Peachtree 10K and the PRRO

Can John Korir win next Monday's Peachtree 10K to claim the Professional Road Racing Organization's (PRRO) Triple Crown? The PRRO Circuit is a nationwide series of road racing events that attracts elite runners from around the world. John Korir is an elite Kenyan runner who won the first two legs of the Triple Crown (Credit Union Cherry Blossom 10 Mile in Washington, DC in April and the Lilac Bloomsday 12K in Spokane, WA in May). If he wins the Peachtree, he'll earn an extra $15K from the PRRO.

Looking at John Korir's past Peachtree performances, it's not going to be easy. He took second place last year with a time of 28:09 which was 7 seconds behind the winner Martin Lel. I didn't see his name in 2003. The winner had a time of 28:23. In 2002, he finished fourth with a time of 28:10. The winner that year was Paul Kosgei who finished with a time of 27:36. In 2001, John Korir won the race with a time of 28:19.

So the last 3 times he ran the Peachtree, he's been very consistent with times of 28:09, 28:10, and 28:19. If he can run Monday with a similar time, he has a chance to win it.

Fastest 1000 Women from Peachtree 2004

Using the same method as I did yesterday for the men, I ran my stats on the open and masters women in the 2004 Peachtree 10K. All of the open and masters women came out to 1017 so instead of stopping at 1000, I just included them all.

One thing caught my eye in the masters division. Carmen Troncoso of my home city of Austin took fourth place with a time of 35:29. She often runs local races and was interviewed last month by Runner's World. The masters winner last year was Colleen S. De Reuck with a time of 32:30. This was third place overall and just 36 seconds behind the winner.

Just like the men, the 20s age group had the fastest mean time. Also just like the men, the vast majority of these top runners were from Georgia. However, it was a higher percentage compared to the men (85% compared to 79%). The fastest state for the women was North Carolina. The 18 women from there had a mean time of 45:54. The North Carolina men also did well. They missed out on the top state by just 25 seconds. I thought perhaps there were some college cross country runners who came together to run the race. But looking at the ages, there are many in their 30s, 40s and 50s.

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

Ages	under 35m	35m to 45m	45m to 55m	over 55m
preteens	0 (0%)	0 (0%)	3 (100%)	0 (0%)
teens	0 (0%)	16 (22%)	43 (58%)	15 (20%)
twenties	6 (3%)	36 (18%)	121 (61%)	34 (17%)
thirties	7 (2%)	28 (8%)	233 (66%)	86 (24%)
forties	2 (1%)	26 (8%)	197 (64%)	81 (26%)
fifties	0 (0%)	1 (1%)	44 (56%)	33 (42%)
sixties	0 (0%)	0 (0%)	3 (75%)	1 (25%)
unknown	0 (0%)	0 (0%)	1 (100%)	0 (0%)
Total	15 (1%)	107 (11%)	645 (63%)	250 (25%)

Average/Best Times By Female Age Groups

Ages	Number	Percent	Mean Time	Best Time
preteens	3	0%	52:04	50:34
teens	74	7%	50:03	38:01
twenties	197	19%	49:21	31:54
thirties	354	35%	51:04	32:13
forties	306	30%	51:30	32:30
fifties	78	8%	53:39	44:20
sixties	4	0%	52:22	49:41
unknown	1	0%	50:30	50:30
Total	1017	100%	51:00	31:54
Fastest Ages (by average)
twenties	197	19%	49:21	31:54

Average/Best Times By Nations (cutoff=1)

Nation	Number	Percent	Mean Time	Best Time
BERMUDA	3	0%	49:18	48:42
GA	1	0%	50:30	50:30
GBR	1	0%	32:36	32:36
KEN	6	1%	34:28	31:54
POL	1	0%	32:42	32:42
ROM	2	0%	32:57	32:13
RUS	7	1%	34:06	32:53
SWE	1	0%	35:32	35:32
USA	994	98%	51:18	32:30
unknown	1	0%	52:49	52:49
Total	1017	100%	51:00	31:54
Fastest Nation (by average)
GBR	1	0%	32:36	32:36

Average/Best Times By State (cutoff=10)

State	Number	Percent	Mean Time	Best Time
AL	18	2%	51:10	40:23
FL	26	3%	50:52	38:31
GA	862	85%	51:41	35:56
NC	18	2%	45:54	34:27
TN	13	1%	51:15	41:13
other	23	2%	37:32	31:54
Below Cutoff	57	6%	47:42	32:30
Total	1017	100%	51:00	31:54
Fastest State (by average)
NC	18	2%	45:54	34:27

Fastest 1000 Men from Peachtree 2004

I thought it would be interesting to look at the top 1000 men from last year's Peachtree 10K. The Peachtree's results page wasn't in the ideal format. It broke up the men into the open and masters category. In the combined results, it didn't list gender. So for simplicity, I took the top 500 from both the open and masters men. This isn't really the top 1000, but it should be close.

There were 17 men who ran under 30 minutes. What makes this extra impressive is the fact that the temperature was a warm 72°F with a humidity of 93%. Kenya dominated the race. All but two of the top 20 were from Kenya. The top US runner came in 16th place with a time of 29:43. There were 25 Kenyans in all and they had the incredible average time of 29:45.

From the age stats, the 20s age group had the fastest mean time.

I was expecting to see more nations represented, but there were only about 4% of the top 1000 men who were from outside of the US and most of these were the Kenyans.

For state representation, Georgia had 793 of the top 1000. Florida was next at about 29 and North Carolina was third with 24. The fastest state was Ohio. Those 12 men had an average time of 38:46.

Below are the details from 2004 Peachtree 10K results page.

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

Ages	under 30	30 to 35	35 to 40	over 40
teens	0 (0%)	6 (6%)	56 (53%)	44 (42%)
twenties	15 (9%)	36 (22%)	56 (34%)	57 (35%)
thirties	2 (1%)	23 (10%)	73 (32%)	132 (57%)
forties	0 (0%)	10 (3%)	80 (21%)	292 (76%)
fifties	0 (0%)	0 (0%)	16 (15%)	90 (85%)
sixties	0 (0%)	0 (0%)	0 (0%)	12 (100%)
Total	17 (2%)	75 (8%)	281 (28%)	627 (63%)

Average/Best Times By Male Age Groups

Ages	Number	Percent	Mean Time	Best Time
teens	106	11%	39:09	33:29
twenties	164	16%	37:15	28:02
thirties	230	23%	39:48	29:31
forties	382	38%	42:02	30:09
fifties	106	11%	42:44	36:27
sixties	12	1%	44:11	42:35
Total	1000	100%	40:32	28:02
Fastest Ages (by average)
twenties	164	16%	37:15	28:02

Average/Best Times By Nations (cutoff=1)

Nation	Number	Percent	Mean Time	Best Time
AUS	1	0%	30:13	30:13
BER	1	0%	38:47	38:47
BERMUDA	3	0%	40:34	38:54
CAN	1	0%	31:05	31:05
KEN	25	3%	29:45	28:02
MEX	1	0%	37:30	37:30
NAM	1	0%	30:28	30:28
NZL	1	0%	29:39	29:39
RSA	1	0%	34:47	34:47
USA	963	96%	40:51	29:43
unknown	2	0%	43:17	41:30
Total	1000	100%	40:32	28:02
Fastest Nation (by average)
NZL	1	0%	29:39	29:39

Average/Best Times By State (cutoff=10)

State	Number	Percent	Mean Time	Best Time
AL	16	2%	40:15	34:28
FL	29	3%	40:45	34:20
GA	793	79%	41:06	30:42
NC	24	2%	39:11	30:43
OH	12	1%	38:46	30:18
SC	14	1%	40:04	32:39
TN	16	2%	40:47	34:15
VA	11	1%	39:36	31:06
other	37	4%	32:01	28:02
Below Cutoff	48	5%	38:50	29:43
Total	1000	100%	40:32	28:02
Fastest State (by average)
OH	12	1%	38:46	30:18

The Peachtree Road Race 10K

Next Monday, July 4th, the US's largest 10K, the Peachtree 10K, will take place in Atlanta Georgia. This race's history goes back to 1970 when it started with 110 runners. By 1974 there were 765 finishers, 6500 runners in 1977, over 20000 in 1979, and in 1980 they decided to limit the race to 25000. It stayed that way through the 80's and the race was having to close its registration earlier and earlier each year. Finally, they reorganized the race in 1990 with staggered time groups, and opened the field to 40000. In 1998, 55000 runners were admitted.

This Peachtree 10K page has some interesting facts about this race: The men's course record is 27:04 set in 1996. The women's course record was also set that year with a time of 30:52. As you would expect, the temperatures are always warm. The coolest starting temperatures on race day was 62°F in 1986 and 1989. The warmest was 80°F in 6 of the past 35 races.

I'll be posting many more facts and stats about this race in the coming days.

Kona Marathon

Last Sunday (6/19/05) the Kona Marathon and Half Marathon were held on the Big Island of Hawaii. It's a small event with each race having around 650 runners.

One interesting stat for this marathon was that there were twice the number of women runners as men (420 to 202 ratio of 2.08). Perhaps too many men wanted to relax on Father's Day. A similar ratio also occurred for the half (485 to 182). Although for the half marathons, it's common to have more women.

Looks like men are gaining ground however. Looking back at the 2004 race, there were 539 women vs. 187 men in the full marathon (2.88 ratio). In 2003, there were 946 women and 356 men (2.66). Also, there seems to be a significant downturn in the turnout for the marathon: 1302 in 2003, 726 in 2004, and 622 in 2005. Perhaps fewer runners are taking Hawaii vacations.

Garry Bjorklund Half Marathon

About an hour before the Grandma's Marathon, they started the Garry Bjorklunk Half Marathon at 6:30am last Saturday (6/18/05). The half marathon is run on the second half of the marathon course. I like how they do this. That means all the half marathon runners will be able to watch the full marathon winners cross the finish line.

This was the 29th Grandma's Marathon and the half has been going on since 1991. The half was listed as the 14th largest in the nation in 2003 according to runningusa.org (the marathon was 11th).

The Duluth News Tribune reports on planning that is already underway for next year's race which will be the race's 30th anniversary. Extra events are being planned to mark the occasion. One of the improvements they made this year was the addition of a 17-foot Jumbo Tron video screen near the finish line. If races want to increase the spectator turnout, this seems like a good way.

Half Marathon Stats

Below are the detailed half marathon statistics. Again this shows that half marathons are more popular with women. In the half women outnumber men by a ratio of 1.30. In the full marathon, men outnumbered the women with a ratio of 1.71.

Another consistent trend is with women in their 20s. They make up the largest age category with 38% of all the women. For the men, the largest age category is the 40s group with 29% of all the men.

Halfs seem to be much more popular with teens compared to full marathons. Perhaps it's closer to the distances they run in track or cross country. In this half both male and female teens made up 5% of the runners compared to only 2% for the full marathon. Also, the male and female teens were the fastest age group in the half. In the full marathon, the 30s age group was the fastest.

Finally, the half marathons don't usually attact the out-of-state folks like the full marathons. This was the case for the Bjorklunk. Only 17% of the half marathon runners were from outside Minnesota compared to 38% in the full marathon.

Below are the stats in table formats derived from the 2005 Gary Bjorklund Half Marathon results page.

Total Runners by Times

under 1:30	1:30 to 2:00	2:00 to 2:30	over 2:30
176 (4%)	1823 (38%)	2187 (45%)	641 (13%)

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%)	2 (50%)	0 (0%)	2 (50%)
teens	21 (21%)	52 (51%)	26 (26%)	2 (2%)
twenties	53 (13%)	189 (45%)	143 (34%)	37 (9%)
thirties	37 (6%)	351 (56%)	206 (33%)	34 (5%)
forties	34 (7%)	283 (55%)	170 (33%)	30 (6%)
fifties	9 (3%)	151 (47%)	125 (39%)	37 (11%)
sixties	1 (1%)	27 (30%)	49 (54%)	13 (14%)
seventies	0 (0%)	4 (27%)	7 (47%)	4 (27%)
Total	155 (7%)	1059 (50%)	726 (35%)	159 (8%)

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%)	2 (100%)	0 (0%)
teens	1 (1%)	64 (45%)	59 (42%)	18 (13%)
twenties	9 (1%)	255 (28%)	485 (54%)	148 (16%)
thirties	7 (1%)	259 (31%)	463 (55%)	114 (14%)
forties	4 (1%)	154 (27%)	313 (54%)	108 (19%)
fifties	0 (0%)	30 (13%)	130 (54%)	80 (33%)
sixties	0 (0%)	2 (10%)	8 (38%)	11 (52%)
seventies	0 (0%)	0 (0%)	1 (25%)	3 (75%)
Total	21 (1%)	764 (28%)	1461 (54%)	482 (18%)

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

Ages	Number	Percent	Mean Time	Best Time
preteens	6	0%	2:12:26	1:41:52
teens	243	5%	1:58:47	1:14:24
twenties	1319	27%	2:06:13	1:06:38
thirties	1471	30%	2:04:07	1:09:47
forties	1096	23%	2:05:08	1:10:24
fifties	562	12%	2:11:01	1:21:47
sixties	111	2%	2:14:30	1:24:54
seventies	19	0%	2:24:18	1:50:12
Total	4827	100%	2:05:47	1:06:38
Fastest Ages (by average)
teens	243	5%	1:58:47	1:14:24

Average/Best Times By Male Age Groups

Ages	Number	Percent	Mean Time	Best Time
preteens	4	0%	2:12:12	1:41:52
teens	101	5%	1:49:06	1:14:24
twenties	422	20%	1:56:50	1:06:38
thirties	628	30%	1:56:17	1:09:47
forties	517	25%	1:56:58	1:10:24
fifties	322	15%	2:03:31	1:21:47
sixties	90	4%	2:11:14	1:24:54
seventies	15	1%	2:19:46	1:50:12
Total	2099	100%	1:58:10	1:06:38
Fastest Ages (by average)
teens	101	5%	1:49:06	1:14:24

Average/Best Times By Female Age Groups

Ages	Number	Percent	Mean Time	Best Time
preteens	2	0%	2:12:55	2:05:29
teens	142	5%	2:05:41	1:28:20
twenties	897	33%	2:10:37	1:17:42
thirties	843	31%	2:09:58	1:21:24
forties	579	21%	2:12:26	1:24:16
fifties	240	9%	2:21:05	1:30:32
sixties	21	1%	2:28:31	1:48:04
seventies	4	0%	2:41:18	2:04:56
Total	2728	100%	2:11:39	1:17:42
Fastest Ages (by average)
teens	142	5%	2:05:41	1:28:20

Average/Best Times By Cities (cutoff=50)

City	Number	Percent	Mean Time	Best Time
Cloquet, MN	75	2%	2:06:37	1:15:37
Duluth, MN	958	20%	2:07:06	1:08:53
Eagan, MN	55	1%	2:04:49	1:32:06
Edina, MN	54	1%	1:59:58	1:27:56
Grand Rapids, MN	61	1%	2:00:05	1:11:58
Hermantown, MN	60	1%	2:05:51	1:28:01
Minneapolis, MN	439	9%	2:03:58	1:09:47
Plymouth, MN	77	2%	2:05:56	1:21:07
St Louis Park, MN	98	2%	2:05:41	1:11:31
St Paul, MN	236	5%	2:05:31	1:15:44
Superior, WI	94	2%	2:10:26	1:22:46
Below Cutoff	2620	54%	2:05:43	1:06:38
Total	4827	100%	2:05:47	1:06:38
Fastest City (by average)
Edina, MN	54	1%	1:59:58	1:27:56

Average/Best Times By State (cutoff=10)

State	Number	Percent	Mean Time	Best Time
CA	12	0%	2:17:14	1:41:21
CO	18	0%	2:03:09	1:29:47
FL	13	0%	2:05:56	1:34:23
IA	46	1%	1:59:16	1:14:14
IL	42	1%	2:06:22	1:16:42
MI	22	0%	2:04:17	1:10:04
MN	4027	83%	2:05:46	1:08:53
ND	24	0%	2:11:54	1:10:16
SD	21	0%	2:05:58	1:09:26
WI	433	9%	2:04:51	1:06:38
other	57	1%	2:08:41	1:21:48
Below Cutoff	112	2%	2:09:19	1:12:08
Total	4827	100%	2:05:47	1:06:38
Fastest State (by average)
IA	46	1%	1:59:16	1:14:14

Average/Best Times By Nation (cutoff=1)

Nation	Number	Percent	Mean Time	Best Time
China	1	0%	1:21:48	1:21:48
Canada	44	1%	2:12:11	1:31:44
St Thomas Virgin I	1	0%	1:45:36	1:45:36
Sweden	1	0%	2:15:04	2:15:04
USA	4780	99%	2:05:44	1:06:38
Total	4827	100%	2:05:47	1:06:38
Fastest Nation (by average)
China	1	0%	1:21:48	1:21:48

Grandma's Marathon Split Comparisons

Running a consistent pace throughout a marathon is much easier said than done. I've looked at the first and second half splits of last Saturday's Grandma's Marathon in Duluth Minnesota. Only about 22% of the runners were able to keep their first and second half times within 5 minutes of each other. About 75% ran the second half over 5 minutes slower. Only about 10% of the runners ran the second half faster.

It's interesting to note how similar this is to the Knoxville Marathon. The Grandma's Marathon runners were a tad more consistent. In the Knoxville Marathon only about 20% of the runners were able to keep their first and second half times within 5 minutes of each other (2% fewer than Grandma's). The weather was quite a bit different between these races. For Knoxville, the temperature went from 41°F to 55°F. For Grandma's, the temperature went from about 55°F to 69°F. Even though Knoxville was cooler, there was more temperature variation. This could be why Knoxville had about 1% fewer runners who ran the second half faster.

In looking at the splits, it's interesting to see how consistency varies with finish times. One would expect that the faster runners (who might be more serious and experienced) would have more consistency. For consistency I mean keeping their first and second half times within 5 minutes of each other. That does seem to be the case. Below is a summary of the percentage of runners who had about equal splits (+/-5 minutes) broken down by overall chip finish times.

These are very similar to the Knoxville Marathon results except for runners who finished under 3hr and over 6hr. Knoxville Marathon was much smaller and only had 19 runners in each of those extremes. Grandma's Marathon had 168 under 3hr and 141 over 6hr. So that may explain the difference in percentage and why Grandma's Marathon has a consistent trend showing a higher likelyhood of pace consistency with faster times.

Finish      Percent of runners who
Times       kept 1st/2nd half splits
            within 5 minutes
----------- -----------------------
under 3hr:    67%
3 to 3.5hr:   46%
3.5 to 4hr:   33%
4 to 4.5hr:   19%
4.5 to 5hr:    9%
5 to 5.5hr:    8%
5.5 to 6hr:    3%
over 6hr:      2%
Overall:      22%

Below are the stats in table formats derived from the Grandma's Marathon results page. The halfway times are assumed to be chip times.

Half Split Changes for Under-4hr Runners

Split Change	Marathon Chip Times
	Under 3hr	3 to 3.5hr	3.5 to 4hr
More than 5m faster	5 (3%)	15 (2.2%)	61 (3.6%)
Less than 5m faster	30 (17.9%)	78 (11.5%)	196 (11.6%)
Less than 5m slower	83 (49.4%)	236 (34.7%)	362 (21.4%)
More than 5m slower	50 (29.8%)	349 (51.3%)	1062 (62.8%)
Unknown		2 (0.3%)	11 (0.7%)
Total	168	680	1692

Half Split Changes for 4hr-to-5.5hr Runners

Split Change	Marathon Chip Times
	4 to 4.5hr	4.5 to 5hr	5 to 5.5hr
More than 5m faster	45 (2.5%)	44 (3.2%)	13 (1.8%)
Less than 5m faster	92 (5.2%)	55 (4%)	13 (1.8%)
Less than 5m slower	242 (13.7%)	74 (5.4%)	43 (6%)
More than 5m slower	1385 (78.2%)	1195 (87%)	647 (90.2%)
Unknown	7 (0.4%)	6 (0.4%)	1 (0.1%)
Total	1771	1374	717

Half Split Changes for Over-5.5hr Runners and Overall

Split Change	Marathon Chip Times
	5.5 to 6hr	Over 6hr	Total
More than 5m faster	6 (1.8%)	2 (1.4%)	191 (2.8%)
Less than 5m faster	3 (0.9%)	2 (1.4%)	469 (6.8%)
Less than 5m slower	7 (2%)	1 (0.7%)	1048 (15.2%)
More than 5m slower	324 (94.7%)	136 (96.5%)	5148 (74.8%)
Unknown	2 (0.6%)		29 (0.4%)
Total	342	141	6885

Grandma's Marathon Statistics

I've put together the stats for last Saturday's Grandma's Marathon. The overall average chip time that I calculated was 4:19:05. The 4:22:28 time that I mentioned in my previous post was from a news article. I suppose this could be gun time.

Out of the 6885 finishers, 63% were males. The 20s trend continues. The largest age group for women are the 20s. There're even more women finishers in their 20s than men (53%).

The fastest city was St Louis Park Minnesota. It had 104 runners with an average time of 4:11:55. The fastest state was Nebraska which had 53 runners with an average time of 4:05:40. Finally, Kenya easily won as the fastest country. It's 11 runners averaged 2:22:41. As I mentioned in the last post, the first and second place men were from Kenya and the 10 of the top 20 men were from Kenya.

Below are the detailed stats. These are based on the 6/18/2005 results from onlineraceresults.com.

Total Runners by Times

under 3:00	3:00 to 4:00	4:00 to 5:00	over 5:00
168 (2%)	2372 (34%)	3145 (46%)	1200 (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	2 (2%)	34 (41%)	36 (44%)	10 (12%)
twenties	48 (6%)	365 (42%)	341 (40%)	107 (12%)
thirties	53 (4%)	554 (45%)	505 (41%)	114 (9%)
forties	40 (3%)	569 (45%)	511 (41%)	135 (11%)
fifties	6 (1%)	240 (33%)	347 (48%)	132 (18%)
sixties	1 (1%)	37 (20%)	84 (46%)	59 (33%)
seventies	0 (0%)	1 (8%)	3 (23%)	9 (69%)
eighties+	0 (0%)	0 (0%)	0 (0%)	1 (100%)
Total	150 (3%)	1800 (41%)	1827 (42%)	567 (13%)

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%)	5 (9%)	32 (57%)	19 (34%)
twenties	3 (0%)	208 (21%)	538 (55%)	229 (23%)
thirties	9 (1%)	212 (28%)	380 (51%)	145 (19%)
forties	6 (1%)	131 (23%)	272 (48%)	159 (28%)
fifties	0 (0%)	16 (9%)	92 (52%)	70 (39%)
sixties	0 (0%)	0 (0%)	3 (27%)	8 (73%)
seventies	0 (0%)	0 (0%)	0 (0%)	3 (100%)
eighties+	0 (0%)	0 (0%)	1 (100%)	0 (0%)
Total	18 (1%)	572 (23%)	1318 (52%)	633 (25%)

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

Ages	Number	Percent	Mean Time	Best Time
teens	138	2%	4:28:20	2:47:37
twenties	1839	27%	4:20:53	2:13:18
thirties	1972	29%	4:12:39	2:13:32
forties	1823	26%	4:16:05	2:24:27
fifties	903	13%	4:27:37	2:48:39
sixties	192	3%	4:43:52	2:57:14
seventies	16	0%	5:22:45	3:34:54
eighties+	2	0%	5:25:09	4:57:20
Total	6885	100%	4:19:05	2:13:18
Fastest Ages (by average)
thirties	1972	29%	4:12:39	2:13:32

Average/Best Times By Male Age Groups

Ages	Number	Percent	Mean Time	Best Time
teens	82	2%	4:14:02	2:47:37
twenties	861	20%	4:08:01	2:13:18
thirties	1226	28%	4:04:58	2:13:32
forties	1255	29%	4:07:16	2:24:27
fifties	725	17%	4:21:20	2:48:39
sixties	181	4%	4:40:50	2:57:14
seventies	13	0%	5:15:02	3:34:54
eighties+	1	0%	5:52:58	5:52:58
Total	4344	100%	4:10:52	2:13:18
Fastest Ages (by average)
thirties	1226	28%	4:04:58	2:13:32

Average/Best Times By Female Age Groups

Ages	Number	Percent	Mean Time	Best Time
teens	56	2%	4:49:17	3:33:12
twenties	978	38%	4:32:13	2:32:44
thirties	746	29%	4:25:17	2:28:42
forties	568	22%	4:35:33	2:33:03
fifties	178	7%	4:53:12	3:17:21
sixties	11	0%	5:33:57	4:18:19
seventies	3	0%	5:56:14	5:16:48
eighties+	1	0%	4:57:20	4:57:20
Total	2541	100%	4:33:09	2:28:42
Fastest Ages (by average)
thirties	746	29%	4:25:17	2:28:42

Average/Best Times By Cities (cutoff=50)

City	Number	Percent	Mean Time	Best Time
Apple Valley, MN	59	1%	4:27:59	3:09:06
Bloomington, MN	96	1%	4:16:53	2:47:10
Burnsville, MN	54	1%	4:16:08	2:46:46
Duluth, MN	237	3%	4:20:27	2:48:37
Eagan, MN	79	1%	4:20:35	2:53:15
Eden Prairie, MN	79	1%	4:13:59	2:47:32
Edina, MN	64	1%	4:25:22	3:09:25
Madison, WI	68	1%	4:13:03	2:58:13
Maple Grove, MN	98	1%	4:15:39	2:36:47
Minneapolis, MN	538	8%	4:15:48	2:34:58
Minnetonka, MN	84	1%	4:26:03	3:06:39
Plymouth, MN	103	1%	4:19:21	2:55:29
Rochester, MN	71	1%	4:24:16	2:57:04
St Cloud, MN	50	1%	4:21:17	2:52:56
St Louis Park, MN	104	2%	4:11:55	3:00:50
St Paul, MN	274	4%	4:18:23	2:32:57
Woodbury, MN	71	1%	4:18:49	2:41:39
unknown	113	2%	3:50:39	2:13:18
Below Cutoff	4643	67%	4:20:10	2:23:20
Total	6885	100%	4:19:05	2:13:18
Fastest City (by average)
St Louis Park, MN	104	2%	4:11:55	3:00:50

Average/Best Times By State (cutoff=50)

State	Number	Percent	Mean Time	Best Time
CA	63	1%	4:24:32	2:37:19
CO	70	1%	4:19:24	3:01:51
FL	71	1%	4:41:11	2:49:58
IA	256	4%	4:16:10	2:36:31
IL	199	3%	4:10:08	2:24:27
KS	56	1%	4:27:15	3:07:54
MI	149	2%	4:14:48	2:48:29
MN	4261	62%	4:20:18	2:32:57
MO	54	1%	4:27:27	2:41:19
ND	93	1%	4:33:07	2:52:40
NE	53	1%	4:05:40	2:35:00
OH	58	1%	4:13:12	2:53:31
SD	66	1%	4:17:28	2:45:14
TX	70	1%	4:24:16	2:42:53
WI	807	12%	4:18:33	2:23:20
other	130	2%	3:52:24	2:13:18
Below Cutoff	429	6%	4:15:45	2:28:41
Total	6885	100%	4:19:05	2:13:18
Fastest State (by average)
NE	53	1%	4:05:40	2:35:00

Average/Best Times By Nation (cutoff=5)

Nation	Number	Percent	Mean Time	Best Time
Canada	77	1%	4:11:42	2:50:41
Kenya	11	0%	2:22:41	2:13:18
Russia	5	0%	2:34:05	2:13:45
USA	6772	98%	4:19:34	2:23:20
Below Cutoff	20	0%	3:37:11	2:15:53
Total	6885	100%	4:19:05	2:13:18
Fastest Nation (by average)
Kenya	11	0%	2:22:41	2:13:18

Grandma's Marathon

The Grandma's Marathon took place last Saturday (6/18/05) in Duluth Minnesota. This marathon was listed by runningusa.org as the 11th biggest marathon in the country in 2003. Last Saturday there were 6885 finishers with an average time of 4:22:28.

Duluth Minnesota seems like a good place for a June marathon. Race day temperatures have been pretty nice in its history. In 2004 it was 53° at the start, 57° in 2003, and 50° in 2002. This year's starting temperature was around 57°.

There were a large number of elites who ran. The top 20 men had times under 2:30. Ten of the top 20 men were Kenyans. Both the winner and the second place finisher were from Kenya with times of 2:13:18 and 2:13:33.

For the women, there were 18 who ran under 3:00. The first place woman was from Belarus and finished with 2:28:43.

More race info at startribune.com and marathonguide.com.

Over the next few days, I'll put together the stats for this race.

UT scientist reveals the secrets behind Lance

How does Lance do it? He's the six-time Grand Champion of the Tour de France which was done after coming back from advanced cancer. He's currently preparing for his last Tour de France which will start July 2nd. A scientist from University of Texas, Dr. Edward Coyle has measured the physiological changes in Lance since he was 20 years old. This month he has published a scientific paper about Lance which describes the physiological changes that took place in his body over the years.

Both WebMD and the New York Times provide a summary of Dr. Coyle's paper. Details of Dr. Coyle's research into Lance are available at his UT website.

Here's a summary of what made Lance a champion from Dr. Coyle's results:

An 8% improvement in mechanical efficiency and thus submaximal power when cycling appears to be a major factor in Lance's improvement from age 21 to 28 years.

He has learned how to reduce his body weight and body fat by 10 pounds (5 kg) prior to each of his victories in the Tour de France.

Lance also possesses is the 'drive' and 'mental toughness' needed to train very, very hard. Furthermore, he is intelligent and semi-scientific in his training making sure to focus on 'specificity', especially for France in July.

What really sets Lance apart from the other great athletes is his comeback from advanced cancer. Lance came back to Dr. Coyle 8 months after his cancer treatment ended and asked to see if there was any long-term damage. Dr. Coyle found nothing. There was no reason for Lance to stop competing.

Lance not only went back to competition, but went back with more training and determination. According to Dr. Coyle:

In the next two years his heart got even better, his lactic acid dropped further and, amazingly, his efficiency increased to 23 percent.

Let's hope that before Lance's retirement, he's able to win his 7th Tour de France this July. It won't be easy. You never know what can happen. Before he was diagnosed with cancer in 1996 he had to pull out of the Tour after coming down with bronchitis. Hopefully, his streak will continue for his 7th win. Good luck Lance!

Here's a brief Lance Armstrong Biography:

At age 13 (1985) Lance won the Iron Kids Triathlon. In 1991 he won the USA National Amateur Championship. In 1992 he took 14th place in the Olympic Road Race in Barcelona. In 1993 he took 1st place in the World Championships of Road Racing in Oslo. He also won one stage in the Tour de France. He won one stage of the Tour de France again in 1995. In the 1996 Tour de France he was forced out of the Tour in the sixth stage with bronchitis. He finished 12th place in the 1996 Olympics in Atlanta. In the Olympic Individual Time trial, he finished 6th place.

Then in 1996 at age 25 a life changing event occurred. Lance was diagnosed with testicular cancer. The cancer spread to his lungs, abdomen, and brain. He had brain surgery in October 1996 and received his last chemotherapy treatment in December 1996.

The aggressive form of chemotherapy worked. He was able to fully recover. In addition, he widen his interests beyond cycling. He formed the Lance Armstrong Foundation within months of his diagnosis to help others with their cancer struggles.

He returned to cycling and in 1998 he took 4th place in the World Championships Road Racing and 4th in the Time trial. Then in 1999 at age 27 he took his first 1st place victory at the Tour de France. He would string together 1st place Tour de France victories through 2004. The Olympics continued to prove a difficult challenge. In 2000, he was 13th in the Olympic Road Race and 3rd place in the Olympic individual Time trial.

This Lance Armstrong bio is based on information from several sources including LanceArmstrong.com, the scientific paper published by Dr. Coyle (pdf), and a 1996 Lubbock Online news article.

Technorati Tags: lance armstrong, Tour de France, Cycling

The San Diego Marathon

The San Diego Coca-Cola Zero Rock 'n' Roll Marathon was held last Sunday (6/5/05). In 2003, this was the nation's 6th largest marathon. There were a few things that I found interesting about the men's winner, Kenyan Christopher Cheboiboch. First, it was his third time he had run this marathon. The first was way back in 1998 in which he finished second. The other time was 2000 when he finished fifth. I wonder how common it is for anyone to come back 7 years later and win the race.

The second thing I found interesting is that Cheboiboch was just getting over a flu. Even with flu symptoms he was able to win with the impressive time of 2:09:17.

Looking at the stats for this marathon, I noticed that women have consistently outnumbered men over the years. This year women made up 53% of the finishers. However, women's percentages are trending down. Last year they made up 56% and in 2003 54%. Below are the detailed demographics for the last 3 years which are based from the Rock 'n' Roll Marathon results page.

Year	Male Finishers	Female Finishers	Total Finishers
2005	8044	9069 (53%)	17113
2004	7640	9577 (56%)	17217
2003	7779	9199 (54%)	16978

In future posts, I'll try to provide some more stats.

Technorati Tags: running, marathons, san diego

Austin's 8K and the Men's Winner

A small 8K race was held here in Austin last Saturday (6/4/05) called the News 8 - 8K. The Austin Cable News Channel 8 sponspors the event which started at 8:08am last Saturday. The men's winner, Gilbert Tuhabonye, had a time of 25:47. He had hoped to break 25:00 but it was particularly warm and humid last Saturday with race time temperature of 77°F and humidity of 90%.

Gilbert Tuhabonye is a well-known Austin running coach and runner who had a remarkable story of survival back in his native country of Burundi in Central Africa.

Below are the stats for the News 8 8K from results provided by Run-FAR Racing Services.

Total Runners by Times

under 30	30 to 40	40 to 50	over 50
12 (3%)	88 (23%)	159 (41%)	128 (33%)

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

Ages	under 30	30 to 40	40 to 50	over 50
preteens	0 (0%)	0 (0%)	0 (0%)	3 (100%)
teens	0 (0%)	4 (80%)	1 (20%)	0 (0%)
twenties	2 (6%)	12 (33%)	15 (42%)	7 (19%)
thirties	4 (5%)	21 (25%)	37 (45%)	21 (25%)
forties	5 (9%)	21 (36%)	22 (38%)	10 (17%)
fifties	0 (0%)	9 (30%)	15 (50%)	6 (20%)
sixties	0 (0%)	2 (25%)	4 (50%)	2 (25%)
seventies	0 (0%)	0 (0%)	1 (20%)	4 (80%)
unknown	0 (0%)	4 (24%)	9 (53%)	4 (24%)
Total	11 (4%)	73 (30%)	104 (42%)	57 (23%)

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

Ages	under 30	30 to 40	40 to 50	over 50
preteens	0 (0%)	0 (0%)	0 (0%)	4 (100%)
teens	0 (0%)	1 (25%)	2 (50%)	1 (25%)
twenties	0 (0%)	2 (4%)	24 (53%)	19 (42%)
thirties	1 (2%)	3 (6%)	19 (40%)	25 (52%)
forties	0 (0%)	9 (31%)	8 (28%)	12 (41%)
fifties	0 (0%)	0 (0%)	1 (14%)	6 (86%)
sixties	0 (0%)	0 (0%)	1 (33%)	2 (67%)
seventies	0 (0%)	0 (0%)	0 (0%)	2 (100%)
Total	1 (1%)	15 (11%)	55 (39%)	71 (50%)

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

Ages	Number	Percent	Mean Time	Best Time
preteens	7	2%	1:07:59	53:43
teens	9	2%	40:54	30:13
twenties	81	21%	46:38	26:17
thirties	131	34%	47:22	25:47
forties	87	22%	44:38	27:45
fifties	37	10%	46:15	33:13
sixties	11	3%	50:25	34:56
seventies	7	2%	1:01:50	49:34
unknown	17	4%	46:31	37:37
Total	387	100%	47:02	25:47
Fastest Ages (by average)
teens	9	2%	40:54	30:13

Average/Best Times By Male Age Groups

Ages	Number	Percent	Mean Time	Best Time
preteens	3	1%	1:03:01	53:43
teens	5	2%	36:27	30:13
twenties	36	15%	42:47	26:17
thirties	83	34%	44:22	25:47
forties	58	24%	42:14	27:45
fifties	30	12%	43:51	33:13
sixties	8	3%	46:08	34:56
seventies	5	2%	57:13	49:34
unknown	17	7%	46:31	37:37
Total	245	100%	44:06	25:47
Fastest Ages (by average)
teens	5	2%	36:27	30:13

Average/Best Times By Female Age Groups

Ages	Number	Percent	Mean Time	Best Time
preteens	4	3%	1:11:43	56:27
teens	4	3%	46:29	39:32
twenties	45	32%	49:43	35:45
thirties	48	34%	52:33	28:37
forties	29	20%	49:27	31:50
fifties	7	5%	56:30	41:14
sixties	3	2%	1:01:51	49:12
seventies	2	1%	1:13:23	1:11:32
Total	142	100%	52:04	28:37
Fastest Ages (by average)
teens	4	3%	46:29	39:32

Average/Best Times By Cities (cutoff=5)

City	Number	Percent	Mean Time	Best Time
AUSTIN	208	54%	46:44	25:47
BUDA	5	1%	52:30	39:49
CEDAR PARK	13	3%	50:25	30:33
ROUND ROCK	21	5%	47:04	32:02
SAN ANTONIO	15	4%	38:36	26:09
Unknown	72	19%	48:28	29:33
Below Cutoff	53	14%	47:14	28:44
Total	387	100%	47:02	25:47
Fastest City (by average)
SAN ANTONIO	15	4%	38:36	26:09

Technorati Tags: running, austin

Boulder 10K and High Altitude Effects

With an elevation of around 5300 feet, the Bolder Boulder 10K may provide some insights into how high altitude effects running. Before crunching the numbers, I first did some research.

I found this useful CoolRunning thread in which a runner asked about what difference he might experience when running the Johannesburg marathon which is at a 6000ft elevation. The replies gave some factors to consider such as the acclimatization time. One reply mentioned that the oxygen levels are about 93% of what they are at sealevel so that can be used as a rough estimate of slowdown. The replies also provided some useful resources such as this Runworks calculator and this Peak Performance article on high altitude training.

Due to the format of the Boulder's 10K results, I wasn't able to get total averages. So I decided to look at the times of individuals and see how much faster they had run in a previous lower-altitude 10K.

First, I looked at the elite runners. The TD Banknorth Beach to Beacon 10K held last August 1st near Portland Maine seemed to provide a good comparison to the Boulder 10K. The Beach to Beacon is near sealevel and the temperature that day was warmer than last week's Boulder 10K. So you would think that any slowdown at Boulder should be due to the altitude.

I found 3 elite men and 1 elite woman who ran both races. All four had faster times at Beach to Beacon 10K. Below is a comparison of the times:

Runner	2005 Boulder 10K	2004 Beach to Beacon 10K	Change
Thomas Kiplitan	29:32	27:39	1:57
Gilbert Okari	29:39	27:35	2:04
Tekeste Kebede	29:36	29:11	0:25
Masako Chiba (F)	33:54	31:51	2:03
Average Change			1:37

So for these 4 elite athletes, the average slowdown was 1:37. The Runworks Running Calculator predicted about a 46 second slowdown.

I then looked at average runners. I pulled down the Texas runners who had run the last 3 Bolder Boulder 10Ks from the Bolder Boulder Citizens Race Results page. I then used this data with the data from the last three years of the Austin Capitol 10K results to find those runners who had run both races in the same year. So if you ran the Austin Capitol 10K, how much slowdown should you expect when you run the Boulder 10K?

Austin is not at sealevel but it's close. Its elevation is around 500ft. The temperature differences between the races were minimal for 2005 and 2003. Like Boulder, Austin temps during the race were in the 50's. In 2004, Austin was warmer with a race time temp of 71°F.

I thought I would find more runners who had run both races. I found only 9 this year, 14 in 2004, and 14 in 2003. The sample is a little larger than the elites but still not as much as I had hoped. Another factor that may complicate comparisons is the Boulder finish times. There is no distinction between chip and gun finish times. Boulder uses a wave system to start, so I'm assuming the Boulder times are essentially chip times.

The tables below provide the detailed results. I tried to summarize these results in two ways. First I took the average of the runners whose times were within 10 minutes of their Cap10K and Boulder 10K times. I assumed other factors besides elevation may have affected those runners who had more than 10 minute differences. I also looked specifically at runners who ran both under 60 minutes (in addition to less than a 10-minute delta.) Below are the results.

Slowdown of Runners at Boulder 10K vs Austin's Cap10K
Excluding those with >10-min deltas:
2005 :  7 runners averaged: 4:23
2004 : 11 runners averaged: 0:52
2003 : 14 runners averaged: 1:56
Average:                    2:24
Excluding those with >10-min deltas and times over 60 minutes:
2005 :  3 runners averaged: 1:05
2004 :  7 runners averaged: 0:57
2003 : 11 runners averaged: 1:33
Average:                    1:12

Including over-60-minute runners, the average of 2:24 minute slowdown is close the the slowdown predicted by Runworks calculator of 2:16 for a 60-minute runner. The average 1:12 slowdown of those who ran under 60 minutes is quite a bit less. Perhaps if I had a larger sample, it would be closer. The detailed results are below.

2005

Boulder vs Austin Change	Number	Percent
over 10 min faster		0
5 to 10 min faster		0
2 to 5 min faster		0
0 to 2 min faster		0
0 to 2 min slower	2	22.2
2 to 5 min slower	2	22.2
5 to 10 min slower	3	33.3
over 10 min slower	2	22.2
Total	9	100

2004

Boulder vs Austin Change	Number	Percent
over 10 min faster	1	7.1
5 to 10 min faster		0
2 to 5 min faster		0
0 to 2 min faster	5	35.7
0 to 2 min slower	2	14.3
2 to 5 min slower	4	28.6
5 to 10 min slower		0
over 10 min slower	2	14.3
Total	14	100

2003

Boulder vs Austin Change	Number	Percent
over 10 min faster		0
5 to 10 min faster		0
2 to 5 min faster		0
0 to 2 min faster	3	21.4
0 to 2 min slower	6	42.9
2 to 5 min slower	2	14.3
5 to 10 min slower	3	21.4
over 10 min slower		0
Total	14	100

Technorati Tags: running, 10K, boulder