Kona Performance Compared to Ironman Performance for Age Group Qualifiers

Another Sunday shut away in my dingy office brings me another step towards better understanding the statistics of Ironman performance and Kona qualification. A small step, an actual model relating race, conditions, gender, age and performance remains a distant goal, but for a subsection of Ironman athletes, those who qualified for Kona, I was able to relate and compare their performances at the World Championship with their other Ironman races. What does that mean? We can examine the typical differences between performance at the World Championship and performance in other Ironman races on the circuit. At the very least it gives those who qualify an idea of how their qualification performance compares with their Championship performance.

Having identified and related as many athletes as I could here is the resulting differences for the 2012 Ironman World Championship qualifying series:

Average Split Difference Between Kona and Qualifying Race for All Age Group Qualifiers

The overall differences are probably more easily followed in graphical form:

Chart of Average Split Difference Between Kona and Qualifying Race for All Age Group Qualifiers

Positive numbers represent faster time, for example the swim time of a qualifier at Ironman Wales in 2011 was on average 13:06 faster than their swim time at Kona in 2012, whereas the bike time was on average 38:38 slower. We can see that with a few exceptions qualifying athletes are typical faster outside of Kona. Not hugely surprising Hawaii is not the fastest race on the circuit and we could speculate as to how many athletes reach Hawaii in as good a condition as they did their qualifier.

As usual it’s important to be aware of the limitations of this data: results are only from the 2012 qualifying period and only include full Ironman distance events (New Zealand is excluded for this reason). The matching of athletes was a labour intensive and imperfect process – also it was tedious – requiring me to attempt to hand match over 500 individuals that failed an automated match. The result is that I matched race results for roughly 85% of the Hawaii field, for each of these athletes I have matched all other Ironman performances found, not just their qualifying performance. While considering the differences between time at Hawaii and time at other races should reduce the impact gender or age has on the data it doesn’t eliminate it – the overall chart above may hide some details.

Naturally I also produced gender specific tables of data, to examine if there was much difference between the way men and women perform at Hawaii versus the rest of the circuit:

Average Split Difference Between Kona and Qualifying Race for Male Age Group Qualifiers

Average Split Difference Between Kona and Qualifying Race for Female Age Group Qualifiers

Unsurprisingly men and women show slightly different averages although the trend towards faster or slower times for a given race remains the same. It appears men tend to see bigger gaps in run performance than women, but smaller gaps in bike performance. It’s worth noting that dividing into gender in this way reduces the pool of athletes considered for each race and should reduce our confidence when making predictions with these numbers.

In previous posts where I’ve examined the differences in performances between age groups my general conclusion has been that, at least for men, between the ages of 25 and 50 performances are reasonably comparable. While I do have data for every age group I felt it would be more relevant to examine this central band of age groups. So again we can compare the typical differences in times for all 25-50 year olds as well as men and women in that age bracket:

Average Split Difference Between Kona and Qualifying Race for 25-50 Year Old Age Group Qualifiers

Chart of Average Split Difference Between Kona and Qualifying Race for 25-50 Year Old Age Group Qualifiers

Average Split Difference Between Kona and Qualifying Race for 25-50 Year Old Male Age Group Qualifiers

Average Split Difference Between Kona and Qualifying Race for 25-50 Year Old Female Age Group Qualifiers

The affect is a tightening of the gap, often quite slight, but the narrowing of the age range has removed some outliers. Again drawing precise conclusions from one year of qualifiers won’t say too much.

What might we be happy to conclude? That a typical age group qualifier can expect to swim between 5 to 10 minutes slower, bike 10 to 30 minutes slower and run 10 to 25 minutes slower in Hawaii. That male qualifiers tend to have the slower runs in Kona while women tend to have the slower bikes. That few athletes perform faster in Hawaii – those racing at St George and Wales are the exception. And that performances from the fastest races naturally see the biggest drop off when the athletes start in Kona. Nothing startling, but interesting to see numbers for this.

These tables are the first products of the updates I’ve made to the Ironman results database, they’re the low hanging fruit, the easiest pieces of analysis to construct, although perhaps not the most informative. The biggest barrier to extending this further is the sheer volume of manual labour required to tidy and normalise the age group data, it limits the quality of the analysis in both breadth and depth. But relating athlete results does provide the potential to build a more accurate picture of comparable Ironman performances and requirements of qualification. At this point though, I wouldn’t hold your breath.

All Ironman Results and Statistics

A growing collection of results and statistics for the whole Ironman race calendar.

Find out what it takes to place in your age group or to qualify for the Ironman Worlds Championships in Kona.


  • Mike O’Brien

    Excellent post Russ. Can’t complain with being only 10 min of Austria time.

  • No doubt you can be pleased with that performance in Kona, above average based on the predictions here.


  • Daniel McParland

    Fascinating blog! I expected to be an outlier in this analysis but not by that much. I went 9 mins faster at kona than at UK, ‘beat’ the average by 34 mins! Also beat the Regensburg average by 31 mins.

    The numbes don’t lie, what you can easily deduce from this is that Kona is a pig of a difficult race.

  • It’s quite surprising that on average most athletes are a good 20-30 minutes faster away from Kona. As you say it’s a tough race (perhaps particularly so this year) and for many present challenges they won’t be used to – high heat and winds. Also wonder how much we see the impact of multiple races in a season and managing to successfully prepare for them all, for some qualifying is the main goal, once there they’re happy to be racing in Hawaii.

    You have made me think it might be interesting to look at the distribution of differences between the races and perhaps see how many people actually beat the predictions and how the odds skew.

    And I now have enough linked athletes to related performances between every race on the circuit – just going to take me a while to work out how to process that data into something neatly presentable.


  • John Towse

    Great work, Russ! Thanks for taking the time to do this and publish it.

    Just a brief comment: You’ve ordered the events by date -I think- and that shows some nice trends too.
    Starting with South Africa in April, it seems that relative Kona times are falling off during the year (ie your blue bars are getting longer). Athletes are struggling to peak again at the end of the season, especially when they qualify in August for example (2 months to recover and prep, etc). Not that surprising either, but it looks quite clear. If you haver to go all-in to get a qualifier slot, it’s going to be hard to repeat your performance

    Dan McP (above) is an exception, but as his clubmates will attest, we’ve always thought he’s a bit different 🙂
    St George is a outlier to the trend too, but as someone who was there, it was a freak day .

  • Hi John,

    I’d not spotted that, but yes some of the later races do have much faster qualifying times compared to Kona performances. I’d want to look at a few more years before I drew any strict conclusions, but it is interesting to speculate that you might be seeing the impact of two close ironman performances where the first has been a push. Of course there is the influence of race course in there and the challenge is removing that factor – Sweden for example is a fast course and a huge outlier.

    I have now done some analysis comparing race performances of all athletes between races in 2012. The results are best described as curious – I’ve reduced them to lists of races in order of speed – many fall where we might expect, but there are a few oddities from the data. I’ll try to post something soon, once I’ve determined the best way to present the information.


  • Jonas Pertoft

    Thanks! One of the best comparisons I have seen. I’ve only experienced the fast and flat Swedish race, but will now try the other end – in Wales – this year. At least 90 minutes slower.

  • dan

    In your opinion which is tougher, Wales (with full run distance) or Nice ??

  • Dan,

    Interesting question and one of the tougher pairs to choose between. This year Wales was particularly slow for the course and Nice was particularly fast, base on one year alone the conclusion would be Wales is the tougher race. A comparison of all Ironman races I did for 2012 has the two events much closer, although we know the run was shorter in Wales that year. (We could also note that the Ironman France bike is shorter than the full 112 miles too).

    Overall though I’d lean towards Wales being the tougher of the two. I think conditions in Tenby tend to challenge athletes more. That said I don’t think there’s a huge gulf between them and it may also depend on personal strengths as to which would better suit an athlete.