The 10K ConocoPhillips Rodeo Run in Houston

Here are some stats that I've pulled together from the 10K ConocoPhillips Rodeo Run at Houston last Saturday (2/26/05). The stats are based on data from doitsports.com. More info is available at the race's main website.

The winning times include 31:30 for the men and 34:02 for the women.

The weather wasn't the best for running. At the start of the race around 9:50am the temperature was 51 deg F with a 9mph average north wind and light rain.

I've listed the stats below. One new thing I did was to break out the average times by city. To keep the table from getting too big, I only list cities with 10 or more race participants. The city with the fastest average time was Austin with 47:16. Besides Houston, the city with the most runners was Katy Texas with 152. Katy is a small town about 20mi west of Houston on I-10.

The total number of 10K runners were 2941. 62% of the Runners were male and 38% were women. As I noted in the Austin half marathon, women in their twenties are outnumbering the men. In this age group, there were 303 women but only 273 men.

10K Participants by City

City	Number	Percent	Mean Chiptime
Austin	12	0%	47:16
Baytown	14	0%	51:32
Beaumont	12	0%	54:41
Bellaire	35	1%	56:48
Conroe	27	1%	58:57
Cypress	69	2%	58:17
Deer Park	21	1%	58:54
Friendswood	28	1%	1:00:02
Galveston	13	0%	58:30
Houston	1677	57%	57:01
Humble	42	1%	58:44
Katy	152	5%	57:12
Kingwood	62	2%	57:16
League City	35	1%	56:28
Missouri City	37	1%	59:01
Montgomery	12	0%	54:23
Pasadena	25	1%	54:55
Pearland	75	3%	58:55
Richmond	18	1%	57:49
Seabrook	19	1%	51:52
Spring	92	3%	58:06
Sugar Land	89	3%	59:12
Sugarland	11	0%	52:35
The Woodlands	67	2%	55:02
Tomball	24	1%	58:44
other	263	9%	57:38
unknown	10	0%	?
Total	2941	100%	57:13

10K Participants by Age Group

AgeGroup	Number	Percent	Mean Chiptime
preteens	8	0%	59:36
teens	86	3%	54:29
twenties	576	20%	57:19
thirties	895	30%	56:42
forties	831	28%	56:54
fifties	420	14%	57:54
sixties	95	3%	1:00:43
seventies	14	0%	1:06:40
eighties+	5	0%	1:13:53
unknown	11	0%	?
Total	2941	100%	57:13

10K Participants by Sex

Sex	Number	Percent	Mean Chiptime
F	1114	38%	1:02:07
M	1827	62%	54:13
Total	2941	100%	57:13

10K Female Participants by Age Group

AgeGroup	Number	Percent	Mean Chiptime
preteens	5	0%	1:03:01
teens	23	2%	59:14
twenties	303	27%	1:00:46
thirties	372	33%	1:01:43
forties	284	25%	1:02:31
fifties	109	10%	1:04:59
sixties	15	1%	1:10:55
seventies	1	0%	1:41:30
eighties+	2	0%	1:15:01
Total	1114	100%	1:02:07

10K Male Participants by Age Group

AgeGroup	Number	Percent	Mean Chiptime
preteens	3	0%	53:54
teens	63	3%	52:46
twenties	273	15%	53:29
thirties	523	29%	53:08
forties	547	30%	53:59
fifties	311	17%	55:26
sixties	80	4%	58:49
seventies	13	1%	1:03:59
eighties+	3	0%	1:13:08
unknown	11	1%	?
Total	1827	100%	54:13

If you would like to see any other stats related to this race feel free to leave a comment.

Are Women Catching Up With Men?

A Runner's World article asked the question "Are Women Catching Up With Men?". Some have theorized that women may have physical advantages over men at ultra endurance events. Women are getting closer to the men in the marathon. For example, the men's world record for the marathon is 2:04:55 while the women's recoard is 2:15:25 (only about 8% difference).

The author of this article described a study he had done in the 90's in which a sample of subscribers to Runner's World provided their gender and best 5K and marathon times. The results show that the men's marathon times were 10.71 times slower over their 5K times. However, the women's marathon times were 10.45 times slower. So there was slight indication that women slow down less in long distance races.

The author admits, however, there were too many variables to draw the conclusion that women are naturally better at long distances.

Nevertheless, I thought I would look at the same thing based on the stats from my previous post. Who slowed down the most from the half marathon to the full? Men or Women? As in the case with the Runner's World study, there are too many other variables to reach definite conclusions. But just for fun, I ran the numbers. Here's what I found:

In 2005, women's mean full marathon times were 2.01 times greater than women's mean half marathon time (4:50:44/2:24:34).

The men's ratio is 2.08 (4:19:24/2:04:31). So just like the Runner's World study, women had less of a slowdown.

The results are similar in 2004: women's ratio is 2.08 (4:45:02/2:16:54) and the men's ratio is 2.12 (4:10:08/1:57:52). Again, the women had less of a slowdown.

Any idea why this is the case? Perhaps men tend to start out too fast? (BTW, comments are appreciated!)

I wonder how common this trend is? I'll keep looking at this in future races.

More Austin Marathon Results

From yesterday's analysis, I realized that it's important when comparing race results between years to break the stats by sex in addition to age. As the data shows, the ratio of women to men can change significantly from year to year. And since women's times tend to be slower than men's, it can affect the overall average times.

So here are the stats comparing 2005 with 2004. I've tried something different this time by using html tables (I've learned that tables in blogger require avoiding new lines). I've broken up the runners by sex and age for both the full and half marathons. All stats are mean times. I also have the median times, but these are pretty close to the means. If someone is interested in these, I can also post them.

Full Marathon

Results For The Women

Age Group	2005 Time	2004 Time	Difference
teens	5:01:45	4:35:16	26:29
twenties	4:49:03	4:42:00	07:03
thirties	4:47:04	4:39:21	07:43
forties	4:47:39	4:43:11	04:28
fifties	5:17:22	5:27:24	-10:02
sixties+	5:59:10	5:48:32	10:38
Overall	4:50:44	4:45:02	05:41

Results For The Men

Age Group	2005 Time	2004 Time	Difference
teens	4:05:48	4:05:50	-00:02
twenties	4:16:01	4:06:36	09:25
thirties	4:15:26	4:03:17	12:09
forties	4:14:58	4:08:48	06:10
fifties	4:30:29	4:24:02	06:27
sixties+	5:09:40	4:51:55	17:45
Overall	4:19:24	4:10:08	09:15

Half Marathon

Results For The Women

Age Group	2005 Time	2004 Time	Difference
teens	2:16:40	2:08:54	07:46
twenties	2:18:06	2:13:03	05:03
thirties	2:22:53	2:15:16	07:37
forties	2:26:45	2:19:21	07:24
fifties	2:44:24	2:31:56	12:28
sixties+	2:59:52	2:58:48	01:04
Overall	2:24:34	2:16:54	07:39

Results For The Men

Age Group	2005 Time	2004 Time	Difference
teens	1:57:26	2:00:11	-02:45
twenties	2:00:52	1:55:16	05:36
thirties	2:02:57	1:56:02	06:55
forties	2:02:31	1:57:07	05:24
fifties	2:13:18	2:02:38	10:40
sixties+	2:20:46	2:17:36	03:10
Overall	2:04:31	1:57:52	06:39

Stats are derived from data posted at the Freescale Austin Marathon site.

Women Are Taking Over

That's at least true for the shorter races. In 2005 Austin Freescale Half Marathon, women outnumbered the men by a factor of 1.43. In 2004 it was 1.39.

However, it's almost reverse in the full marathon: men outnumbered women in 2005 by a factor of 1.52 and 1.39 in 2004.

In my previous post I mentioned how it was odd that there was more of a slowdown in 2005 half marathon than in the 2005 full marathon. The weather should have had less of an effect in the half marathon, and thus times between 05 and 04 should have been similar.

The problem was that I left out the men/women numbers in the comparison. This is important since women tend to have slower times (on average) than men.

For example, in 2005 and 2004 half marathons, women were slower than men by a factor of 1.16. This is also very similar to the full marathon: 1.12 in 2005 and 1.14 in 2004.

So comparing 2005 to 2004, the women to men ratio increased in the half marathon but decreased in the full marathon. Thus, the average time for all runners would be expected to increase in 2005 just based on the ratio changes of women to men.

So I think that explains the 2005 half marathon time mystery (probably not as exciting as a murder mystery).

Austin Is Not Alone In These Numbers

What brought this issue to my attention was this Green Bay Press-Gazette article on its city marathon. The race director for that marathon had been looking at the demographics of the 2004 race and found some very interesting trends.

Here's an excerpt from this article:


"When Ryan started looking at the demographics of last year's Cellcom marathon, he was astonished to see the number of twenty-something women who were participating, particularly in the half-marathon and 5K Family Run/Walk, the two events that have shown significant growth.

...

"Among the 4,356 individuals who participated in the three main events in 2004 -- marathon, half-marathon and 5K Family Run/Walk -- men outnumbered women 53 percent to 47 percent, thanks to a 2-1 margin among full marathon competitors.

However, there were more women than men in the half-marathon and 5K Family Run/Walk. The gender gap was especially evident among young adults."


It looks like Austin shares these similar trends. The number of women running the short races are increasing and far outnumber the men. And just like in Green Bay, most of the women are in their twenties and thirties. In this age group for the Austin Half Marathon, women outnumber men by a factor of 1.71 in 2005 and by a factor of 1.73 in 2004.

The article mentions how understanding the demographics can help to understand the motivations of the runners. Here's another excerpt:


"These are runners -- more often women than men -- whose purpose in training isn't to record some unbelievable time, qualify for the Boston Marathon, or beat their neighbor. Rather, it's to fulfill a lifelong goal of completing an endurance run."


Below are all the age stats for the Austin 2005 and 2004 full and half Marathons.

Finally, this Green Bay marathon sounds like a pretty cool race. Runners get to run through Lambeau Field. If you're a Packer fan, this could be for you.

Austin Half Marathon Number Of Runners:

2005 Number of Women/Men = 1.43
2004 Number of Women/Men = 1.39

Women:

Age Group  # 05  # 04  Diff  % Diff
---------  ----  ----  ----  ------
    teens    61    56     5      9%
 twenties   629   546    83     15%
 thirties   755   588   167     28%
  forties   450   368    82     22%
  fifties   180   124    56     45%
 sixties+    36    18    18    100%
---------  ----  ----  ----  ------
    Total  2111  1700   411     24%

Men:

Age Group  # 05  # 04  Diff  % Diff
---------  ----  ----  ----  ------
    teens    41    27    14     52%
 twenties   291   244    47     19%
 thirties   516   411   105     26%
  forties   356   355     1      0%
  fifties   202   144    58     40%
 sixties+    68    46    22     48%
---------  ----  ----  ----  ------
    Total  1474  1227   247     20%


Austin Full Marathon Number Of Runners:

2005 Number of Women/Men = 0.66
2004 Number of Women/Men = 0.72

Women:

Age Group  # 05  # 04  Diff  % Diff
---------  ----  ----  ----  ------
    teens    19    28    -9    -31%
 twenties   529   602   -73    -11%
 thirties   704   726   -22     -2%
  forties   461   529   -68    -12%
  fifties   130   145   -15     -9%
 sixties+    18    17     1      6%
---------  ----  ----  ----  ------
    Total  1861  2047  -186     -8%

Men:

Age Group  # 05  # 04  Diff  % Diff
---------  ----  ----  ----  ------
    teens    25    31    -6    -18%
 twenties   440   460   -20     -3%
 thirties   970   985   -15     -1%
  forties   855   871   -16     -1%
  fifties   437   398    39     10%
 sixties+    92   100    -8     -7%
---------  ----  ----  ----  ------
    Total  2819  2845   -26      0%

Stats are derived from data posted at the Freescale Austin Marathon site.

Time For The Half Marathon Stats

Don't know why it took me so long, but here are some of Freescale Austin Half Marathon stats. I was talking to a coworker today who mentioned that he ran the half. It then occurred to me that I've been neglecting the half. Finally, when a post at runtex forums gave the same thought, I knew it was time.

You would think that there would be less of a slowdown in 2005 in the half since runners were able to finish before it got too hot and humid. However, that's not the case. All age groups ran slower in 2005 as compared to 2004. The slowdowns were between 2 and 12 minutes.

Interestingly, the biggest slowdowns in the half were the runners in their 50s. The full marathon 50 year olds had the least slowdown.

After thinking about this, I have a theory about why there was more of a slowdown in the half than in the full. I have to do some more crunching of the numbers first. I'll be sure to report back.

Here are the stats that I derived from the 2005 Freescale Half Marathon and 2004 Motorola Half Marathon.

Year: 2005

                     Mean      Median    Mean Chg
Age Group # in Group Chip Time Chip Time From 2004
--------- ---------- --------- --------  ---------
    teens    102     2:08:56   2:05:52   02:52
 twenties    920     2:12:39   2:10:28   05:06
 thirties   1271     2:14:47   2:10:41   07:26
  forties    806     2:16:03   2:12:32   07:37
  fifties    382     2:27:58   2:20:20   11:46
 sixties+    104     2:34:18   2:27:31   05:07


Year: 2004

                     Mean      Median   
Age Group # in Group Chip Time Chip Time
--------- ---------- --------- -------- 
    teens     83     2:06:04   2:00:02          
 twenties    790     2:07:33   2:04:52          
 thirties    999     2:07:21   2:04:52          
  forties    723     2:08:26   2:03:35          
  fifties    268     2:16:12   2:08:58          
 sixties+     64     2:29:11   2:23:07          

Note: Some runners were excluded due to strange
fields (like a runner under 19 with an age of two)

My Grandma Runs Faster Than You?

Well, that may actually be a complement. Old runners seem to do very well in marathons such as the Austin Freescale Marathon. By applying my stats programs to the 2005 and 2004 Austin Marathons, I was able to get the average finish times (chip) by major age groups. These breakdowns make for more readable stats than in my previous post.

Interesting, the average finish times for each age group are all very close. The teens, twenties, thirties, and forties all have mean and median times right around 4.5 hours. The fifties are a little higher, and sixties+ (which lumps 70 and 80 year olds with the 60 year olds) are also a little higher.

But for sixty year olds to run a marathon in low five hours is an impressive accomplishment.

Another thing I wanted to look into was how the times changed from last year. Were the average finish times slower? As previous data shows, times this year were slower. All age groups had slower average times. The fifty year olds had the least slowdown with less than a minute slower race than last year. The largest slowdown was with those above sixty. The heat and the humidity this year hit hard, especially for those who finished after 5 hours. So those who ran slower were more prone to worse times. That's my guess anyway.

The numbers of runners in the age group is also interesting. Not many teens seem to run marathons. In fact, there were more runners over 60 than under 20. Most of the runners are in their thirties or forties. Running marathons seem to gain popularity as you age until you hit your late forties. I suppose at that time, old age starts to take its toll. But for those who can tough it out (and have some good luck), you should be able to run well into your 70's.

Year: 2005

                     Mean      Median    Mean Chg
Age Group # in Group Chip Time Chip Time From 2004
--------- ---------- --------- --------  ---------
    teens     44     4:29:58   4:26:59   10:10
 twenties    970     4:34:03   4:29:24   07:23
 thirties   1674     4:28:44   4:23:51   10:09
  forties   1317     4:26:25   4:19:40   04:37
  fifties    567     4:41:14   4:32:11   00:16
 sixties+    110     5:17:46   5:13:27   17:38

Year: 2004

                     Mean      Median
Age Group # in Group Chip Time Chip Time
--------- ---------- --------- --------
    teens     59     4:19:48   4:17:14          
 twenties   1062     4:26:40   4:22:05          
 thirties   1711     4:18:35   4:10:48          
  forties   1400     4:21:48   4:13:00          
  fifties    543     4:40:58   4:29:09          
 sixties+    117     5:00:08   4:55:38          

Note, several runners without age data were excluded.
Times are chip times and not total times.

Marathon Times by Age

In this month's Freescale Marathon, I wanted to find the average finish times by age. And then I wanted to compare these average time to last year's. What are the average finish times? And how did they change?

As previous results show, this year's marathon was tough due to the high temperature and humidity. 39 age groups ran slower than last year while only 20 ran faster.

If your marathon time is between 4 and 5 hours, you're pretty average, unless you're over 60. I'm amazed at the average times of the 50+ runners. There are many 50 to 70 year olds who ran the marathon in under 5 hours.

I'm not sure if you can take as fact the finish times of some of the very old runners. I suppose runners may put down old ages for the fun of it. But if these times are real, they would be impressive. For example, in 2004, two 70 year olds averaged 3:34:35 finish times. I checked the stats and confirmed this. One finished at 3:22:42 and the other finished at 3:46:28. In 2005, the most impressive old-age result is a 79 year old runner who finished in 5:31:18.

And here are the numbers:

Year: 2004
               Average
    Number At  Finish
Age That Age   Times
--- ---------  -------
13     1       4:06:05          
14     1       5:48:18          
15     3       5:42:44          
16     3       4:50:44          
17     8       4:02:09          
18    15       4:35:56          
19    28       4:08:57          
20    54       4:30:26          
21    52       4:34:02          
22    69       4:32:56          
23    81       4:38:15          
24   112       4:24:27          
25   119       4:32:14          
26   119       4:32:40          
27   138       4:26:15          
28   143       4:35:50          
29   175       4:27:19          
30   142       4:31:51          
31   143       4:27:18          
32   163       4:27:27          
33   198       4:25:02          
34   185       4:19:53          
35   180       4:21:58          
36   173       4:19:56          
37   162       4:17:55          
38   195       4:14:27          
39   168       4:19:54          
40   207       4:21:06          
41   188       4:24:08          
42   153       4:14:44          
43   133       4:21:46          
44   133       4:19:27          
45   134       4:25:10          
46   142       4:28:28          
47   121       4:29:58          
48    86       4:32:54          
49   102       4:49:38          
50    93       4:42:07          
51    88       4:37:06          
52    60       4:34:39          
53    55       5:02:14          
54    67       4:32:41          
55    51       4:53:30          
56    48       4:39:14          
57    40       4:50:57          
58    14       4:53:35          
59    28       5:19:17          
60    25       4:55:30          
61    14       5:14:47          
62    12       5:08:43          
63    11       4:49:16          
64     8       4:53:32          
65    13       4:49:59          
66     5       4:36:30          
67     5       5:03:21          
68     4       4:53:13          
69     7       5:48:18          
70     2       3:34:35          
71     2       5:41:13          
72     4       4:41:08          
74     1       6:48:19          
75     2       5:59:02          
79     1       7:34:39          
83     1       8:05:44          

Year: 2005
               Average   Changes
    Number At  Finish    From Last
Age That Age   Times     Year
--- ---------  -------   -------
15     2       4:57:28    -45:16
16     6       4:44:51    -05:53
17     4       4:13:03     10:54
18     7       4:23:54    -12:02
19    22       4:27:47     18:50
20    35       4:33:12     02:46
21    49       4:30:12    -03:50
22    57       4:30:21    -02:35
23    59       4:41:00     02:45
24    92       4:40:18     15:51
25   117       4:34:49     02:35
26   130       4:30:32    -02:08
27   126       4:42:53     16:38
28   143       4:38:32     02:42
29   129       4:42:41     15:22
30   130       4:35:49     03:58
31   150       4:32:48     05:30
32   149       4:30:07     02:40
33   162       4:36:02     11:00
34   183       4:30:21     10:28
35   180       4:35:50     13:52
36   161       4:26:45     06:49
37   172       4:30:43     12:48
38   159       4:31:40     17:13
39   181       4:31:18     11:24
40   162       4:17:54    -03:12
41   153       4:32:24     08:16
42   156       4:26:37     11:53
43   132       4:27:38     05:52
44   136       4:24:30     05:03
45   122       4:34:20     09:10
46   103       4:30:59     02:31
47   124       4:37:30     07:32
48    93       4:31:06    -01:48
49    84       4:33:53    -15:45
50   110       4:39:30    -02:37
51    86       4:38:07     01:01
52    66       4:37:29     02:50
53    55       4:52:16    -09:58
54    60       4:54:23     21:42
55    43       4:29:58    -23:32
56    40       4:48:17     09:03
57    44       5:01:50     10:53
58    27       4:52:46    -00:49
59    20       4:46:09    -33:08
60    24       4:51:00    -04:30
61    10       5:19:01     04:14
62    12       5:37:36     28:53
63    16       5:37:47     48:31
64     3       4:50:51    -02:41
65     7       5:23:24     33:25
66    13       5:30:12     53:42
67     3       4:34:12    -29:09
68     2       6:05:29   1:12:16
69     4       5:02:20    -45:58
70     3       5:51:28   2:16:53
72     3       6:04:32   1:23:24
73     2       4:16:26          
74     1       6:28:27    -19:52
79     1       5:31:18  -2:03:21
80     1       7:49:40          

Number of age groups finishing faster in 2005 = 20
Number of age groups finishing slower in 2005 = 39

Note 1: Negative "Changes From Last Year" mean the
runners ran faster in 2005.
Note 2: Finish times were used instead of chip times.

Pace Changes - First vs. Second Half of Austin Freescale Marathon

Intro

Maintaining a constant pace through out a marathon is tough even in perfect conditions. Last Sunday's heat and humidity were anything but perfect for marathons. As would be expected, very few were able to keep a consistent pace.

I did these split stats a little differently than what I did for the 2004 marathon. The stats at doitsports for 2005 were in a little different format than previous marathons. The 2005 split times and paces were cumulative. So I haven't yet repeated the stats that I did for the 2004 marathon.

For now, I've coded up some new programs to look at the paces between the first and second half of the marathon. I partitioned the paces into speedup/slowdown minutes. For example, those who ran the second half 1 to 2 minutes faster than the first half were put into the "-2:00 to -1:00" category. For those who ran the second half 1 to 2 minutes slower than the first half were put into the "1:00 to 2:00" category.

Note, I had to exclude some runners who had fields with invalid data. So that's why my total is less than the 4958 total given at doitsports. Also note that I used the chip times. This created a little complication since the halfway pace provided in the stats was based on clock time. I had to do a little math to ensure both halves were based on chip times. This helps avoid having the stats skewed by runners who started far behind the starting lines.

Results

The first set of stats show the pace changes for all runners. Out of 4576 runners, I found only 147 (about 3%) who ran faster in the second half as compared to the first half. Out of these 147, only 9 ran 1 to 2 minutes/mile faster. The rest just ran up to 1 minute/mile faster.

About 97% of all runners ran the second half slower. 61% of the runners had second half paces up to 2 minutes/mile slower. 29% had paces between 2 and 4 minutes/mile slower, and 6% had paces over 4 minutes/mile slower. The missing 1% is due to roundoff errors.

I then wanted to know how this compared based on marathon finish times. I would expect the more experienced runners to have more consistent paces. So I looked at these pace for runners who ran the marathon under 3 hours, between 3 and 4 hours, between 4 and 5 hours, and over 5 hours.

As would be expected, the sub 3 runners were very consistent. 95% of them ran the second half within a minute/mile pace of the first. Only 5 out of 104 runners had slowdowns of over 1 minute/mile.

There were 1297 sub 4 runners. The consisteny starts to fall here. Only 59% maintained a second half pace within a minute/mile of the first. But most were able to keep a decent pace to finish sub 4.

Most of the runners fell into the sub 5 category (finishing between 4 and 5 hours). There were 1954 runners in this category. And you can see that the consistency again went down. 74% of these runners ran the second half over a minute/mile slower than the first.

Finally, the runners who ran the marathon in over 5 hours had even more second half slowdowns. About 87% of them ran the second half over a minute/mile slower than the first.

I'm sure a lot of these folks probably were hit hard by the heat and the humidity. One thing I'm going to work on is to compare these 2005 stats with those from 2004 and earlier. Also, I would like to see how paces vary based on age and sex. If you have any stats that you would like to see, feel free to leave a comment. I can't promise anything, but I can give it a try.

'Change In Pace' is the change in mintues/mile
between the first half and the second half.
Negative means faster second half.


All those who ran the marathon at all different paces.

 Change In Pace       #     %
 --------------    ----   ---
 -2:00 to -1:00       9    0%
  -1:00 to 0:00     138    3%
   0:00 to 1:00    1369   30%
   1:00 to 2:00    1403   31%
   2:00 to 3:00     890   19%
   3:00 to 4:00     477   10%
      over 4:00     290    6%
 --------------    ----   ---
          Total    4576

Those who ran the marathon in under 3 hours.

 Change In Pace       #     %
 --------------    ----   ---
  -1:00 to 0:00       3    3%
   0:00 to 1:00      96   92%
   1:00 to 2:00       4    4%
   2:00 to 3:00       1    1%
 --------------    ----   ---
          Total     104

Those who ran the marathon between 3 and 4 hours.

 Change In Pace       #     %
 --------------    ----   ---
  -1:00 to 0:00      61    5%
   0:00 to 1:00     700   54%
   1:00 to 2:00     426   33%
   2:00 to 3:00      96    7%
   3:00 to 4:00      14    1%
 --------------    ----   ---
          Total    1297

Those who ran the marathon between 4 and 5 hours.

 Change In Pace       #     %
 --------------    ----   ---
 -2:00 to -1:00       6    0%
  -1:00 to 0:00      51    3%
   0:00 to 1:00     449   23%
   1:00 to 2:00     714   37%
   2:00 to 3:00     477   24%
   3:00 to 4:00     192   10%
      over 4:00      65    3%
 --------------    ----   ---
          Total    1954

Those who ran the marathon in over 5 hours.

 Change In Pace       #     %
 --------------    ----   ---
 -2:00 to -1:00       3    0%
  -1:00 to 0:00      23    2%
   0:00 to 1:00     124   10%
   1:00 to 2:00     259   21%
   2:00 to 3:00     316   26%
   3:00 to 4:00     271   22%
      over 4:00     225   18%
 --------------    ----   ---
          Total    1221

Did You Improve Your Marathon Time?

The hot and humid weather yesterday made it tough on all the runners. The low was 58 degrees and high was 79 degrees which was way above averages of 44/65. But that wasn't the worst of it. The morning rain followed by the sunny and hot temperatures resulted in brutal humidity. This took its toll on the race times.

To see how it affected the race times, I took the results from doitsports and ran them through my custom program. I also took the results from the 2004 Austin marathon. Then for each runner that ran both, I compared their 2005 time with their 2004 time. As would be expected, most runners had slower times yesterday than they did in 2004 (63%).

Then I wanted to know how did this compare to previous years. So I repeated this analysis for the previous two marathons. In 2004, only 46% ran slower than they did in 2003. In 2003, only 37% ran slower than they did in 2002. So for the last 2 years, most repeat runners improved their time. But not this year.

Austin Marathon Temperature History

For the previous 3 years, the Austin marathon days had much more conducive temperatures for running. Here are the numbers:

High / Low Temperatures at Austin Bergstrom on Marathon days:

2/13/05 - 79 / 58
2/15/04 - 57 / 26
2/16/03 - 53 / 30
2/17/02 - 68 / 27

Austin Marathon Race Stats

And here are details about how repeat runners have faired for the last 3 marathons:

2005 Results As Compared To 2004

Of 3688 runners from yesterday's marathon, I found 1021 who also ran last year.

Of these 1021 runners:
641 (63%) ran slower in 2005
379 (37%) ran faster in 2005

Of those who ran faster:
100 (10%) ran up to 5min faster
64 (6%) ran between 5 and 10min faster
100 (10%) ran between 10 and 20min faster
73 (7%) ran between 20 and 40min faster
42 (4%) ran over 40min faster

2004 Results As Compared To 2003

Of 3962 runners who ran in 2004, I found 693 who also ran in the 2003 marathon.

Of these 693 runners:
319 (46%) ran slower in 2004
372 (54%) ran faster in 2004

Of those who ran faster:
135 (20%) ran up to 5min faster
90 (13%) ran between 5 and 10min faster
85 (12%) ran between 10 and 20min faster
57 (8%) ran between 20 and 40min faster
5 (1%) ran over 40min faster

2003 Results As Compared To 2002

Of 2049 runners who ran in 2003, I found 682 who also ran in the 2002 marathon.

Of these 682 runners:
250 (37%) ran slower in 2003
431 (63%) ran faster in 2003

Of those who ran faster:
92 (14%) ran up to 5min faster
94 (14%) ran between 5 and 10min faster
129 (19%) ran between 10 and 20min faster
80 (12%) ran between 20 and 40min faster
36 (5%) ran over 40min faster

Another Win By Tatiana Borisova

Tatiana Borisova did it again with another win at today's Austin Freescale Marathon. Her time was 2:31:01 which was a little slower than last year. I'm sure if the weather were the same as last year, she would have broken another women's course record. I couldn't believe how hot and humid it was this morning.

Just like last year I saw Tatiana around mile 20. This year was a little different however. Last year two other women runners were running along side her. This year she had about a 3 to 4 minute lead to the other women runners. The second place women finished at 2:34:47.

Unfortunately, I wasn't able to get a good picture of her. She was being escorted by several bicyclist who blocked her view. I did take one picture. I'll post it once I get it developed (still have that cheap film camera).

I'll be working on this years stats. The raw numbers are available now here at doitsports.

Superwoman May Be In Austin Tomorrow

Last year I was amazed by Tatiana Borisova (from Kyrgyzstan) who broke the women course record for the Motorola Marathon. It was her first official marathon and previously she had been just a short distance runner.

Unfortunately, I didn't see her finish since I was helping a friend during the Marathon, however, I was able to see her at around mile 20. She stood out from the other two women in the pack. She was tall, blonde, and looked like she could be a model.

It's hard to appreciate the pace that they run since it's so smooth. But it's fast. I had stopped on my bike to take her picture as she ran by. I then tried to get another picture so I pedaled my bike fast along the edge of the Townlake trail and stopped to get another shot. But as I stopped and turned around, she and the other two runners were already passing me, and I didn't get another shot. Oh well, it really didn't matter since the pictures didn't come out well from my cheap camera. Here's the one picture that I did take.



From what I hear, she is suppose to be running tomorrow at the Austin Freescale Marathon. From sources at RunTex Forum, she was suppose to run the Houston and Arizona marathons earlier this year but did not start. Also she was in last year's Olympics where she ran the 1500m. She came in 14th at her first heat and did not advance. Perhaps it was too hot. Well, unfortunately, it won't be as cool as it was last year for the Marathon. So that may not be good news for her. Either it was the weather last year or it's something about Austin which turned her into Superwoman.

BTW, here are the overall past winners from the Freescale (Motorola) Marathons. And finally, be sure to check out the runners. Here are the prime viewing locations. Come down and see Superwoman in action!

Pace Consistency and Experience

I received a recommendation to break out the pace changes by the pace speed. I thought this would also be interesting. I would think the experienced runners who run 5 to 7 minute/mile paces would more likely keep a consistent pace throughout the marathon as opposed to the more casual runners.

So I tweaked my program and put the 2004 Motorola Marathon data through it. As anticipated, those who did the first 10K at 5 to 7 minute/mile paces were more likely to run at a similar pace at the last 2.7 miles. For example, 74% of those who ran the first 10K between 5 and 6 minutes/mile were able to run the last 2.7 miles within a minute of that pace. That percentage decreased to 50% for those who ran the first 10K between 6 to 7 minutes/mile, 40% for 7 to 8, 42% for 8 to 9, and then it went into the 30% range for all slower paces.

One thing that was mentioned is that the elevation of the marathon course is likely to have a big affect on these numbers. There is a lot of downhill in the first half. The second half flattens out.

In the future I would like to factor in the other splits (in addition to the first and last). Also, I would like to factor in age and sex to see how these affect the numbers. And as always, suggestions and comments are always welcome.

Minutes/mile changes    Number of Runners

in pace between first   and percentage 

10K and last 2.7 miles  within pace change

----------------------  ------------------

Starting pace between 4:00 minute/mile to  5:00 minute/mile

       -0:59 to 0:59       1   100%

Starting pace between 5:00 minute/mile to  6:00 minute/mile

       -0:59 to 0:59      25    74%

        1:00 to 1:59       5    15%

        2:00 to 2:59       3     9%

        4:00 to 4:59       1     3%

Starting pace between 6:00 minute/mile to  7:00 minute/mile

       -0:59 to 0:59     134    50%

        1:00 to 1:59      83    31%

        2:00 to 2:59      20     7%

        3:00 to 3:59      15     6%

        4:00 to 4:59       8     3%

        5:00 to 5:59       7     3%

Starting pace between 7:00 minute/mile to  8:00 minute/mile

       -0:59 to 0:59     264    40%

        1:00 to 1:59     184    28%

        2:00 to 2:59     127    19%

        3:00 to 3:59      40     6%

Starting pace between 8:00 minute/mile to  9:00 minute/mile

       -0:59 to 0:59     471    42%

        1:00 to 1:59     306    27%

        2:00 to 2:59     173    15%

        3:00 to 3:59      99     9%

        4:00 to 4:59      35     3%

Starting pace between 9:00 minute/mile to  10:00 minute/mile

       -0:59 to 0:59     382    33%

        1:00 to 1:59     304    26%

        2:00 to 2:59     217    19%

        3:00 to 3:59     112    10%

        4:00 to 4:59      62     5%

        5:00 to 5:59      30     3%

Starting pace between 10:00 minute/mile to  11:00 minute/mile

      -1:59 to -1:00      25     3%

       -0:59 to 0:59     288    36%

        1:00 to 1:59     191    24%

        2:00 to 2:59     136    17%

        3:00 to 3:59      83    10%

        4:00 to 4:59      24     3%

Starting pace between 11:00 minute/mile to  12:00 minute/mile

      -1:59 to -1:00      17     4%

       -0:59 to 0:59     125    33%

        1:00 to 1:59      83    22%

        2:00 to 2:59      65    17%

        3:00 to 3:59      42    11%

        4:00 to 4:59      23     6%

        5:00 to 5:59      10     3%

Starting pace between 12:00 minute/mile to  13:00 minute/mile

      -1:59 to -1:00      10     5%

       -0:59 to 0:59      64    34%

        1:00 to 1:59      35    19%

        2:00 to 2:59      37    20%

        3:00 to 3:59      20    11%

        4:00 to 4:59       8     4%

Starting pace between 13:00 minute/mile to  14:00 minute/mile

      -1:59 to -1:00       5     5%

       -0:59 to 0:59      34    34%

        1:00 to 1:59      19    19%

        2:00 to 2:59      14    14%

        3:00 to 3:59      11    11%

        4:00 to 4:59       7     7%

        5:00 to 5:59       8     8%

Starting pace between 14:00 minute/mile to  15:00 minute/mile

      -3:59 to -3:00       2     3%

      -1:59 to -1:00       5     8%

       -0:59 to 0:59      21    35%

        1:00 to 1:59      13    22%

        2:00 to 2:59       6    10%

        3:00 to 3:59       9    15%

        4:00 to 4:59       2     3%

        5:00 to 5:59       2     3%

Starting pace between 15:00 minute/mile to  16:00 minute/mile

       -0:59 to 0:59      27    40%

        1:00 to 1:59      15    22%

        2:00 to 2:59       7    10%

        3:00 to 3:59      12    18%

        4:00 to 4:59       2     3%

        5:00 to 5:59       3     4%

Starting pace between 16:00 minute/mile to  17:00 minute/mile

      -2:59 to -2:00       1     6%

      -1:59 to -1:00       4    22%

       -0:59 to 0:59       6    33%

        2:00 to 2:59       7    39%

Starting pace between 17:00 minute/mile to  18:00 minute/mile

       -0:59 to 0:59       2    33%

        1:00 to 1:59       4    67%

------------------------------------------

Note: To reduce the size, percentages under 2% were removed.

So not all pace groups have percentages that add up to 100%.

For more explanation about the chart, refer to the previous post.

Next Sunday's Austin Marathon and Hitting the Wall

Before Sunday I thought it would be interesting to look at last year's results to see how many runners hit the wall.

When you run a marathon, you probably know that a consistent pace is the best way to run. It's easier said than done, especially when you're talking about 26.2 miles.

So I thought it would be interesting to see how many people are able to keep a consistent pace.

From the 2004 Austin Marathon race results, I put everyone's split times through my program and recorded their split time for the first 10K and for their last 2.7 miles. I then grouped the runners by how much their pace changed.

For example, there were 1242 runners who did the last 2.7 miles 1 to 2 minutes slower than their pace for the first 10K (6.2 mi). I defined positive minutes to indicate that the runners ran the last leg slower. Negative numbers mean that they ran it faster.

As can be seen from the numbers, very few people actually ran the last leg more than 1 minute per mile faster than the first leg. However, there were more than 800 who hit the wall and ran the last leg over 3 minutes per mile slower than the first 10K. But the majority of the runners were able to avoid the wall and keep their pace within a minute or two of their starting pace. That's very impressive. Good luck to all who run this Sunday.

Minutes/mile changes

in pace between first

10K and last 2.7 miles  Number Of Runners

----------------------  ------------------

      -3:59 to -3:00       2

      -2:59 to -2:00      13

      -1:59 to -1:00      91

       -0:59 to 0:59    1844

        1:00 to 1:59    1242

        2:00 to 2:59     812

        3:00 to 3:59     443

        4:00 to 4:59     187

        5:00 to 5:59     113

        6:00 to 6:59      45

        7:00 to 7:59      26

        8:00 to 8:59      14

        9:00 to 9:59       4

      10:00 to 10:59       1

      11:00 to 11:59       5

      13:00 to 13:59       1

      25:00 to 25:59       1

-------

Note: Negative time ranges signify that the runners

finished their last 2.7 miles that many mintues/mile

faster than their first 10K.

My Austin Marathon Artwork

The official logo of the Austin Freescale Marathon is not bad, but it doesn't do a good job at combining Freescale and running in my opinion. That's why I came out with my own version.

It combines an integrated circuit package with a silhouette of a runner in the middle. Austin has many other major semiconductor companys than Freescale. So this seems to be something that makes the Austin marathon unique.

You may not appreciate the name above the IC. It's the abbreviation for the Marathon followed by 26.2. Semiconductor companies often give their chips names with cryptic letters and numbers. So I thought this would make a good name for this one (plus this avoided any trademark/copyright infringement).

I've also combined this image with SUB X. After you've finished a marathon, your next goal is to run it in under 5 hours, 4 hours, and maybe even 3 hours. So I thought it would be cool to include this with the logo.

If you would like to purchase products with this logo, click on the image, and you'll be taken to my cafepress storefront where you can order one.

Cafepress is a cool service where anyone with creative ideas can offer their art to the public. Cafepress offers all kinds of shirts, hats, stickers and other stuff that you can attach your artwork to. They've been around for years and are well known for good customer service so there's no worry about buying online.

If you would like use your own service for shirts or other products, you may download the original image. I only ask that you use it for your own private use.

	Click left image to purchase shirts, hats, etc. with this image. Click here to download image for private use.
	Click left image to purchase shirts, hats, etc. with this image. Click here to download image for private use.
	Click left image to purchase shirts, hats, etc. with this image. Click here to download image for private use.
	Click left image to purchase shirts, hats, etc. with this image. Click here to download image for private use.