropped to 8%.
Temperature Effects
I'll be eventually combining these stats with the race temperatures and expanding my temperature effects data. For now, I'll just list the temperature facts. The race day weather was ideal. From Weather Underground, the temperature at 7:51am (51 minutes after the marathon full/half start) was 51°F (83% humidity) with scattered clouds. By 9:51am it had warmed to 61°F (60% humidity).
Below are the detailed stats. Let me know in the comments if you find any interesting observations.
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
Average/Best Times By Cities (cutoff=20)
Average/Best Times By State (cutoff=20)
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
Average/Best Times By Cities (cutoff=20)
Average/Best Times By State (cutoff=20)
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
Average/Best Times By Cities (cutoff=50)
Average/Best Times By State (cutoff=10)
The above stats are based on 5/22/05 results from the Rite Aid Cleveland Marathon and 10K results page.
Women Slow Down More with Age?
The stats suggest women slow down with age more than men. There are likely other factors, but the stats are interesting. For the marathon the mean time of women in their twenties was 4:16:55. This increased to 4:32:40 for the thirties age group and 4:34:12 for the forties (slowdown of over 17 minutes)
For the men in their twenties, the mean time was 4:00:45. For those in their thirties it was 3:59:55, and for those in their forties it was 4:02:12 (slowdown of less than 2 minutes).
Similar results were seen in the half-marathon. For the men, the average time for the forties age group was actually 4 seconds faster than the twenties age group. For the women, the forties age group was over 17 minutes slower (very close to the marathon results coincidentally).
And this trend held up with the 10K.
Half-Marathons More Popular with Women
Men outnumbered the women in both the marathon (2.29 to 1) and the 10K (1.32 to 1). However, in the half-marathon, women outnumber men (1.13 to 1). As I've seen in previous half-marathons, women in their twenties greatly outnumber men (239 to 107). Even in the marathon, women in their twenties were a large number although not quite as much as the men (167 women to 171 men). Perhaps this is a factor in the observed slowdown-with-age for women.
Marathons Attract More Out-of-State Runners
I guess this is to be expected, the longer the race, the more out-of-state runners participated. 39% of the marathon runners were from outside of Ohio. For the half-marathon, this percentage dropped to 21%. And for the 10K it dropped to 8%.
Temperature Effects
I'll be eventually combining these stats with the race temperatures and expanding my temperature effects data. For now, I'll just list the temperature facts. The race day weather was ideal. From Weather Underground, the temperature at 7:51am (51 minutes after the marathon full/half start) was 51°F (83% humidity) with scattered clouds. By 9:51am it had warmed to 61°F (60% humidity).
Below are the detailed stats. Let me know in the comments if you find any interesting observations.
Full Marathon
Total Runners by Times
| under 3:00 | 3:00 to 4:00 | 4:00 to 5:00 | over 5:00 |
|---|---|---|---|
| 41 (3%) | 676 (42%) | 665 (42%) | 218 (14%) |
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 | 1 (11%) | 5 (56%) | 1 (11%) | 2 (22%) |
| twenties | 9 (5%) | 92 (55%) | 48 (29%) | 18 (11%) |
| thirties | 16 (4%) | 183 (51%) | 136 (38%) | 26 (7%) |
| forties | 12 (4%) | 178 (52%) | 118 (35%) | 33 (10%) |
| fifties | 1 (1%) | 74 (38%) | 97 (50%) | 22 (11%) |
| sixties | 0 (0%) | 10 (29%) | 11 (31%) | 14 (40%) |
| seventies | 0 (0%) | 0 (0%) | 1 (17%) | 5 (83%) |
| unknown | 0 (0%) | 0 (0%) | 1 (100%) | 0 (0%) |
| Total | 39 (4%) | 542 (49%) | 413 (37%) | 120 (11%) |
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 (13%) | 5 (63%) | 2 (25%) |
| twenties | 2 (1%) | 59 (35%) | 89 (52%) | 21 (12%) |
| thirties | 0 (0%) | 45 (29%) | 80 (51%) | 32 (20%) |
| forties | 0 (0%) | 26 (23%) | 60 (53%) | 27 (24%) |
| fifties | 0 (0%) | 3 (9%) | 16 (48%) | 14 (42%) |
| sixties | 0 (0%) | 0 (0%) | 1 (33%) | 2 (67%) |
| unknown | 0 (0%) | 0 (0%) | 1 (100%) | 0 (0%) |
| Total | 2 (0%) | 134 (28%) | 252 (52%) | 98 (20%) |
Average/Best Times By Age Groups (Male and Female)
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 17 | 1% | 4:17:24 | 2:57:03 |
| twenties | 338 | 21% | 4:08:56 | 2:40:00 |
| thirties | 518 | 32% | 4:09:51 | 2:22:00 |
| forties | 454 | 28% | 4:10:10 | 2:44:50 |
| fifties | 227 | 14% | 4:22:36 | 2:58:02 |
| sixties | 38 | 2% | 4:50:56 | 3:30:43 |
| seventies | 6 | 0% | 5:33:15 | 4:43:54 |
| unknown | 2 | 0% | 4:30:29 | 4:12:57 |
| Total | 1600 | 100% | 4:12:57 | 2:22:00 |
| Fastest Ages (by average) | ||||
| twenties | 338 | 21% | 4:08:56 | 2:40:00 |
Average/Best Times By Male Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 9 | 1% | 4:03:57 | 2:57:03 |
| twenties | 167 | 15% | 4:00:45 | 2:40:00 |
| thirties | 361 | 32% | 3:59:55 | 2:22:00 |
| forties | 341 | 31% | 4:02:12 | 2:44:50 |
| fifties | 194 | 17% | 4:17:21 | 2:58:02 |
| sixties | 35 | 3% | 4:46:28 | 3:30:43 |
| seventies | 6 | 1% | 5:33:15 | 4:43:54 |
| unknown | 1 | 0% | 4:48:01 | 4:48:01 |
| Total | 1114 | 100% | 4:05:49 | 2:22:00 |
| Fastest Ages (by average) | ||||
| thirties | 361 | 32% | 3:59:55 | 2:22:00 |
Average/Best Times By Female Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| teens | 8 | 2% | 4:32:32 | 3:40:11 |
| twenties | 171 | 35% | 4:16:55 | 2:54:53 |
| thirties | 157 | 32% | 4:32:40 | 3:03:54 |
| forties | 113 | 23% | 4:34:12 | 3:09:22 |
| fifties | 33 | 7% | 4:53:25 | 3:25:46 |
| sixties | 3 | 1% | 5:43:04 | 4:34:53 |
| unknown | 1 | 0% | 4:12:57 | 4:12:57 |
| Total | 486 | 100% | 4:29:17 | 2:54:53 |
| Fastest Ages (by average) | ||||
| twenties | 171 | 35% | 4:16:55 | 2:54:53 |
Average/Best Times By Cities (cutoff=20)
| City | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| Akron, OH | 32 | 2% | 4:18:14 | 3:17:33 |
| Canton, OH | 21 | 1% | 4:06:40 | 3:07:51 |
| Chagrin Falls, OH | 21 | 1% | 4:13:16 | 3:18:24 |
| Cleveland, OH | 67 | 4% | 4:13:42 | 2:22:00 |
| Columbus, OH | 40 | 3% | 4:04:16 | 3:07:04 |
| Lakewood, OH | 32 | 2% | 4:33:09 | 3:09:50 |
| Medina, OH | 36 | 2% | 4:19:18 | 2:38:08 |
| Pittsburgh, PA | 79 | 5% | 4:06:14 | 2:55:54 |
| Solon, OH | 20 | 1% | 3:52:22 | 2:50:45 |
| Westlake, OH | 23 | 1% | 4:23:34 | 3:24:02 |
| Below Cutoff | 1229 | 77% | 4:13:01 | 2:23:18 |
| Total | 1600 | 100% | 4:12:57 | 2:22:00 |
| Fastest City (by average) | ||||
| Solon, OH | 20 | 1% | 3:52:22 | 2:50:45 |
Average/Best Times By State (cutoff=20)
| State | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| IL | 42 | 3% | 4:07:56 | 3:03:17 |
| MI | 113 | 7% | 4:14:31 | 2:48:26 |
| NY | 53 | 3% | 4:03:13 | 2:58:15 |
| OH | 977 | 61% | 4:15:29 | 2:22:00 |
| PA | 216 | 14% | 4:05:48 | 2:23:18 |
| VA | 25 | 2% | 4:05:21 | 2:38:58 |
| other | 20 | 1% | 4:18:29 | 3:33:10 |
| Below Cutoff | 154 | 10% | 4:10:55 | 2:53:50 |
| Total | 1600 | 100% | 4:12:57 | 2:22:00 |
| Fastest State (by average) | ||||
| NY | 53 | 3% | 4:03:13 | 2:58:15 |
Half-Marathon
Total Runners by Times
| under 1:30 | 1:30 to 2:00 | 2:00 to 2:30 | over 2:30 |
|---|---|---|---|
| 26 (2%) | 684 (42%) | 643 (39%) | 288 (18%) |
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 |
|---|---|---|---|---|
| preteens | 0 (0%) | 0 (0%) | 0 (0%) | 1 (100%) |
| teens | 1 (6%) | 10 (63%) | 2 (13%) | 3 (19%) |
| twenties | 4 (4%) | 64 (60%) | 34 (32%) | 5 (5%) |
| thirties | 10 (4%) | 153 (62%) | 66 (27%) | 19 (8%) |
| forties | 8 (3%) | 137 (59%) | 71 (30%) | 17 (7%) |
| fifties | 1 (1%) | 60 (46%) | 48 (37%) | 21 (16%) |
| sixties | 0 (0%) | 7 (28%) | 13 (52%) | 5 (20%) |
| seventies | 0 (0%) | 1 (20%) | 1 (20%) | 3 (60%) |
| eighties+ | 0 (0%) | 0 (0%) | 0 (0%) | 1 (100%) |
| unknown | 0 (0%) | 3 (75%) | 1 (25%) | 0 (0%) |
| Total | 24 (3%) | 435 (56%) | 236 (31%) | 75 (10%) |
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 |
|---|---|---|---|---|
| preteens | 0 (0%) | 0 (0%) | 1 (50%) | 1 (50%) |
| teens | 0 (0%) | 4 (29%) | 6 (43%) | 4 (29%) |
| twenties | 2 (1%) | 84 (35%) | 126 (53%) | 27 (11%) |
| thirties | 0 (0%) | 101 (32%) | 156 (50%) | 57 (18%) |
| forties | 0 (0%) | 49 (24%) | 86 (42%) | 69 (34%) |
| fifties | 0 (0%) | 9 (11%) | 32 (39%) | 41 (50%) |
| sixties | 0 (0%) | 1 (9%) | 0 (0%) | 10 (91%) |
| eighties+ | 0 (0%) | 0 (0%) | 0 (0%) | 1 (100%) |
| unknown | 0 (0%) | 1 (25%) | 0 (0%) | 3 (75%) |
| Total | 2 (0%) | 249 (29%) | 407 (47%) | 213 (24%) |
Average/Best Times By Age Groups (Male and Female)
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| preteens | 3 | 0% | 3:27:55 | 2:18:46 |
| teens | 30 | 2% | 2:13:57 | 1:27:36 |
| twenties | 346 | 21% | 2:05:38 | 1:21:18 |
| thirties | 562 | 34% | 2:06:54 | 1:17:03 |
| forties | 437 | 27% | 2:11:23 | 1:14:29 |
| fifties | 212 | 13% | 2:18:26 | 1:29:45 |
| sixties | 36 | 2% | 2:33:54 | 1:34:02 |
| seventies | 5 | 0% | 2:53:50 | 1:44:42 |
| eighties+ | 2 | 0% | 3:16:58 | 3:12:25 |
| unknown | 8 | 0% | 2:23:44 | 1:34:35 |
| Total | 1641 | 100% | 2:10:30 | 1:14:29 |
| Fastest Ages (by average) | ||||
| twenties | 346 | 21% | 2:05:38 | 1:21:18 |
Average/Best Times By Male Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| preteens | 1 | 0% | 4:02:30 | 4:02:30 |
| teens | 16 | 2% | 1:58:50 | 1:27:36 |
| twenties | 107 | 14% | 1:58:14 | 1:24:31 |
| thirties | 248 | 32% | 1:57:42 | 1:17:03 |
| forties | 233 | 30% | 1:58:10 | 1:14:29 |
| fifties | 130 | 17% | 2:06:26 | 1:29:45 |
| sixties | 25 | 3% | 2:15:00 | 1:34:02 |
| seventies | 5 | 1% | 2:53:50 | 1:44:42 |
| eighties+ | 1 | 0% | 3:12:25 | 3:12:25 |
| unknown | 4 | 1% | 1:49:03 | 1:34:35 |
| Total | 770 | 100% | 2:00:33 | 1:14:29 |
| Fastest Ages (by average) | ||||
| thirties | 248 | 32% | 1:57:42 | 1:17:03 |
Average/Best Times By Female Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| preteens | 2 | 0% | 3:10:38 | 2:18:46 |
| teens | 14 | 2% | 2:31:15 | 1:46:32 |
| twenties | 239 | 27% | 2:08:57 | 1:21:18 |
| thirties | 314 | 36% | 2:14:10 | 1:37:29 |
| forties | 204 | 23% | 2:26:29 | 1:35:18 |
| fifties | 82 | 9% | 2:37:28 | 1:50:16 |
| sixties | 11 | 1% | 3:16:51 | 1:51:14 |
| eighties+ | 1 | 0% | 3:21:32 | 3:21:32 |
| unknown | 4 | 0% | 2:58:25 | 1:39:09 |
| Total | 871 | 100% | 2:19:17 | 1:21:18 |
| Fastest Ages (by average) | ||||
| twenties | 239 | 27% | 2:08:57 | 1:21:18 |
Average/Best Times By Cities (cutoff=20)
| City | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| Akron, OH | 58 | 4% | 2:02:59 | 1:25:43 |
| Avon Lake, OH | 21 | 1% | 2:02:04 | 1:32:00 |
| Cleveland Height, OH | 25 | 2% | 2:03:07 | 1:43:27 |
| Cleveland, OH | 106 | 6% | 2:09:29 | 1:21:18 |
| Columbus, OH | 22 | 1% | 2:08:39 | 1:38:07 |
| Hudson, OH | 24 | 1% | 2:01:10 | 1:37:03 |
| Lakewood, OH | 52 | 3% | 2:04:56 | 1:30:03 |
| Medina, OH | 41 | 2% | 2:16:51 | 1:14:29 |
| Mentor, OH | 29 | 2% | 2:13:50 | 1:40:34 |
| Pittsburgh, PA | 30 | 2% | 2:07:47 | 1:31:57 |
| Rocky River, OH | 33 | 2% | 2:03:15 | 1:31:53 |
| Strongsville, OH | 23 | 1% | 2:01:36 | 1:24:31 |
| Westlake, OH | 25 | 2% | 2:05:59 | 1:27:17 |
| Below Cutoff | 1152 | 70% | 2:12:00 | 1:17:03 |
| Total | 1641 | 100% | 2:10:30 | 1:14:29 |
| Fastest City (by average) | ||||
| Hudson, OH | 24 | 1% | 2:01:10 | 1:37:03 |
Average/Best Times By State (cutoff=20)
| State | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| IL | 21 | 1% | 2:03:21 | 1:30:06 |
| MI | 77 | 5% | 2:28:27 | 1:30:33 |
| NY | 34 | 2% | 2:18:10 | 1:33:26 |
| OH | 1296 | 79% | 2:09:48 | 1:14:29 |
| PA | 99 | 6% | 2:06:49 | 1:26:55 |
| Below Cutoff | 114 | 7% | 2:08:33 | 1:17:23 |
| Total | 1641 | 100% | 2:10:30 | 1:14:29 |
| Fastest State (by average) | ||||
| IL | 21 | 1% | 2:03:21 | 1:30:06 |
The 10K
Total Runners by Times
| under 40 | 40 to 50 | 50 to 60 | over 60 |
|---|---|---|---|
| 76 (3%) | 390 (16%) | 976 (39%) | 1061 (42%) |
Male Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
| Ages | under 40 | 40 to 50 | 50 to 60 | over 60 |
|---|---|---|---|---|
| preteens | 0 (0%) | 2 (12%) | 5 (29%) | 10 (59%) |
| teens | 1 (2%) | 21 (50%) | 12 (29%) | 8 (19%) |
| twenties | 19 (10%) | 47 (25%) | 72 (38%) | 50 (27%) |
| thirties | 15 (4%) | 101 (27%) | 170 (45%) | 92 (24%) |
| forties | 21 (5%) | 103 (25%) | 203 (48%) | 92 (22%) |
| fifties | 6 (2%) | 44 (15%) | 124 (44%) | 111 (39%) |
| sixties | 0 (0%) | 6 (8%) | 30 (41%) | 37 (51%) |
| seventies | 0 (0%) | 0 (0%) | 1 (7%) | 13 (93%) |
| unknown | 0 (0%) | 2 (29%) | 3 (43%) | 2 (29%) |
| Total | 62 (4%) | 326 (23%) | 620 (44%) | 415 (29%) |
Female Runners by Times - Move mouse over cells to see median times. Top 3 times also shown in left columns.
| Ages | under 40 | 40 to 50 | 50 to 60 | over 60 |
|---|---|---|---|---|
| preteens | 0 (0%) | 0 (0%) | 1 (10%) | 9 (90%) |
| teens | 0 (0%) | 5 (9%) | 27 (48%) | 24 (43%) |
| twenties | 7 (2%) | 11 (4%) | 120 (41%) | 155 (53%) |
| thirties | 6 (2%) | 25 (7%) | 109 (29%) | 230 (62%) |
| forties | 1 (0%) | 20 (9%) | 77 (34%) | 131 (57%) |
| fifties | 0 (0%) | 3 (3%) | 19 (20%) | 74 (77%) |
| sixties | 0 (0%) | 0 (0%) | 3 (15%) | 17 (85%) |
| seventies | 0 (0%) | 0 (0%) | 0 (0%) | 1 (100%) |
| unknown | 0 (0%) | 0 (0%) | 0 (0%) | 5 (100%) |
| Total | 14 (1%) | 64 (6%) | 356 (33%) | 646 (60%) |
Average/Best Times By Age Groups (Male and Female)
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| preteens | 27 | 1% | 1:06:23 | 47:27 |
| teens | 98 | 4% | 57:47 | 36:20 |
| twenties | 481 | 19% | 1:01:14 | 28:44 |
| thirties | 748 | 30% | 1:00:55 | 32:38 |
| forties | 648 | 26% | 59:35 | 32:09 |
| fifties | 381 | 15% | 1:04:06 | 37:57 |
| sixties | 93 | 4% | 1:07:35 | 41:37 |
| seventies | 15 | 1% | 1:17:53 | 57:14 |
| unknown | 12 | 0% | 1:06:50 | 48:42 |
| Total | 2503 | 100% | 1:01:26 | 28:44 |
| Fastest Ages (by average) | ||||
| teens | 98 | 4% | 57:47 | 36:20 |
Average/Best Times By Male Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| preteens | 17 | 1% | 1:03:07 | 47:27 |
| teens | 42 | 3% | 52:29 | 36:20 |
| twenties | 188 | 13% | 55:40 | 28:44 |
| thirties | 378 | 27% | 54:58 | 32:38 |
| forties | 419 | 29% | 54:49 | 32:09 |
| fifties | 285 | 20% | 59:27 | 37:57 |
| sixties | 73 | 5% | 1:03:46 | 41:37 |
| seventies | 14 | 1% | 1:17:09 | 57:14 |
| unknown | 7 | 0% | 55:52 | 48:42 |
| Total | 1423 | 100% | 56:37 | 28:44 |
| Fastest Ages (by average) | ||||
| teens | 42 | 3% | 52:29 | 36:20 |
Average/Best Times By Female Age Groups
| Ages | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| preteens | 10 | 1% | 1:11:57 | 58:26 |
| teens | 56 | 5% | 1:01:45 | 44:44 |
| twenties | 293 | 27% | 1:04:48 | 31:10 |
| thirties | 370 | 34% | 1:06:59 | 32:44 |
| forties | 229 | 21% | 1:08:18 | 34:53 |
| fifties | 96 | 9% | 1:17:53 | 46:19 |
| sixties | 20 | 2% | 1:21:28 | 54:40 |
| seventies | 1 | 0% | 1:27:58 | 1:27:58 |
| unknown | 5 | 0% | 1:22:11 | 1:06:10 |
| Total | 1080 | 100% | 1:07:46 | 31:10 |
| Fastest Ages (by average) | ||||
| teens | 56 | 5% | 1:01:45 | 44:44 |
Average/Best Times By Cities (cutoff=50)
| City | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| Akron, OH | 57 | 2% | 58:16 | 37:57 |
| Cleveland, OH | 323 | 13% | 1:03:32 | 35:27 |
| Lakewood, OH | 110 | 4% | 1:04:24 | 41:51 |
| Medina, OH | 58 | 2% | 57:22 | 36:12 |
| Mentor, OH | 56 | 2% | 58:57 | 33:58 |
| Strongsville, OH | 79 | 3% | 1:00:37 | 34:53 |
| Westlake, OH | 88 | 4% | 57:40 | 34:38 |
| Below Cutoff | 1732 | 69% | 1:01:24 | 28:44 |
| Total | 2503 | 100% | 1:01:26 | 28:44 |
| Fastest City (by average) | ||||
| Medina, OH | 58 | 2% | 57:22 | 36:12 |
Average/Best Times By State (cutoff=10)
| State | Number | Percent | Mean Time | Best Time |
|---|---|---|---|---|
| MI | 35 | 1% | 1:06:00 | 42:03 |
| OH | 2315 | 92% | 1:01:36 | 30:24 |
| PA | 62 | 2% | 57:15 | 28:44 |
| Below Cutoff | 91 | 4% | 58:20 | 29:58 |
| Total | 2503 | 100% | 1:01:26 | 28:44 |
| Fastest State (by average) | ||||
| PA | 62 | 2% | 57:15 | 28:44 |
The above stats are based on 5/22/05 results from the Rite Aid Cleveland Marathon and 10K results page.
posted by Ken at
5:03 PM
4 Comments:
I don't think it's accurate to say that women slow down more than men as they age based on comparing age group results. What it IS more appropriate to say is that women in the older age groups ran slower than men in the older age groups. It's a subtle difference.
If you were to track individual male and female athletes as they age, they would probably experience similar age-related changes in performance, all other things being equal.
Plus, I think it's difficult to accurately compare average race times now that there are so many folks walking in races nowadays. Who do the walkers tend to be? Usually women. So I think this will naturally bring down women's average finish times compared to men's.
By
Anonymous, at 7:26 AM
Thanks for your inputs. That's a good point about walkers. I can see how it could affect the numbers.
By
Ken, at 7:33 AM
I agree with Meredith... as a (male) statistician I can't believe that from your simple tables you make the claim that women slow down more than men. Your sample changes as people age and in addition you are mostly just considering the average. How about considering the top 10 runners in each age category, what happens to the standard deviation with age of the top 50 runners, etc? Actually from what I can tell from your tables men actually slow down more! If you look at the fastest time in each age category, the women's fastest time slows less than the men's fastest time. This is probably a better indication of potential ability than average finish time.
By
Anonymous, at 10:49 AM
Ryan, I like your idea about considering the top ten runners in each age group. That would remove walkers from the comparisons. I'll try to add the top-ten mean time to the tables. Thanks.
By
Ken, at 11:05 AM
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