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IM Mar del Plata

Cancelled Pro Race at IM Mar del Plata

IMMarDelPlataA few days ago, I was trying to update the entry list for the “IRONMAN South American Championship, Mar Del Plata”. The race was scheduled for December 1st and – as a Regional Championship – was offering a total of six Pro slots for Kona 2020. However, I was no longer able to find mentions of a Pro race in Mar del Plata. Here’s what I was able to find out so far:

  • Mar del Plata is no longer a Pro race
    It is no longer mentioned in the Pro Qualifying Event Schedule. Pros who were registered for Mar del Plata have been notified, and a lot have already changed their schedule to race Cozumel (one week earlier, e.g. Matt Hanson or Andy Raelert) or Western Australia (same weekend, e.g. Gurutze Frades).
  • Agegroup race is still going ahead
    On the website for the race it is still billed as the “Ironman South American Championship” with an increased number of agegroup Kona slots  and that “after the evaluation made by the WTC  and given the great acceptance that the last edition had among the triathletes of the whole world, the IRONMAN of Argentina was positioned as one of the best distance races” worldwide. (Apparently, you can still register for the race.)
  • Cozumel replaces Mar del Plata as a Pro Regional Championship
    Ironman Cozumel (planned for November 24th) is now billed as the “IRONMAN Latin American Championship”. The prize money for Cozumel has been increased from US$ 80,000 to US$ 100,000, the amount originally designated for Mar del Plata. The net effect is an overall reduction of prize money from these two races of US$ 80,000.
  • Kona slots reassigned to Cozumel and Western Australia
    Four of the six Kona slots from Mar del Plata have been assigned to Cozumel. Cozumel now offers three male and three female Pro Kona slots (no “unassigned” or “floating slots”). This creates the weird situation that Cozumel has the same number of slots as Hawaii, but that the slots in Hawaii won’t rolldown beyond the podium.
    Another two slots have been assigned to Western Australia (planned for December 1st, the same date as IM Mar del Plata), there are now two male and two female Pro slots available (again no “unassigned slots”). There are no “lost” Kona Pro slots.

I have no information on why the Pro race in Mar del Plata was canceled, but as the age group race is still going ahead, it does not seem to be organizational issues (The “additional burden” of a Pro race seems manageable.) Is it financial issues? Then that would not bode well for the future of the Mar del Plata race. Or is there an important part of the story that is still hidden for now? I will update this post as soon as more details get known.

Ironman Mar del Plata 2019 (Dec 1st) – Entry List

Kona Slots and Prize Money

IM Mar del Plata has 2m+2f +2u Pro Kona slots. It has a total prize purse of 100.000 US$, paying 10 deep.

Male Race Participants

Name Nation
Igor Amorelli BRA
Kyle Buckingham ZAF
Tyler Butterfield BMU
Nicholas Chase USA
Andres Chirinos PER
Antony Costes FRA
Felipe De Oliveira Manente BRA
Zsombor Deak ROM
Matt Hanson USA
Jeremy Jurkiewicz FRA
Markus Liebelt GER
Sebastian Mahr GER
Urs Mueller SUI
Jesper Nybo Riis DEN
Seppe Odeyn BEL
Luis Henrique Ohde BRA
Andreas Raelert GER
Gustavo Rodriguez Iglesias ESP
Evert Scheltinga NED
Paul Schuster GER
Nacho Villarruel ESP
Thiago Vinhal BRA

Female Race Participants

Name Nation
Barbara Buenahora ARG
Gurutze Frades Larralde ESP
Mareen Hufe GER
Angela Naeth CAN

Kona Pro Slots – Part 2: Different Approaches

The current algorithm applied by Ironman to allocate Pro slots between and women (see my previous post “Kona Pro Slots – Part 1: Reverse Engineering The Assignment Algorithm“) is working based on the size of the field. This post describes two different approaches: Strength of the Field and Performance. I’ll discuss the Pros and Cons of these approaches in my next post.

Strength of Field

Measuring Strength of the Field

Measuring the quality of a field isn’t straightforward: I have tried a number of approaches that either didn’t work or were too complicated before settling on a relatively simple “points” system when showing in my seedings how good a field is. (The details can be found in my March 2017 “Strength of Field” post.) The base approach is to look at which starters have been racing Kona in the two previous years. As we’re looking for a system to determine how many athletes in each category to qualify for Kona, this seems to be a reasonable approach for assigning slots.

Basically, the points system determines how many “Kona athletes” are in the current race. Here’s how the system works:

  • 1 point for each athlete that has raced the previous Kona race (so for the current 2019 qualifying season athletes that have raced Kona 2018),
  • 0.5 points for each athlete that hasn’t raced the previous Kona race but the year before (athletes that haven’t raced Kona 2018 but Kona 2017),
  • 1 bonus point for each athlete that has won Kona in the past,
  • 0.5 bonus points for each athlete that has finished on the podium in Kona before

If you apply these numbers to the male and female fields, you get two numbers that you can then use as the base for the Jefferson Method as determined in the previous post. Please note that this system still favors the male athletes (as the male Pro field in Kona has been larger and there are therefore more male Kona Pros that can contribute points).

Example 1: IM Arizona

First, let’s have a look at the female field in Arizona:

  • Kona 2018 athletes: Annett, Jackson, Kessler, Lester, Robertson, Smith (6 points)
  • No Kona 2017 athletes that haven’t also raced in 2018 (no points)
  • No previous Kona winners (no points)
  • Kona podium: Jackson (0.5 bonus points)

This means the female fields “scores” 6.5 points. Next up, the men’s field:

  • Kona 2018 athletes: Dreitz, Plese, Skipper (3 points)
  • Kona 2017: Llanos (0.5 points)
  • No previous Kona winners (no points)
  • Kona podium: Llanos (0.5 bonus points)

The men’s field has a strength of 4 points. Running these number through the Jefferson Method (for unassigned slots), we get the following grid:

Arizona Strength 1 2
Male 4 4 2
Female 6.5 6.5 3.25
Total   2 slots

The result would have been an even split of slots.

Example 2: IM Mar del Plata

Here’s the strength of the female Pro field in Mar del Plata:

  • Kona 2018 athletes: Carfrae, Cheetham, Crowley, Lundstroem, Piampiano (5 points)
  • No Kona 2017 athletes that haven’t also raced in 2018 (no points)
  • Previous Kona winner: Carfrae (1 bonus point)
  • Kona podium: Carfrae, Crowley (1 bonus point)

This means the female fields “scores” 7 points. The men’s field:

  • Kona 2018 athletes: Chrabot, Hanson, O’Donnell, Potts, Weiss (5 points)
  • No additional Kona 2017 athletes (no points)
  • No previous Kona winners (no points)
  • Kona podium: O’Donnell (0.5 bonus points)

The men’s field has a strength of 5.5 points. Here’s the resulting grid for these numbers, taking into account the extra slots:

Mar del Plata Strength 1 2 3
Male 5.5 Auto 2.75 1.5
Female 7 Auto 3.5 2.33
Total   4 slots (1 each minimum)

Once again, we’d get even slots.

Performance

On the “If We Were Riding” podcast, Kelly O’Mara suggested to not “fix” the number of slot assignment before the race but to use the performance on race day. While her full blown version of “qualifying standards” is much more complicated and probably not workable given the differences between courses and conditions on race day, here is a suggestion on how to compare the performances between the male and female Pros in a given race.

Comparing Finishing Times

When looking at the best finishing times between the men and women, a conversion factor can be calculated. As a start, the average Top 10 finishing time of the male Pros in Kona this year was 8:04:02, the average Top 10 time for the females was 8:48:05. Dividing the female average by the male average, we get a factor of 91.66% that can be used to convert the female times into male equivalents and thus compare their performance. (Obviously, this factor will need to take more races into account if this approach is going to be used, but it seems to reasonable to calculate a factor after each Kona race and then use it for the remainder of the qualifying season.)

Example 1: IM Arizona

When applying the conversion factor to the female times, we get the following order of performances:

  1. 7:55:59 Heather Jackson (8:39:18 * 91.66%)
  2. 8:00:29 Carrie Lester
  3. 8:04:24 Eneko Llanos (no change to his finish time)
  4. 8:07:09 Jen Annett
  5. 8:08:41 Clemente Alonso

As we have four slots available, three would go to the women (Heather, Carrie and Jen) and only one to the men. (This would also “observe” the minimum of one slot for each gender.)

Example 2: IM Western Australia

For Western Australia we get the following performance order:

  1. 7:56:00 Terenzo Bozzone
  2. 7:57:40 Cameron Wurf
  3. 8:05:34 Caroline Steffen
  4. 8:07:18 Matt Burton
  5. 8:09:43 Luke McKenzie

IM WA also has four slots, in this case they would be assigned to three men and one woman.

Example 3: IM Mar del Plata

The conversion for Mar del Plata gives the following ranking:

  1. 7:30:23 Michael Weiss (already qualified)
  2. 7:38:33 Sarah Crowley
  3. 7:39:47 Matt Hanson
  4. 7:41:39 Susie Cheetham
  5. 7:42:22 Mario de Elias
  6. 7:46:30 Minna Koistinen
  7. 7:46:39 Jesper Svensson (already qualified)
  8. 7:48:09 Lukas Kraemer

With six available slots, we’d have an even split with three male and three female slots. (In addition, Mirinda Carfrae validates her Kona Winner slot.)

Ironman Mar del Plata 2018 (South American Championships) – Analyzing Results

IMMarDelPlataCourse Conditions

The swim at IM Mar del Plata was shortened to 1.9k (or 1.2 miles, possibly even a bit shorter) due to low temperatures. Obviously, this makes this years results ineligible for course records and comparing the results a bit tricky. Even though the fastest athletes were quicker than last year’s athletes (and new course records would have been set), it seems that the bike and the run were a bit slower than last year.

Male Race Results

Rank Name Nation Swim Bike Run Time Prize Money
1 Michael Weiss AUT 00:22:24 04:14:19 02:49:11 07:30:23 US$ 20,000
2 Matt Hanson USA 00:22:18 04:28:46 02:45:07 07:39:47 US$ 10,000
3 Mario De Elias ARG 00:22:15 04:28:45 02:47:24 07:42:22 US$ 6,500
4 Jesper Svensson SWE 00:19:09 04:32:04 02:51:49 07:46:39 US$ 4,000
5 Lukas Kraemer GER 00:22:02 04:30:20 02:51:42 07:48:09 US$ 3,000
6 Stefan Schumacher GER 00:26:05 04:17:12 02:58:37 07:48:40 US$ 2,000
7 Andrej Vistica CRO 00:22:28 04:38:05 02:50:42 07:55:53 US$ 1,500
8 Pedro Jose Andujar ESP 00:22:26 04:28:37 03:05:49 08:01:12 US$ 1,250
9 Felipe De Oliveira Manente BRA 00:22:16 04:47:14 02:52:46 08:08:17 US$ 1,000
10 Matt Chrabot USA 00:19:05 04:34:24 03:15:23 08:13:02 US$ 750
11 Felipe Van de Wyngard CHI 00:19:18 04:36:34 03:16:33 08:16:47  
12 Andy Potts USA 00:19:21 04:30:10 03:27:27 08:21:11  
13 Ivan Risti ITA 00:19:42 04:57:01 03:02:01 08:22:31  
14 Diego Vasquez ECU 00:22:40 04:48:01 03:09:32 08:25:35  
15 Marcus Hultgren SWE 00:23:35 04:56:00 03:07:45 08:32:37  
16 Andres Chirinos PER 00:23:29 04:56:53 03:14:02 08:39:25  
17 Nacho Villarruel ESP 00:22:30 05:14:27 03:12:34 08:56:59  
18 Giovanny Marmol Ruiz ECU 00:23:19 05:21:52 03:14:20 09:04:20  
19 Andres Darricau ARG 00:22:12 05:11:51 03:38:08 09:16:53  
  Dylan McNeice NZL 00:19:18 04:48:39   DNF  
  Christian Carletto ARG 00:22:21 09:58:55   DNF  
  Timothy O’Donnell USA 00:19:14     DNF  
  Frank Silvestrin BRA 00:20:51     DNF  

Female Race Results

Kona QualifyingWith 23 men and 15 women starting the race, I initially thought that there would be even Kona slots. But apparently the two “base slots” each for the men and women played a role, and Ironman announced that there would be four slots for the men and two for the women.For the men, Michael Weiss and Jesper Svensson had secured Kona slots in earlier races, and the slots rolled down to sixth place. Matt Hanson, Mario de Elias, Lukas Kraemer and Stefan Schumacher received the four slots. The two female slots went to Sarah Crowley and Susie Cheetham, while Mirinda Carfrae validated her Kona Champion slot.

Rank Name Nation Swim Bike Run Time Prize Money
1 Sarah Crowley AUS 00:22:23 04:51:10 03:01:54 08:20:17 US$ 20,000
2 Susie Cheetham GBR 00:23:18 04:56:01 03:00:02 08:23:40 US$ 10,000
3 Minna Koistinen FIN 00:25:06 04:53:25 03:06:04 08:28:57 US$ 6,500
4 Sarah Piampiano USA 00:25:29 05:00:53 03:00:48 08:32:18 US$ 4,000
5 Asa Lundstroem SWE 00:24:59 04:56:43 03:07:06 08:32:59 US$ 3,000
6 Mirinda Carfrae AUS 00:23:02 04:59:22 03:11:37 08:39:31 US$ 2,000
7 Dede Griesbauer USA 00:22:08 04:55:40 03:33:46 08:56:52 US$ 1,500
8 Bruna Mahn BRA 00:24:07 05:18:48 03:10:04 08:57:26 US$ 1,250
9 Ashley Paulson USA 00:29:03 05:26:00 03:00:16 09:00:22 US$ 1,000
10 Caroline Livesey GBR 00:24:20 05:13:57 03:41:52 09:25:33 US$ 750
11 Barbara Buenahora ARG 00:27:52 05:32:36 03:20:19 09:28:19  
12 Jennie Hansen USA 00:28:15 05:23:25 03:40:46 09:39:37  
13 Erika Simon ARG 00:27:55 05:46:33 03:53:49 10:15:48  
  Kimberley Morrison GBR 00:23:12 04:54:53   DNF  
  Pamela Tastets CHI 00:23:13 05:22:54   DNF  

Kona Qualifying

With 23 men and 15 women starting the race, I initially thought that there would be even Kona slots. But apparently the two “base slots” each for the men and women played a role, and Ironman announced that there would be four slots for the men and two for the women.

For the men, Michael Weiss and Jesper Svensson had secured Kona slots in earlier races, and the slots rolled down to sixth place. Matt Hanson, Mario de Elias, Lukas Kraemer and Stefan Schumacher received the four slots. The two female slots went to Sarah Crowley and Susie Cheetham, while Mirinda Carfrae validated her Kona Champion slot.

Ironman Mar del Plata 2018 (Dec 2nd) – Seedings

IMMarDelPlataPrevious Winners

Year Male Winner Time Female Winner Time
2017 Matt Chrabot (USA) 08:19:57 Sarah Piampiano (USA) 09:11:03

Last Race’s TOP 3

Here’s a link to the full analysis of last year’s results.

Male Race Results

Rank Name Nation Swim Bike Run Time
1 Matt Chrabot USA 00:48:58 04:30:46 02:55:46 08:19:57
2 Jozsef Major HUN 00:59:43 04:29:20 02:51:48 08:26:03
3 Igor Amorelli BRA 00:48:54 04:27:16 03:06:42 08:27:11

Female Race Results

Rank Name Nation Swim Bike Run Time
1 Sarah Piampiano USA 01:03:12 04:52:19 03:10:57 09:11:03
2 Tine Deckers BEL 00:59:14 04:55:51 03:19:56 09:19:22
3 Magali Tisseyre CAN 00:56:00 05:12:19 03:07:42 09:24:37

Course Records

Leg Gender Record Athlete Date
Total overall 08:19:57 Matt Chrabot 2017-12-03
Swim overall 00:48:51 Ivan Risti 2017-12-03
Bike overall 04:27:16 Igor Amorelli 2017-12-03
Run overall 02:51:48 Jozsef Major 2017-12-03
Total female 09:11:03 Sarah Piampiano 2017-12-03
Swim female 00:53:08 Dede Griesbauer 2017-12-03
Bike female 04:52:19 Sarah Piampiano 2017-12-03
Run female 03:07:42 Magali Tisseyre 2017-12-03

Course Rating

The Course Rating for IM Mar del Plata is 08:46.

Race Adjustments for IM Mar del Plata

Year Adjustment Swim Adj. Bike Adj. Run Adj. # of Finishers Rating Swim Rating Bike Rating Run Rating
2017 08:46 -00:45 11:06 03:20 24 of 25 08:46 -00:45 11:06 03:20

Kona slots and Prize Money

IM Mar del Plata has 2m+2f (+2 floating) Pro Kona slot(s). It has a total prize purse of 100.000 US$, paying 10 deep. (The floating slots will be assigned proportionally according to the number of Pros starting the race.)

Male Race Participants

The strength of the field is 22% of a typical Kona field.

# Bib Name Nat Expected Rating ESwim EBike ET2 ERun Consistency Overall
1 6 Timothy O’Donnell USA 08:07:11 08:16:26 00:48:05 04:24:36 05:17:41 02:49:30 69% +19% -12% (18) 9
2 2 Andy Potts USA 08:09:58 08:17:25 00:48:52 04:26:09 05:20:01 02:49:57 96% +4% -0% (20) 11
3 3 Michael Weiss AUT 08:12:35 08:25:08 00:55:18 04:18:37 05:18:56 02:53:39 88% +2% -10% (23) 29
4 5 Matt Hanson USA 08:14:34 08:28:12 00:53:04 04:30:30 05:28:34 02:46:00 16% +37% -47% (15) 34
5 9 Clemente Alonso McKernan ESP 08:14:43 08:30:05 00:49:31 04:30:23 05:24:55 02:49:48 40% +5% -55% (17) (44)
6 12 Jesper Svensson (KQ) SWE 08:15:25 08:31:08 00:47:43 04:26:57 05:19:40 02:55:45 66% +0% -34% (3) (50)
7 8 Andreas Raelert GER 08:17:35 08:35:21 00:49:57 04:26:03 05:21:00 02:56:35 18% +8% -74% (22) (64)
8 7 Eneko Llanos ESP 08:22:39 08:35:05 00:49:58 04:26:32 05:21:29 03:01:10 75% +0% -25% (35) 61
9 28 Lukas Kraemer GER 08:23:58 08:36:05 00:55:36 04:33:56 05:34:31 02:49:27 100% +0% -0% (3) 67
10 4 Igor Amorelli BRA 08:24:29 08:32:18 00:48:42 04:26:38 05:20:20 03:04:09 68% +8% -24% (19) 55
11 1 Matt Chrabot USA 08:24:32 08:43:49 00:49:04 04:33:04 05:27:07 02:57:25 34% +10% -57% (9) 93
12 17 Paul Matthews AUS 08:24:59 08:30:56 00:48:48 04:32:22 05:26:09 02:58:50 39% +0% -61% (16) 49
13 14 Miquel Blanchart Tinto ESP 08:27:40 08:35:13 00:50:47 04:41:45 05:37:32 02:50:08 91% +2% -7% (22) 62
14 11 Andrej Vistica CRO 08:29:36 08:37:32 00:56:00 04:35:42 05:36:41 02:52:55 93% +0% -7% (17) 77
15 21 Pedro Jose Andujar ESP 08:30:15 08:51:44 00:56:45 04:33:21 05:35:05 02:55:10 n/a (1 IM Pro race) (119)
16 22 Dylan McNeice NZL 08:30:43 08:40:46 00:47:23 04:35:17 05:27:40 03:03:03 22% +37% -40% (19) 84
17 10 Thiago Vinhal BRA 08:31:06 08:41:17 00:50:36 04:41:47 05:37:23 02:53:43 54% +25% -21% (17) 86
18 16 Ivan Risti ITA 08:36:34 09:03:35 00:49:03 04:40:36 05:34:39 03:01:55 26% +17% -57% (13) 153
19 15 Frank Silvestrin BRA 08:38:42 08:52:58 00:50:09 04:44:42 05:39:50 02:58:52 50% +48% -2% (10) 127
20 18 Mario De Elias ARG 08:40:29 08:52:49 00:54:06 04:42:28 05:41:35 02:58:54 61% +22% -17% (10) 126
21 24 Johannes Moldan GER 08:43:39 09:05:42 00:52:17 04:32:26 05:29:42 03:13:57 n/a (1 IM Pro race) (161)
22 19 Urs Mueller SUI 08:57:50 09:12:46 00:54:03 04:44:26 05:43:29 03:14:21 60% +11% -30% (10) 182
23 27 Felipe De Oliveira Manente * BRA 09:03:27 09:19:56 00:55:58 04:52:10 05:53:08 03:10:19 57% +4% -40% (10) 196
24 35 Marcus Hultgren SWE 09:12:33 09:33:30 00:58:15 04:48:10 05:51:25 03:21:08 26% +22% -52% (10) 227
25 36 Michael Louys BEL 09:14:26 09:30:43 01:05:43 04:47:27 05:58:10 03:16:16 45% +4% -51% (15) 221
26 34 Andres Darricau ARG 09:15:16 09:27:22 00:55:51 04:59:11 06:00:02 03:15:14 7% +93% -0% (2) (217)
27 29 Christian Carletto ARG 09:18:59 09:47:35 00:55:09 04:57:13 05:57:22 03:21:37 64% +36% -0% (11) 242
28 26 Diego Vasquez ECU 09:26:17 09:51:36 00:56:13 04:55:38 05:56:51 03:29:26 100% +0% -0% (2) (244)
29 32 Gaston Duran ARG 10:01:23 10:32:58 01:00:48 05:19:03 06:24:51 03:36:32 4% +0% -96% (2) (262)
20 Felipe Van de Wyngard CHI n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)
23 Iuri Josino Vinuto BRA n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)
25 Giovanny Marmol Ruiz ECU n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)
30 Andres Chirinos PER n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)
31 Stefan Schumacher GER n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)
33 Nacho Villarruel ESP n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)

Note: Athletes with a ‘*’ are also registered for another race within 8 days.

Female Race Participants

The strength of the field is 26% of a typical Kona field.

# Bib Name Nat Expected Rating ESwim EBike ET2 ERun Consistency Overall
1 42 Mirinda Carfrae (KQ) AUS 08:54:11 09:03:31 00:58:39 04:54:08 05:57:46 02:56:25 81% +6% -14% (17) 3
2 43 Sarah Crowley AUS 08:58:19 09:10:05 00:55:12 04:52:38 05:52:51 03:05:28 40% +60% -0% (8) 6
3 48 Susie Cheetham GBR 09:07:55 09:15:48 00:57:03 04:58:14 06:00:17 03:07:38 75% +0% -25% (11) 12
4 41 Sarah Piampiano USA 09:10:23 09:20:06 01:03:51 04:57:11 06:06:01 03:04:22 85% +5% -10% (24) 17
5 46 Angela Naeth CAN 09:10:43 09:29:37 00:59:56 04:49:49 05:54:45 03:15:58 19% +56% -26% (11) 36
6 45 Asa Lundstroem SWE 09:16:06 09:24:43 01:03:03 04:56:12 06:04:15 03:11:51 85% +15% -0% (21) 29
7 47 Kimberley Morrison GBR 09:18:01 09:31:28 00:55:33 04:49:39 05:50:12 03:27:49 100% +0% -0% (3) 39
8 44 Dede Griesbauer USA 09:29:34 09:51:47 00:53:51 04:56:14 05:55:06 03:34:28 45% +8% -47% (30) 71
9 50 Bruna Mahn BRA 09:31:38 09:53:40 00:58:58 05:13:35 06:17:33 03:14:05 48% +52% -0% (6) 74
10 51 Pamela Tastets CHI 09:39:58 09:53:22 00:58:52 05:12:33 06:16:25 03:23:33 100% +0% -0% (4) 73
11 49 Jennie Hansen USA 09:40:27 09:46:16 01:05:32 05:11:51 06:22:22 03:18:05 77% +0% -23% (14) 57
12 55 Caroline Livesey GBR 09:42:49 10:08:18 01:01:15 05:10:15 06:16:30 03:26:19 51% +14% -35% (10) (92)
13 52 Ashley Paulson USA 09:52:09 10:08:27 01:14:25 05:23:24 06:42:49 03:09:20 66% +12% -23% (10) 94
14 57 Barbara Buenahora ARG 09:57:33 10:09:21 01:02:03 05:22:31 06:29:34 03:27:59 42% +34% -25% (4) (97)
15 56 Erika Simon ARG 10:47:37 11:16:39 01:04:51 05:43:40 06:53:31 03:54:06 34% +0% -66% (2) (140)
53 Svenja Thoes GER n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)
54 Minna Koistinen FIN n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)
58 Nayara Luniere BRA n/a unrated unrated unrated unrated unrated n/a (no IM Pro race) (n/a)

Winning Odds

Male Race Participants

  • Timothy O’Donnell: 35% (2-1)
  • Michael Weiss: 20% (4-1)
  • Matt Hanson: 19% (4-1)
  • Andy Potts: 14% (6-1)
  • Clemente Alonso McKernan: 6% (17-1)
  • Andreas Raelert: 4% (24-1)

Female Race Participants

  • Mirinda Carfrae: 47% (1-1)
  • Sarah Crowley: 32% (2-1)
  • Sarah Piampiano: 10% (9-1)
  • Susie Cheetham: 4% (24-1)
  • Asa Lundstroem: 4% (24-1)
  • Angela Naeth: 3% (29-1)
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