Dipsea Data (Initial Data)

In response to a thread I've been participating in on the Tamalpa Runners Message Board, I've begun a statistical analysis of Dipsea records. The thread started with the question of whether the boys age 8 handicap gave them a disadvantage over other runners. I don't know anything about the methods actually used and regretably have not had a chance to buy and read Dipsea expert Barry Spitz's book. This may be a benefit to this small project since I can consider a fresh approach.

I promised an analysis which would determine the ideal handicaps for every age/gender combination. As everyone in Marin County, CA and many people outside of Marin knows, the Dipsea is a 7.1 mile trail race, famous for allowing alternate routes and for giving runners head starts based on age and gender. I proposed that handicaps should be based on projected times for each age gender as determined by a best-fit line calculated using historical Dipsea times.

Barry provided me with all of the single age/gender records. There are 162 total records - women aged 5-77 and men aged 6-95, excluding men aged 91 as the record holder Jack Kirk's official time is unavailable. Using this data I've developed 3 graphs which plot each record. Each graph also has a best-fit line. A best fit line is one that best appromixates each Y-value (time) for every X-value (age). For this line I used a polynomial formula with an order of 6. The best-fit line is determined by calculating the minimum variances as determined by comparing the line with the various data points.

Here are the graphs with brief explanation:

This is the master graph. All data is reflected here. Women's data (red) and men's data (blue) are plotted. The women's best-fit line is in green and men's in orange. One thing I noticed is it appears that the women's best-fit line is not a U. The men's is a U - starting at a young age, times get faster to a certain point and then get slower. But the women's seem to bottom out around age 19, then rise a little, then bottom out again in the mid 40's. The data does this too - if you see on Barry's blog, women in their teens can run under an hour, women in their early 20's seem unable to, and women starting at age 26 seem to be able to again. There is possibly a confounding variable there as most of the sub 1 hour times were from the 1980's and the best times at other ages tend more toward recent years. I will talk to Barry about this as I speculate these are due to course differences.

You also can see which records are the most "impressive" and which records are "soft". The impressive records are ones where the plotted point is far below the best fit line and soft receords are ones considerably above the best fit line. The women seem to be less consistent - their points are generally farther from their best fit line than men's. One possible explanation for this is more men the race which would lead to the best men's times have been whittled down more.

A couple soft records seem to be:
Women age 65
Men age 84-86, 89
A few impressive records seem to be:
Women age 66 and 68
Men age 87, 88, 90
It also appears that there are some kind-of-soft records:
Women - around age 20. As I wrote above teens and late 20's women ran faster, maybe due to the faster women around age 20 being on college racing/training schedules?
Men - mid-30's, because men aged 38-41 ran faster with no reason to think that extra speed comes with the 38th birthday.


This 2nd graph works the same as the first except I cut off men at age 83. I did this because it's difficult to see the meat part of the graph due to the high ages causing the Y-axis to go so high. I arbitrarily picked age 83 because 84 is where the earliest occurance of the men's record being slower than the slowest women's record (which is women age 77) exists. If the graph has to go up to the women age 77, we might as well include all of the men's time up to that point.

Also on the 2nd graph the men's best fit line is not exactly the same as the 1st graph. This is because the men's age 84+ times are exllucded from the calculation. It's close but not the same. For handicapping purposes which I'll discuss in a post (hopefully next week) using the best-fit line on the 1st graph would be a better choice.


I further truncated the 2nd graph to develop the 3rd, in the same way I truncated the 1st to get the 2nd. Again, the best-fit line will not exactly match the above graphs because it considers only that graph's data. This graph shows the ages where the most competitive times are posted. I used ages 16 and 55 endpoints arbitrarily because that's where it appears the times start and stop being "real fast".

Race 11-17 Hamilton YMCA TCRS 4.36mi.

February 20th, 2011
4.36mi. - 27:15 - 5th/113

Since the beginning of 2010 I’ve been making the effort to race in more of the monthly TCRS races which are put on by Tamalpa Runners in Marin. The cost is $3 for members and $5 for non-members and what you get is a 5k-12k course over varied terrain, usually it’s a cross country type course with at least one decent size hill in the middle. This month’s TCRS was no different. The course is a 4-ish mile loop that starts on the levee behind the Novato YMCA, runs on some dirt trails and through a neighborhood going up 2 short but steep hills before returning to the finish. I had never run this course before.

The weather today was mild and sunny and I arrived at the race quite early. I was a little sore from yesterday’s 50k but not too fatigued. I thought having done yesterday’s race might cost me a handful of places. The TCRS series has some competitive runners – I’ve never been within striking distance of the leader after the halfway mark. No one knew exactly how long the course was but for some reason we had to start a quarter mile down the levee and run toward the parking lot to make the course long enough.

I started out in about 9th place but 1st wasn’t too far ahead. Everyone was more or less running in back of the person in front of him (mostly hims with the exception of Valerie Young who was a couple places in front of me). As we got to the first hill I started picking off runners until I got to (I think) 2nd, maybe 3rd? As we crested that hill I lost a couple places but I kept running strong. Also, first place had pulled away from the pack.

We descended down into a neighborhood and ran toward a second hill. I passed 2 guys going up that hill and at least one passed me back as we were at the top. When we started the descent I was in 5th with first place being out of reach but the next 3 guys were all close. I thought I might be able to make up ground going downhill but no dice – it wasn’t happening. I ran as hard as I could to avoid getting caught by the guy in 6th and managed to hold him off. I had saved a little in the tank for the last 100 meters in case he caught me, which I used but didn’t have to.

After the race a bunch of us went to Peet’s down the road. I should be at or near the top of the TCRS standings having placed fairly well in both of the events so far this year, but I expect to miss the next one due to it being the same weekend as the National Snowshoe Championship in Wisconsin.

Race 11-06 Tennessee Valley 3.78mi.