Which Ironman event gives me the
best chance of qualifying for
Is this a
question that you have asked yourself? More than likely you have if you have
The first objective, and really the key to the whole exercise, is to neutralise the differences between the races. There have been studies done to achieve this by comparing the performance of the Kona participants at Kona versus their qualifying races in order to quantify the relative difficulties of the qualifying events. I think this approach certainly has its merits, but also has some pitfalls.
1. The condition of the athletes in the two races. Did they peak better for Kona than they did for their qualifying race?
2. The time
difference between the qualifying event and Kona.
3. The differences in the courses. Qualifiers from courses with large bike elevations are typically less suited to Kona. Will a comparison of their respective performances lead to a conclusion that they qualified from a weaker event?
I intend to perform that analysis at a later date as a secondary validation; however my initial approach at determining the relative strengths of the race is via another route. I have taken the times of the top 5 finishers in each race (including age groupers that came in the top 5) and calculated the average of that time. This time I am calling the Elite Reference Time [ERT].† Why the top 5 finishers? Well just looking at the winning time would subject the ERT to large fluctuations based on the quality of the winner. Taking an average over more athletes statistically yields a more stable result. So why not the first 10 or 20 finishers? Well at some point if we go too deep then the strength in depth of the Male Pro field will end up being judged rather than the race itself. Somewhere between these numbers there lies a compromise and I have chosen five as the number. A future opportunity for study would be to see how the analysis changes based on that choice.
Another important point to make about the ERT is that it is specific to each race and not each event. What I mean here is that Ironman UK is the event and Ironman UK 2006 is the race. Because of a bike course change the ERT varied significantly between IMUK 2005 and IMUK 2006.
I have analysed all the course data available to me going back as far as 2002. I have had to make one or two judgement calls along the way and Iíll explain them here so that you understand what has been included and omitted.
1. Shortened races (NZ 2006, Malaysia 2005, Korea 2006 etc) have not been included
2. For events
with a complete change of venue and management like Ironman
reference times of
then have is the reference table Table 1. (right) which shows the ERTs for
each race for each year. I have calculated an average ERT for the event but
for the reasons stated earlier, please treat this average with extreme
caution. Also note that I have assigned the races by the qualification
season. So the
Now there is a huge assumption here that most of you will have noticed already. We are assuming that the strength of the menís field is the same in each race. Obviously the strength of the menís field will vary with the following factors.
1. Prize Money
2. Pro Slots Available
3. Travel And Expense to get to the location. Note now the value of my Grand Prix table to determine in which geographical areas the strength of the field lies.
in the calendar to
5. Course type. There are ďgrimpeursĒ and ďrouleursĒ and most of the really top pros are not climbers since only 3-4 courses really provide a significant elevation to be considered. So these could be argued as specialist courses. Iím not for a moment saying that Herve Faure, Marcel Zamora, Gilles Reboul are not top quality triathletes. They absolutely are, as Tim Deboom found out in 2005, however I would suggest that their prize was the ďmaillot a poisĒ rather than the ďmaillot jauneĒ.†
6. Course history, conditions and organisation. Will the weather conditions in the courses that were shortened and nearly postponed in recent years weaken the field?
However that being said, the data show a good level of consistency year over year for the same events and the results do bear out the levels of difficulties of each course as anecdotal reports have indicated over the years. I would therefore advance that this table serves us well in determining a valid reference time for each race for each year.
Now that we have established this the next step is simply to determine the time of the last qualifier in each age group for each race to determine the degree of difficulty for qualification.† Letís calculate this as follows. In IM France 2006 the time recorded by the last qualifier in the M40-44 age group was 10h33m42s by a M. Olivier Bianchi. This was 20.3% more time that the reference time for this event 8h46m42s.
I call this the number (20.3%) the Qualification Coefficient. Actually I take that back. Iím now going to call this the Hammond Qualification Coefficient [HQC] and since youíre all getting this for free you can jolly well call it that too. Canít you?
So all you
need to know in fact is which race gives you the highest HQC. i.e. which race allows you to run the slowest relative to
the elite reference time and still qualify for
For my age group I was then able to create the table showing the HQC for each race each year (Table 2)
I am desperately trying to figure out how to publish my database in an interactive format so that you simply have to click your AG to get Table 2 for your own AG. However Iím still struggling with the technology for the moment. In the interim, please click on the following link to get the HRQ Table for your own AG
THE ROLL DOWN FACTOR
Although I think the pure analysis does not really require it, I will address the roll down factor as the question is frequently asked.
everyone who earns a qualification slot actually wants to go to
Here are some interesting facts about the rolls downs.
1. Globally the acceptance rate of earned Hawaii Slots has changed as follows over recent years
a. 2003 56%
b. 2004 63%
c. 2005 68%
d. 2006 66%
So please note that whilst
Now that we have the mechanism in place, please realise that this is just a tool and apply some common sense in using it. Also remember to apply the other factors that will weigh into the equation.
all I would treat this like I would if I were evaluating an investment.
Remember that phrase ďpast performance is no guarantee of future resultsĒ.
Well that is indeed true, but for some investments it is truer that others.
This is no different. The key word is volatility. If this chart is going to
play a large roll in my quest for Kona, then Iím going to study the history
very closely. So whilst top of the pile with the highest HQC is
same vein another question is ďhow long has the race been in going on?Ē
a large number of slots available is a good thing, but not for the obvious
reason. The reason that it is a good thing is that it will provide more
consistency in the roll down factor and therefore allow a more solid
projection of the next yearís required qualifying time. With 2 slots available
Mathematically a good way to look at the volatility is to measure the Standard Deviation of the data, the lower the Standard deviation, the greater chance that future results will indeed reflect past performance. As an added tool the Table 3 shows the three factors to consider along with the HQC to validate your choice, the inauguration year, the Total slots available and the Std Deviation (for the M40-44Age group only)
My advice to your overall approach would be as follows.
1. Determine the order of events by HQC for your Age Group
2. Eliminate the events that fail to meet the required your required statistical certainly standards
3. Eliminate the events that do not meet your other constraints in terms of course type, calendar placement, cost, travel and registration availability.
4. From what is left, the event with the highest HQC should be your choice.
2007 season I selected
sincerely hope that this helps you make your best choice in your personal journey
to Kona. Good Luck and Hope to see you some day on the
I am actively working on the following items to enhance this analysis
1. Obtain more historical data from 2002-2004
2. Include data from 70.3 Events with Hawaii Qualifying slots
3. Conduct Kona performance versus qualifying race performances to validate Elite Reference Times
4. Add HQC tables for guaranteed qualification place. (i.e. if there were 5 slots available, what was the HQC for the time of the 5th place person)
5. Add complete analysis for 70.3 Florida World Championship qualification
Any comments† corrections and critique of this analysis will be warmly received and considered for improvement. Please send to neil@neilhammond,com