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Analysis

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.)

Kona Pro Slots – Part 1: Reverse Engineering The Assignment Algorithm

Late in 2017 Ironman announced a new system for Kona 2019 Pro Qualifying, moving to a slot-based system almost equal to the agegroup qualifying system. One aspect of the system is “unassigned slots” for some races that will be “assigned according to the ratio of starting Pro Athletes” (as stated in the official “Ironman World Championship Profession Athlete Qualification“). The specific details of the assignment algorithm is considered private by Ironman. Based on the first races and the resulting slot assignments Russell Cox (who is focused on the agegroup side, his data can be found at http://coachcox.co.uk) and I have done our best to reverse engineer this algorithm. This post looks at the available data, potential algorithms and the conclusions that can be drawn. This “algorithm post” will be followed in the next days by one looking at alternative approaches and an “opinion post”.

Data on Races With Unassigned Pro Slots

Here’s a quick look at the Pro races with unassigned slots so far:

  • IM Arizona – 2 MPRO slots (based on 15 female and 32 male Pros starting the race) plus 1m+1f base slot
  • IM Western Australia – 1 Pro slot each (based on 10 female and 13 male Pro starters)  plus 1m+1f base slot
  • IM Mar del Plata (South American Regional Championship) – 2 MPRO slots (based on 15 female and 23 male Pro starters) plus 2m+2f base slots

In addition, Ironman has stated that they use the same algorithm for determining the slot assignment for the agegroups, so we can also cross-reference if the “suspected” algorithm also fits the agegroup slots.

Assignment Algorithms

There are a number of algorithms dealing with a similar problem to slot assignment. Typically, they come from a voting context, where a small number of indivisible “seats” (usually tens to hundreds) has to be assigned based on “votes” (usually thousands). Even though the US voting system is typically majority-based, it also has to deal with a number of “representational” issues. One example is assigning a fair number of seats in the House of Representatives (capped at 435 seats) to the States in relation to their population (total US population based on the 2010 census 308.7 million, with state populations between 37.25 Million and 0.56 Million).

This post looks in detail at the two most widely used approaches, the Hamilton and Jefferson methods using the size of the field as the basis for the slot assignment. Different approaches such as depth of field will be discussed in a follow-up post. When working off the size of the field, it seems best to apply the algorithm to the number of athletes starting the race. The number of registered athletes is often quite different from the number of athletes actually racing, especially on the Pro side. And the number of finishers isn’t finalized for some time during and after the race (especially considering DQs that might be contested for days or weeks), and DNFs often contain an element of bad mechanical luck.

Hamilton Method

The Hamilton Method, also know as Hare-Niemeyer or “Largest Remainder”, is one of the oldest systems of assigning seats. It calculates the number of votes required for a seat by dividing the total number of votes by the number of seats available and then divides the votes a party has received by this number. Another way to put this is that it multiplies the number of available seats with the fraction of votes a party has received. This calculation results in a number with an integer part and a fractional part. According to Wikipedia:

Each party is first allocated a number of seats equal to their integer. This will generally leave some seats unallocated: the parties are then ranked on the basis of the fractional remainders, and the parties with the largest remainders are each allocated one additional seat until all the seats have been allocated.

In the context of Kona slots, the Hamilton Method multiplies the number of slots with the number of starters in a group divided by the total number of starters. The algorithm is probably easier to understand with a few examples.

Hamilton Method on Unassigned Slots

The first suggested algorithm applies the Hamilton method to the number of unassigned slots. (Russ and I believe that this is the “old” method of assigning agegroup slots that was used until the summer of 2018.)

For the Pros, there are two unassigned slots. Using IM Arizona as an example, we get the following calculations:

Arizona Starters Quota
Men 32 1.36 (2* 32/47)
Women 15 0.64 (2* 15/47)
Total 47 2 slots

This means that the men get one slot (the integer part of their ratio), while the second slot would go to the females (as their fractional part of 0.64 is larger than 0.36). As both unassigned slots at IM Arizona went to the men, this is obviously not the algorithm that is used for the 2019 qualifying season.

If you look at this type of calculation, then the larger agegroup will have to be at least three times as large as the smaller one to get both slots (i.e. 75% of the whole Pro field):

HamiltonUnassigned

Obviously this is a very tough requirement, and therefore not very useful to achieve “proportional slots” for the Pros when assigning only two slots. It’s also not fair that the men will always have a smaller fraction of slots than their fraction of the Pro field. It’s a bit of speculation, but I think that Ironman also felt that the system they have been using so far for assigning agegroup slots doesn’t work well for the small number of Pro slots, and that’s why they decided to change their algorithm going into the Kona 2019 qualifying season.

Hamilton Method on All Slots

Another approach would be to apply the Hamilton method on all slots while observing “minimum” slots. Again using Arizona as an example:

Arizona Starters Quota
Men 32 2.72 (4* 32/47)
Women 15 1.28 (4* 15/47)
Total 47 4 slots

This would result in the men getting three slots: two from the integer part of their ratio, and another one because 0.72 is larger than 0.28) – the minimums are already observed in this example. In order for the larger agegroup to get three slots, they would need more than 5/3 of the smaller agegroup or at least 62.5% of the field:

HamiltonAll

While this method gives the observed slot assignment in Arizona, IM has stated that their assignment process is based on the number of unassigned slots and not all slots. It’s also tricky to extend this algorithm to include minimum slots for the bigger number of agegoups for all cases. (For the technically minded: The minimum slots plus the integer parts may already assign more slots than available.) It’s very unlikely that this is the method used by Ironman.

Jefferson Method

The Jefferson Method (also known as D’Hondt method) uses a larger number of operations to determine the slots:

The total votes cast for each party is divided, first by 1, then by 2, then 3, up to s, the total number of seats. The winning entries are the s highest numbers in the whole grid; each party is given as many seats as there are winning entries in its row.

Similar to the Hamilton Method, it can be applied to all slots or only those that are unassigned.

Jefferson Method on Unassigned Slots

Based on the unassigned slots, here’s the resulting Jefferson grid for IM Arizona:

Arizona Starters 1 2
Male 32 32 16
Female 15 15 7.5
Total 47 2 slots

There are two unassigned slots, and as the male starters divided by 2 is larger than the number of females starters, both “winning entries” are from the men and both slots would get assigned to the MPROs. This fits the slot assignment in Arizona.

In general, to get both unassigned slots the larger agegroup needs to have at least twice as many starters as the smaller one, i.e. at least two thirds or 66.7% of the whole Pro field:

JeffersonUnassigned

Jefferson Method on All Slots

As for the Hamilton Method, we can also apply Jefferson Method for all available slots while observing minimums.

Arizona Starters 1 2 3
Male 32 Auto 16 10.34
Female 15 Auto 7.5 5
Total 47 4 slots

Observing minimums is relatively straightforward in the Jefferson Method – instead of starting with the divisor 1, you start with the first divisor that is larger than the minimum. As there is one minimum slot for each, the Divisors start with 2, and again the two unassigned slots would go to the men. For Arizona, this approach would also yield the “observed” 3:1 slots, but as we know that two more WPRO starters would have changed the slots, this can’t be the actual algorithm.

In order to get both slots using this approach, the larger agegroup needs to have at least 60% of the starters:

JeffersonAll

Conclusion .. For Now

Here’s an overview of the different approaches so far:

Algorithms4Slots

Based on the text in the Pro Qualifying Rules (referencing “the ratio of starters to Unassigned Slots”) and the fact that the correct Arizona distribution is yielded by the Jefferson Method on Unassigned slots, I thought that I had identified the method used – that’s why it’s highlighted in the graph shown above. Russ provided further evidence from the age-group side that was supposedly using the same algorithm. (More on the agegroup side of things in Russell’s post on Age Group Kona Slot Allocation.) It also correctly predicts an even split of Pro slots for IM Western Australia. But we have not reached the end of the story yet …

Slot Assignment For Regional Championships

Regional Championships have a different number of slots: While they also have two unassigned slots, they offer two base slots each for the men and women. (IM Arizona has one slot each, plus two unassigned slots.) But as the Pro Qualifying Rules state that the slots are assigned based on “the ratio of starters to Unassigned Slots”), I was confident that there would be even slots in Mar del Plata. Here’s Jefferson Grid for Mar del Plata:

Mar del Plata Starters 1 2
Male 23 23 11.5
Female 15 15 7.5
Total 38 2 slots

However, the actual slot assignment was that both slots went to the men, resulting in the final numbers of four slots for the men and two for the women. So we need another twist to the algorithm.

It seems reasonable that the distribution for the unassigned slots is slightly different when there are two base slots as the resulting “uneven distribution” is 3:1 (or 75%) in case of the normal races and 4:2 (or 66.7%) for the Regional Championships. If the Jefferson Method on Unassigned Slots were used, then the fraction of slots for the larger agegroup would always be lower their fraction of starters.

Jefferson Method On All Minus 2 Slots

As the Jefferson Method has been working remarkably well for the Ironman races with just one base slot each, I was looking for slight tweaks to get the right results for Mar del Plata and some of the variations. (Apparently, one more WPRO or one less MPRO would have changed things for Mar del Plata.) This “tweaking” results in the “Jefferson All Minus 2” method:

Mar del Plata Starters 1 2 3
Male 23 Auto 11.5 7.67
Female 15 Auto 7.5 5
Total 38 4 slots (1 each minimum)

This method is equivalent to the Jefferson Method on Unassigned Slots except for the Regional Championships that offer two base slots each. (In addition, it’s the same for agegroups as there is always a minimum of one slot there.)

For the Regional Championships, there is a minimum of 60% of the field needed in order to get both unassigned slots:

JeffersonMinus

Conclusion

Going forward, the “Jefferson Method on All Minus 2 Slots” will be the algorithm I’ll be using to predict how the slot assignments will look like. New results will either send me back to the drawing board, but hopefully they will strengthen the evidence that this is indeed the algorithm Ironman currently uses.

Based on this algorithm, the “inflection points” for the slot assignments are 66.7% of the Pro starters for “regular” Ironman races with unassigned slots and 60% for the Regional Championships:

CurrentSlotAssignment

Previous Kona Results by the 2018 Participants

This post looks at the previous Kona results by the 2018 Pro field.

A few observations:

  • Ronnie Schildknecht has the longest active Kona streak and the most Kona starts in the current field, he’s been racing Kona since 2006 (12 races).
  • Cam Brown has been racing even longer – his first race was in 2000! He also has 12 starts in Kona.
  • On the female side, Linsey Corbin has the most starts. She also the most finished in the whole Pro field (10 finishes out of 11 starts).
  • With 9 finishes, Luke McKenzie and Andy Potts have the most finishes on the male side.
  • The longest active streak on the female side is by Michelle Vesterby, she has been racing the last six races in Kona.

I am going to provide a lot more details on the race and the participants in my free “Kona Rating Report” which you can already pre-order at https://gum.co/Kona2018 (donations welcome).

Male Participants

Athletes 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 # of Races Highest Finish
Bart Aernouts 11 8 9 8 12 5 of 6 8
Josh Amberger 29 1 29
Igor Amorelli 13 25 33 14 4 of 5 13
Nick Baldwin
Terenzo Bozzone 11 20 6 3 of 5 6
Cameron Brown 2 8 5 22 17 9 of 12 2
Kyle Buckingham 24 30 26 3 of 4 24
Tyler Butterfield 28 7 5 36 4 of 6 5
Denis Chevrot 23 32 2 of 3 23
Matt Chrabot 37 1 37
Will Clarke 41 1 41
Maurice Clavel
Simon Cochrane
Kevin Collington 0 of 1
Antony Costes
James Cunnama 51 4 26 5 4 of 5 4
Braden Currie 30 1 30
Alessandro Degasperi 20 20 2 20
Tim Don 15 1 of 2 15
Andreas Dreitz
Marc Duelsen 18 1 18
Jan Frodeno 3 Win Win 35 4 Win
Javier Gomez
Romain Guillaume 17 10 19 3 10
Matt Hanson 34 1 of 2 34
Ben Hoffman 55 42 15 2 27 4 9 7 of 8 2
Nick Kastelein 0 of 1
Sebastian Kienle 4 3 Win 8 2 4 6 Win
Philipp Koutny
Patrick Lange 3 Win 2 Win
Luke McKenzie 54 19 29 15 9 24 2 15 35 9 of 10 2
Brent McMahon 9 30 2 of 3 9
David McNamee 11 13 3 3 3
Callum Millward 36 1 of 2 36
Giulio Molinari 28 1 28
Patrik Nilsson 8 1 8
Timothy O’Donnell 8 5 32 3 6 19 6 of 7 3
Jens Petersen-Bach 0 of 1
Mike Phillips
David Plese 27 17 2 of 4 17
Andy Potts 7 9 21 17 7 4 4 11 7 9 4
Ivan Rana 6 17 12 9 11 5 6
Tim Reed 21 23 2 of 3 21
Matthew Russell 23 20 18 23 12 5 of 6 12
Lionel Sanders 14 29 2 3 2
Ronnie Schildknecht 15 4 18 15 19 12 15 31 8 of 12 4
Joe Skipper 13 41 2 13
Andrew Starykowicz 19 1 of 2 19
Boris Stein 20 10 7 10 4 7
Ivan Tutukin 0 of 1
Jan van Berkel 32 22 2 of 3 22
Tim Van Berkel 7 36 19 15 4 7
Frederik Van Lierde 34 14 3 Win 8 25 10 7 of 10 Win
Cyril Viennot 15 18 12 5 6 18 6 of 7 5
Thiago Vinhal 13 1 13
Michael Weiss 25 13 16 16 32 5 of 7 13
Ruedi Wild 21 16 2 16
Cameron Wurf 17 1 17

Female Participants

Athletes 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 # of Starts Highest Finish
Corinne Abraham 11 16 2 11
Teresa Adam
Jen Annett
Liz Blatchford 3 10 3 3 3
Lauren Brandon 26 1 26
Melanie Burke 26 1 26
Mirinda Carfrae 2 Win 2 3 Win Win 2 7 of 8 Win
Lucy Charles 2 1 2
Susie Cheetham 6 6 2 of 3 6
Linsey Corbin 23 5 11 12 16 8 10 12 13 13 10 of 11 5
Sarah Crowley 15 3 2 3
Tine Deckers 12 19 12 16 4 of 6 12
Gurutze Frades Larralde 33 22 2 22
Helle Frederiksen
Manon Genet
Anne Haug
Melissa Hauschildt 14 1 of 2 14
Lisa Huetthaler
Mareen Hufe 19 21 11 3 of 4 11
Heather Jackson 5 3 4 3 3
Kirsty Jahn
Meredith Kessler 26 7 26 35 4 of 6 7
Katja Konschak 36 30 31 3 30
Carrie Lester 23 10 7 3 7
Asa Lundstroem 17 11 8 17 4 8
Annabel Luxford 12 9 2 of 3 9
Rachel McBride
Jocelyn McCauley 10 1 10
Beth McKenzie 15 1 15
Emma Pallant
Sarah Piampiano 23 7 7 3 of 4 7
Lisa Roberts 20 16 2 16
Jodie Robertson 20 1 of 2 20
Daniela Ryf 2 Win Win Win 4 Win
Kaisa Sali 5 5 2 5
Laura Siddall 15 1 15
Lesley Smith
Maja Stage Nielsen 12 1 12
Sara Svensk
Sarah True
Michelle Vesterby 12 8 14 4 6 5 of 6 4

Unofficial KPR & 2018 Kona Pro Slot Allocation for August Cutoff

2018 Kona Rating Report Title ThumbHere is my calculation of the KPR at the end of August qualifying, deciding the final 10 male and 7 female slots (in addition to the July Qualifiers). My results are unofficial, the official results will be posted on the Ironman website at http://eu.ironman.com/triathlon/triathlon-rankings/points-system.aspx (but as far as I can tell will show the same data). I do not show the July qualifiers, therefore it is a bit easier to determine the August qualifiers. The ranks of athletes just outside the slots will be shown in (brackets). I will update this post with new information regarding declined slots and rolldown.

Once the field has been completed, I will work on this year’s version of the Kona Rating Report, looking at the field and each athlete’s chances for a good result. The free report will be released in time before the Kona race, you can already pre-order your copy.

Update Aug 21st: As expected, Yvonne has declined her slot and it’s been accepted by Katja Konschak. Most of the other slots have been accepted by now, the few remaining ones are expected to do so with the next day or two.

Update Aug 22nd: As Tim Don posted on his Instagram feed, he received a rolldown slot, apparently from Jonathan Shearon who is the only athlete not marked with a Q on the KPR website.

Update Aug 23rd: Matt Russell was offered a wild-card slot by Ironman which he accepted (details in his Instagram post). Matt was racing last year’s race in Kona when he was hit by cross-traffic and barely escaped with his life.

Male KPR Rankings

Rank Name Nation Points Races Last Race
1 Koutny, Philipp SUI 4925 3+1 (855/400) 2018-08-04
2 Stein, Boris GER 4880 2+2 (960/320) 2018-08-19
3 Duelsen, Marc GER 4250 3+1 (705/345) 2018-08-04
4 Viennot, Cyril FRA 4060 2+2 (1280/280) 2018-08-19
5 Molinari, Giulio ITA 3610 3+1 (720/540) 2018-08-19
6 Millward, Callum NZL 3465 2+2 (685/540) 2018-08-04
7 Cochrane, Simon NZL 3420 3+1 (720/140) 2018-07-15
8 Kastelein, Nick AUS 3340 1+2 (2455/345) 2018-07-08
9 Baldwin, Nick SEY 3305 3+1 (305/280) 2018-08-19
10 D Shearon, Jonathan USA 3290 3+1 (540/540) 2018-07-29
– Kanute, Ben USA 3200 0+2 (0/500) 2018-06-03
11 Don, Tim GBR 3160 1+2 (230/500) 2018-08-19
12 Russell, Matt USA 3145 2+2 (1280/240) 2018-08-19
(13) Jurkiewicz, Jeremy FRA 3125 3+1 (540/345) 2018-07-29
– Appleton, Sam AUS 3105 0+2 (0/920) 2018-08-04
(14) Vistica, Andrej CRO 3060 3+1 (720/100) 2018-08-15
(15) Gambles, Joe AUS 2885 1+2 (1600/500) 2018-08-19

Female KPR Rankings

Rank Name Nation Points Races Last Race
1 Blatchford, Liz AUS 5535 2+2 (2000/750) 2018-08-19
2 Abraham, Corinne GBR 5280 3+1 (1100/180) 2018-08-18
3 D Van Vlerken, Yvonne NED 5100 3+1 (960/540) 2018-08-12
4 Kessler, Meredith USA 4485 2+2 (1280/750) 2018-08-19
5 Brandon, Lauren USA 4470 2+2 (1335/750) 2018-08-19
6 Lundstroem, Asa SWE 4390 3+1 (880/240) 2018-08-18
7 McKenzie, Beth USA 4310 1+2 (2890/500) 2018-08-19
8 Konschak, Katja GER 4110 3+1 (960/100) 2018-08-05
(9) Naeth, Angela CAN 4065 3+1 (720/785) 2018-08-18
(10) Lindholm Borg, Camilla SWE 3920 3+1 (720/320) 2018-08-18
(11) Chura, Haley USA 3875 2+2 (705/920) 2018-08-05
(12) Grohmann, Katharina GER 3620 3+1 (340/345) 2018-07-29

 

Kona 2018 Pro Qualifying Before the Final August Races

This post looks at Kona Pro Qualifying before the remaining races before the August cutoff:

Date Type Race Points
12-Aug 70.3 70.3 Steelhead P-750
18-Aug IM IM Sweden – WPRO only P-2000
19-Aug 70.3 70.3 Bintan P-500
19-Aug IM IM Copenhagen – MPRO only P-2000
19-Aug 70.3 70.3 Dun Laoghaire P-500
19-Aug IM IM Mont Tremblant P-2000

(The results from 70.3 Steelhead and 70.3 Dun Laoghaire did not influence the race for the August slots.)

There are more Ironman and 70.3 races in August, but they are already part of 2019 qualifying. The August qualifiers for 2018 are determined on August 19th.

The following analysis is built on the available start lists posted by Ironman and assumes that there are not going to be any late entries. As always, you can check start lists and seedings on TriRating.com.

Women’s Qualifying

August 18th: Updated after IM Sweden, August 19th: Updated after 70.3 Bintan

There are 7 Kona points slots (not counting the athletes already qualified in July) for the female Pros in August. The following table lists the athletes currently occupying the qualifying slots:

Rank Athlete Points Races Comments
1 Corinne Abraham 5.289 3+1
(2) Yvonne Van Vlerken 5.100 3+1 expected to decline (not interested in racing Kona)
3 Asa Lundstroem 4.390 3+1
4 Beth McKenzie 4.310 1+2
5 Katja Konschak 4.110 3+1
6 Angela Naeth 4.065 3+1
7 Camilla Lindholm Borg 3.920 3+1
8 Haley Chura 3.875 2+2

The following table lists what each of the athletes will need who are on one of the start lists and who can still overtake Katharina (who was initially the athlete in the last qualifying spot with 3.620 points), even if that is probably not going to be enough for securing a slot (i.e. even if one can pass Katharina, there are likely others that leap further ahead). In brackets I have added the (result) that will be needed to be quite certain of a slot (regardless of where others may finish, “n/a” meaning that even with a win a slot is not assured). For the women, the “magic number” of points to qualify in August should be just below 4.200, anyone who can pass Katja should be safe:

Athlete Points Races Registered for Needs
Liz Blatchford 3.535 1+2 IM Mont Tremblant 8th (5th)
Asa Lundstroem 3.510 3+1 IM Sweden 4th (2nd)
Laurel Wassner 3.480 2+2 IM Mont Tremblant (DNS) 4th (3rd)
Angela Naeth 3.425 2+2 IM Sweden, IM Mont Tremblant 4th (2nd)
Corinne Abraham 3.280 2+1 IM Sweden 7th (4th)
Lauren Brandon 3.210 2+2 IM Mont Tremblant 4th (2nd)
Meredith Kessler 3.205 1+2 IM Mont Tremblant 5th (3rd)
Dede Griesbauer 2.780 2+1 IM Sweden 4th (2nd)
Kim Morrison * 2.690 2+2 IM Sweden 2nd (Win)
Jessie Donavan 2.395 3+1 IM Mont Tremblant (DNS) Win (Win)
Sonja Tajsich 1.800 2+1 IM Sweden Win (n/a)

* Similar to Yvonne Van Vlerken, Kim Morrison has indicated that she would decline a Kona slot.

Update August 10th: With Sara no longer in the mix for an August slot, the cutoff will probably occur somewhere between Katja and Camilla, likely around 4.000 points. This slightly reduces the needed finishes, in most scenarios athletes should qualify by finishing one rank further down than listed above.

There are a lot more athletes registered for the remaining August races, you can check start lists and seedings on TriRating.com.

Men’s Qualifying

August 19th: Updated after IM Copenhagen

There are 10 Kona points slots (not counting the athletes qualified in July) for the male Pros in August. The following table lists the male Pros in the direct qualifying ranks:

Rank Athlete Points Races Comments
1 Philipp Koutny 4.925 3+1
2 Boris Stein 4.880 2+2
3 Marc Duelsen 4.250 3+1
4 Cyril Vienot 4.060 2+2
5 Giulio Molinari 3.610 3+1
6 Callum Millward 3.465 2+2
7 Simon Cochrane 3.420 3+1
8 Nick Kastelein 3.340 1+2
9 Nick Baldwin 3.305 3+1
10 Jonathan Shearon 3.290 3+1
– Ben Kanute 3.200 0+2 not validated, no known IM plans
11 Tim Don 3.160 1+2 registered for IM Copenhagen (should be safe with a 7th)
12 Jeremy Jurkiewicz 3.125 3+1
– Sam Appleton 3.105 0+2 not validated, no known IM plans

Boris Stein still needs an Ironman finish to be eligible for a slot. He is registered for IM Copenhagen and “just finishing” will secure a points slot for him. With Ben Kanute and Sam Appleton not being eligible for Kona (no Ironman finish), this means that currently Nick Baldwin occupies the last direct qualifying slot, but it’s safe to assume that a number of athletes are going to score and that more than 3.100 points will be needed.

The next table lists what each of the athletes will need who are on one of the start lists and who can still get to at least 3.105 points, even if that is probably not going to be enough for securing a slot (i.e. even if one can pass that mark, there are likely others that leap further ahead). In brackets I have added the (result) that will be needed to be quite certain of a slot (regardless of where others may finish, “n/a” meaning that even with a win a slot is not assured). For the men I consider 3.500 to be the “magic number” for an August slot, anyone who can pass Callum should be safe:

Athlete Points Races Registered for Needs
Andrej Vistica * 3.060 3+1 IM Copenhagen 4th (3rd)
Joe Gambles 2.885 1+2 IM Mont Tremblant 8th (5th)
Mark Bowstead 2.830 3+1 70.3 Indonesia 2nd (n/a)
Giulio Molinari 2.670 3+1 IM Copenhagen 4th (3rd)
Jesper Svensson 2.620 1+2 IM Copenhagen 6th (4th)
Patrick McKeon 2.595 2+1 IM Mont Tremblant (DNS) 6th (4th)
Jeff Symonds 2.320 2+0 IM Mont Tremblant 4th (3rd)
Sam Long 2.305 3+1 IM Mont Tremblant 3rd (2nd)
Matthew Russell 2.080 2+2 IM Mont Tremblant 3rd (2nd)
Cyril Viennot 2.060 1+2 IM Copenhagen 3rd (2nd)
Johann Ackermann 1.905 2+2 IM Copenhagen 2nd (Win)
Stefan Schmid 1.680 2+0 IM Copenhagen 2nd (Win)
Daniil Sapunov 1.465 2+2 IM Copenhagen Win (n/a)

* Andrej Vistica has announced that he will skip IM Copenhagen and is therefore out of the qualifying game.

As for the women, there are a lot more athletes registered for the remaining August races, you can check start lists and seedings on TriRating.com.

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