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Analysis

SwimRatings – How did I calculate them?

My latest blog post on the development of Heather Wurtele’s swim times has generated some interest. Rather than explaining how I calculated the Swim Ratings in comments or private emails, I’ve decided to write a longer, technical blog post explaining the algorithm I’m using. Here are the steps to process new results:

  1. Calculate the race adjustment
  2. Adjust the individual times
  3. Calculate the new rating

Each of these steps is explained in more detail in the following sections. As an example, I’m using Heather’s results from IM Lake Placid 2011 in order not to overwhelm you with lots and lots of results. (Lake Placid had 24 Pros, her later races had way more.) The description also applies to my calculations for any of the legs in a triathlon or the total time, but as the question was specific to swim results, I’ll use the swim times as an example.

Calculate the race adjustment

The goal of the race adjustment is to figure out if the race was slow or fast, taking things into account like how accurate the course was measured or how conducive the conditions on race day were for fast times. In order to calculate this number, let’s have a look at the actual results (Pros, both men and women) first:

Swim

The next step is adding in the existing swim rating. (Some athletes haven’t got a swim rating yet, these can’t be used for the adjustment calculation.) Then I can calculate the difference between the rating and the actual swim time and calculate the difference in percent of the rating. Here’s the data after resorting the table based on the percentage:

SwimDiffs

Only two athletes were able to beat their swim rating (compared to 16 that took longer), so you can already see that the swim was “slow”. There are a few statistical tricks to come up with a “fair” overall adjustment, such as using the average (-4,23%) or the median (-4,33%). What I’ve found works best is to use a percentage of athletes closest to the median. This way larger variations than what we have in this data set (aka. “explosions” on the run) do not play such a big role. Here I end up with a swim adjustment of -4,51%. 

Adjust the individual times

Once we have calculated the race adjustment, we can apply this adjustment to the individual times:

Adjusted

Basically we have removed all course and condition factors from the time and have arrived at a “neutral” swim time that is comparable between races held on different courses and in different years.

Calculate the new rating

Now that we have calculated an adjusted swim time for each athlete’s results, we can pull all of these individual results into a swim rating. To continue with the example, here are Heather’s swim results and adjusted swim times up to Lake Placid 2011:

HeatherSwims

(We can also see that the results Heather based her original assessment on – St. George 2010 – was by far her best swim result.)

The simplest solution is to just take the average of all the results. But then an old result has the same influence as a new result – which doesn’t help much in assessing the current capabilities of a developing athlete or an athlete way past his prime. Therefore, I’m assigning each result a weight based on how old the result is – the older the result, the lower the weight is. I’ve found a value of 0.75 per year works well at reflecting current capabilities without making the ratings change too much. For Heather’s results, the difference between an average and my method is small (54:21 vs. 54:22) but there are examples where the difference is meaningful.

Summary

I hope that I was able to explain in detail how I came up with the swim numbers that form the basis of my blog post comparing the different swim results. The calculation itself is pretty complicated and takes a lot of factors and situations into account. This has the disadvantage of making it almost impossible to calculate the numbers by hand, but so far I have not seen a better system. I accept that these numbers might not be “true” and cannot reflect the assessment of an athlete by a trainer who sees the athlete much more often than the few times per year an athlete can race in an Ironman. But a race is where “the rubber meets the road” and where an athlete has to show what all the hard training has been worth. The numbers just indicate whether there was an improvement or not and cannot judge the reasons behind it. Also, I can’t assess the future improvements of an athlete or the quality of a training program. I certainly wish Heather some improvements in her swim time (and overall results), and I’m sure she is busy planning with Paulo on how to improve.

Kona 2012 – Swim Time Analysis for Heather Wurtele

On her blog, Heather Wurtele wrote that she was frustrated about her swim time in Kona:

In 2010 I swam a 51 min IM swim in St. George, beating Meredith Kessler out of the water. I also used to be in front of Caitlin Snow out of the water, pretty much guaranteed  These two ladies now soundly kick my ass. … Their improvement highlights my stagnation.

Here’s the data that Heather’s statement is based on:

SwimTimesShort

(I put Meredith’s Hawaii time in brackets as she didn’t finish this year after a bike crash.)

Heather’s coach, Paulo Souza, replied with an analysis of the Kona swim times:

  • Your time difference to the best time has decreased both in 2011 and 2012
  • Your time difference to the most consistent performer in the years you raced Kona (Rachel Joyce) has decreased in 2011 and 2012.
  • Your time difference to the best athlete in that list (Mirinda) has also decreased from last year to this year.

He comes to the following conclusion:

I think the data shows your clear progression in the last couple years.

As I have started to analyze swim/bike/run times (in addition to the total finishing times), this discussion inspired me do have a closer look at the data. First, here’s a look at the swim times where Heather was racing with one of the ladies mentioned:

SwimTimesLong

(The table is just a comparison with Heather’s results; of course, the other athletes have more results than these.)

From this table, it looks that the only time Heather was swimming faster than Meredith and Caitlin was St. George 2010, and she was “soundly kicked in the ass” (her words) in this year’s Kona. But what should be considered “normal” .. was St. George the exception or Kona 2012? Another question is what influence the different courses have. Obviously the differences in the swim time largely stem from the fact that Kona (as an ocean swim with swell and currents) is slower that the lake swims in St.George, Canada or Arizona. Also, how accurately a course is measured is also an influence.

I’m trying to account for all of these factors by calculating an adjusted swim time (similar to the adjusted total time I use for my ratings). The adjusted swim times of an athlete can then be averaged to a swim rating. Here is a look how the swim ratings of Heather and the others ladies has developed over the years:

SwimRating

A couple of observations from this graph:

  • The red line is mainly horizontal, which means that Heather’s swim rating hasn’t changed much between 2008 and 2012.
  • Meredith’s swim rating (green line) has steadily improved from 2010 to 2012, she is about three minutes quicker than Heather (and Caitlin) now
  • Caitlin (purple line) has also improved, she used to be two minutes slower than Heather and has improved to be faster by a few seconds. (But nowhere close to “soundly kicking my ass”, at least not in Ironman races.)
  • Rinnie (blue line) made a big step (almost two minutes) after her first Ironman, she has been pretty steady since then.
  • Rachel (orange line) is the best swimmer of these five athletes, she steadily improved until last year and is pretty steady at a sub-50-minutes rating since then.

All in all, the data agrees more with Heather’s assessment that her swim hasn’t improved, while other athletes managed to get better. Of course, the data is purely looking at the times – other factors such as how much effort was required cannot play a role here. If Paulo’s observation about her improved pool times is correct, maybe Heather can swim a bit harder without sacrificing too much bike or run time, or we can look forward to a breakthrough performance from Heather in one of her future Ironman races. For the next months,I think she correctly predicted when she wrote:

Oh my god, I am going to suffer in the water this winter!!!!!  🙂

Heather, enjoy your off-season!

HeatherSwim

(Photo from her blog.)

Changes for the Kona Pro Ranking 2013 (KPR) – Updated

Almost by accident I noticed that WTC has already posted points and rules for the 2013 KPR. After a quick scan here are the changes I noticed:

  • The number of Kona slots for female PROs has been increased by 5 (28 by July, another 7 by August). The number of male PROs stays the same (40+10 = 50).
  • St. George is no longer on the schedule as a full distance race – this has been announced for a while.
  • New York has also been cancelled – this is a relatively recent development, it was announced a few days ago (i.e. early September).
  • Canada is also no longer on the list – the old venue has become a Challenge event, and the new event hasn’t been announced yet. I’m sure WTC has a few slots saved for a Canadian race.
  • The new Ironman Canada in Whistler has been designated a 2000 points race. (The 2012 race in Penticton was just a 1000 points race.)
  • IM Regensburg is also absent. The race site has not announced a new date yet, and there is lots of speculation in the German triathlon forums if and when the race is going to be held. The race has been officially canceled for 2013.
  • One more thing that is missing for now: A North American Championship race (i.e. a 4.000 points race with a similar status to Melbourne and Frankfurt).
  • The race in Mont Tremblant has been designated the new North American Championship race (i.e. it is now a 4.000 points race).
  • There are also two new races: Los Cabos (March) and Lake Tahoe (September, a qualifier for 2014), both are 2.000 points races.

Kona 2012 Predictions: Running Strengths

As usual, the race will be decided on the run. Therefore, I’ve done some extended analysis on the athlete’s run performance. It will be no surprise that the athletes with the best odds (Crowie and Rinnie) are also the best runners in the field. Here is a closer look at the data on athlete’s running strengths.

Run Rating

Looking at the individual run results, I’ve come up with some rating-like assessment of athlete’s run leg during an Ironman triathlon. The following tables list the main contenders and some other athletes that might be in a good position during the race.

I’m listing three different times:

  • The average run time (across all courses)
  • The average time for a Kona run (for all Kona races, empty if no Kona race so far)
  • The Run PR (regardless of the course it was run)

Men

By all numbers, Crowie is the strongest runner in the field. It remains to be seen if Macca’s Olympic training has given him an extra edge – I’m sure that he believes he can beat Crowie on the run.

Name Avg Run Kona Run Run PR
Craig Alexander 02:45:37 02:44:52 02:38:46
Paul Matthews 02:47:24 02:47:24
Andreas Raelert 02:47:47 02:47:46 02:40:52
Marino Vanhoenacker 02:51:59 02:56:17 02:39:24
Eneko Llanos 02:51:44 02:54:08 02:43:46
Sebastian Kienle 02:52:19 02:50:17
Timo Bracht 02:52:52 02:57:54 02:43:33
Dirk Bockel 02:53:57 02:54:16 02:51:56
David Dellow 02:54:38 02:45:05
Michael Raelert 02:54:40 02:54:40
Faris Al-Sultan 02:57:04 02:59:19 02:50:38
Jordan Rapp 02:57:17 02:46:55
Chris McCormack 02:50:02 02:47:21 02:42:02
Cameron Brown 02:52:09 02:58:40 02:41:17
Daniel Fontana 03:01:56 03:04:04 02:58:23
Andy Potts 02:57:08 02:59:17 02:52:15
Rasmus Henning 02:58:40 03:03:21 02:39:43
Joe Gambles 03:00:36 03:12:56 02:54:02
Pete Jacobs 02:57:02 02:50:08 02:41:06
Luke McKenzie 03:10:58 03:13:10 02:51:38

Women

On the women’s side, the numbers show that Rinnie is by far the best runner in the field. There are a few athletes that have a better potential than the average numbers indicate – Caroline Steffen, Bek Keat and Leanda Cave come to mind.

Name Avg Run Kona Run Run PR
Mirinda Carfrae 02:56:25 02:54:11 02:52:09
Mary Beth Ellis 03:09:59 03:13:48 03:01:29
Caroline Steffen 03:19:49 03:10:32 03:01:22
Rachel Joyce 03:18:57 03:14:55 02:59:53
Sonja Tajsich 03:08:28 03:09:56 02:55:43
Amy Marsh 03:21:51 03:25:25 03:11:19
Rebekah Keat 03:11:54 03:18:22 02:55:28
Linsey Corbin 03:10:25 03:13:57 03:02:27
Leanda Cave 03:23:06 03:24:11 02:58:51
Kelly Williamson 03:08:59 03:07:18 03:03:33
Tine Deckers 03:21:13 03:27:52 03:02:31
Meredith Kessler 03:19:55 03:28:11 03:10:14
Anja Beranek 03:20:44 03:18:06
Michelle Vesterby 03:21:17 03:20:16
Amanda Stevens 03:29:50 03:32:47 03:23:41

Playing with Numbers: Standing before Run

If I take the predicted finish time (based on the ratings and the Kona course rating) and the run times (I’m using the lower of the average and Kona Run times), I can speculate on the standing before the run. Of course, this is just playing with the numbers and does not take real race dynamics into account, but I think some speculation is still interesting.

Men

In the last years it was Chris Lieto who was the front-runner coming off the bike. I’m sure that a lot of athletes would like to take that spot this year – but I don’t really see Marino as the one leading off the bike, even if that’s what the numbers say. The next spots show a pretty large group of athletes including Andreas Raelert, Jordan Rapp, Dirk Bockel, Faris Al-Sultan and Crowie. If Timo Bracht ends up in that group as well, he’ll have a great chance for a podium finish. Maybe the presence of Jordan Rapp will help him make that front group this year. I would also think that Sebastian Kienle will use his bike strength to bike into the front group, and he may even be the athlete off the front. Also, Chris McCormack will do his utmost to be in that front group, maybe even a few minutes ahead of Crowie. Maybe he can round up a few other athletes (as he did when winning in 2010) who help him trying to break Crowie …

# Name Before Run
1 Marino Vanhoenacker 05:26:33
2 Andreas Raelert 05:29:15
3 Paul Matthews 05:29:24
4 Jordan Rapp 05:29:58
5 Dirk Bockel 05:30:02
6 Faris Al-Sultan 05:30:04
7 Daniel Fontana 05:30:05
8 Craig Alexander 05:30:51
9 Timo Bracht 05:30:56
10 Sebastian Kienle 05:31:23
11 David Dellow 05:31:24
12 Eneko Llanos 05:31:28
13 Michael Raelert 05:32:22
14 Joe Gambles 05:33:38
Rasmus Henning 05:34:31
Luke McKenzie 05:35:17
Andy Potts 05:35:20
Cameron Brown 05:36:50
Chris McCormack 05:41:11
Pete Jacobs 05:50:44

Women

On the women’s side, my numbers predict Amy Marsh leading off the bike. The real story, however, will be how far back Rinnie is going to be (I have her 13 minutes behind and not even in the TOP10 after the bike) and how far ahead of her Caroline Steffen is going to be. If it’s really going to be 8 minutes, Rinnie has to come up with one of her best runs in order to win again in Kona. Also, one of the other girls should be able to come up with a run a bit better than her Run Rating – maybe Mary Beth (being a bit more rested this year), Rachel or Leanda. I think that the race will be decided after the Energy Lab – maybe we’ll have a female version of Mark Allen running down Thomas Hellriegel from 1995 (he was 13 minutes after the bike).

# Name Before Run
1 Amy Marsh 06:04:44
2 Mary Beth Ellis 06:06:16
3 Rachel Joyce 06:06:26
4 Leanda Cave 06:07:46
5 Caroline Steffen 06:09:33
6 Tine Deckers 06:14:05
7 Rebekah Keat 06:14:58
8 Michelle Vesterby 06:16:14
9 Anja Beranek 06:16:19
10 Meredith Kessler 06:16:49
11 Amanda Stevens 06:17:32
12 Mirinda Carfrae 06:17:50
Sonja Tajsich 06:18:06
Linsey Corbin 06:18:34
Kelly Williamson 06:25:04

Run Comparison Charts

The following tables show the projected time after T2, the Run Rating and the total finishing time. In a row, a positive number means that the athlete has to be ahead of the other athlete, a negative number that he can afford to be behind.

Men

RunMatrix Men

As the strongest runner in the field, Crowie can afford to give up more than two minutes to every athlete and still expect to win the race. (For example, he can be 8 minutes behind Timo Bracht after T2 and they would be even at the end of the race.)

This table also shows that if Macca or Pete Jacobs make it into T2 close to the front group, they have a good chance for a podium spot or even winning the race.

Women

Run Matrix Women

Again, it is amazing to see how better Rinnie’s Run Rating is compared to the rest of the field. Based on the numbers, she can give up more than 15 minutes to everyone! As noted earlier, this number may be a bit misleading. The rest of the field is much closer together, and a lot will ride on who’s having a good day in the Kona heat.

Kona Strength: Who is racing well in Kona?

My ratings are a course-independent number, so they don’t give a complete picture of how an athlete is going to do in Kona. By comparing the relative performances in Kona and on other courses, I can determine athletes who are racing well in Kona and those that struggle on Hawaii. I’m expressing this number – the “Kona Strength” – as the time difference between the expected result (based on the athlete’s rating before the race) and the actual result (finishing time adjusted for the course and conditions on race day). For example, Caroline Steffen has a Kona Strength of 24:29 – this means that here results in Kona have been more than 24 minutes faster than her rating predicted. A Kona Strength of 0 shows that an athlete is not racing faster or slower in Kona than their rating predicts, and a negative number (e.g. -31:18 by Meredith Kessler) shows that the athlete has struggled in Kona. I’ve added a number to show how many Kona results the Kona Strength is based on – one race may always be a fluke (so maybe the one result by Meredith Kessler was not caused by the Kona heat and she’s going to do much better this year).

Good Kona Results

Here is a list of athletes that have races well in Kona:

  • Caroline Steffen 24:29 (2)
  • Pete Jacobs 22:34 (4)
  • Mirinda Carfrae 21:26 (3)
  • Caitlin Snow 18:07 (4)
  • Rachel Joyce 14:15 (3)
  • Ronnie Schildknecht 10:09 (4)
  • Craig Alexander 09:05 (5)

Inferior Kona Results

The following athletes have struggled in their Kona races:

  • Meredith Kessler -31:18 (1)
  • Jan Raphael -25:35 (3)
  • Rebekah Keat -16:50 (2)
  • Linsey Corbin -12:09 (5)
  • Marino Vanhoenacker -09:34 (4)
Jan Raphael has declined his Kona slot (he qualified late in the year in Sweden), he wants to get his bad Kona results out of his mind before trying again. 

New to Kona

There are also a few athletes that haven’t yet raced in Kona. Usually, these athletes should race a bit conservatively and build some experience in the Kona conditions:

  • Jordan Rapp
  • Trevor Wurtele
  • David Dellow
  • Sebastian Kienle
  • Michael Raelert
  • Greg Bennett
  • Michelle Gailey
  • Michelle Vesterby
This post is an excerpt from my Kona Rating Report. You can receive your copy by using this link to subscribe to my email list.
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