CoachCox

Ironman South Africa 2014: Results and Analysis

I had a good idea what to expect when I downloaded and analysed the 2014 Ironman South Africa results this morning. Splits from my athletes on Sunday had quickly established that under race day conditions the new bike course appeared particularly slow. Looking at the results in detail confirms it wasn’t just those I coached – the field in general was significantly slower on the bike this year.

Distribution of Finisher Splits at Ironman South Africa 2014 Compared with Past Races

The distribution charts speak for themselves: comparing 2014 with previous years (themselves a mix of faster and slower race days) the bike was heavily weighted towards slower times and as a result so were the overall times. The difference is significant, easily outweighing the slightly faster swim distribution and probably leading to the slightly slower run distribution.

Distribution of Finisher Splits at Ironman South Africa 2012 Vs 2014

Ironman South Africa has seen tough bikes before. If we look back at the 2012 results the two races are broadly comparable; other than this year’s much faster swim distributions and averages don’t deviate much between the two.

Median Splits by Category at Ironman South Africa 2014
Median Splits by Category at Ironman South Africa 2007-2013

Comparison of median split times supports the pattern almost universally – swim very slightly faster, bike much slower, run very slightly slower. The slower median bike trend even holds among the professionals too – conditions and the new course had a clear impact on splits across the field.

Top 20 Male Age Group Performances and Kona Qualification at Ironman South Africa 2014
Top 20 Female Age Group Performances and Kona Qualification at Ironman South Africa 2014

When we look at the results for the top 20 in each age group compared with past races the picture is far less clear. In some categories times were at the very slow end of performances in South Africa, in others they trended marginally faster than average; in the case of the F30-34 age group some times are faster than previously recorded. Year-on-year variations in the quality of the competitive age group field has huge impact on race outcomes and is probably most notable in smaller categories. Certainly in the larger men’s field and the major age groups under 50 the impact is clear – top 20 times are at best average for South Africa in these consistently competitive fields. It should be noted that year’s change in course makes comparisons with the past difficult and largely superficial.

It’ll take a few more years of results to have a sense whether expectations at Ironman South Africa should be set lower (from a time perspective). The new bike course clearly gives the potential for a much slower day under the right, or rather wrong, conditions. At the same time the front-of-pack athletes continue to develop and the affect of tough conditions is less obvious in age group winning times.

As usual I’ve put a spreadsheet of the full results and splits from Ironman South Africa 2014 on Google Drive.

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Comments

  • Steve

    Many first time athletes for which this race was a bucket list item being the 10th anniversary edition – could that explain also the results being skewed to the left when compared to previous years? Wind was a factor on the last 45km of the bike, a piece of the bike course that was unchanged from previous years.

    Given a westerly wind on the day, the new course should make for much better times than before.

  • Steve,

    Thanks for commenting. It will be a factor and that is a trend I’m seeing across races in general – while there’s no real change in the average performances or distributions in races outside of yearly variation the front-of-pack age groupers are becoming more consistent and faster. So certainly the composition of the field is a factor in any race distribution, that said this is a much larger shift than I’d normally expect from that and compare with results from 2012. Seeing it among the pro field and also slower times in some competitive male age groups suggests bike conditions proved tough. It’ll be interesting to see how a few years of results pan out.

    Cheers

    Russ

  • Hi Russel,

    Awesome write up. As usual you are spot on with your analysis. As far as I could tell on the day the new wave seperation also played a role in slowing down the later waves as the easterly wind picked up and hit the older and younger third wave which would explain the slower times in those categories.

  • Ryan,

    I completely forgot about the wave starts and that probably played a role too. Unfortunately Ironman.com results never indicate wave or rolling start times for athletes although in this case I could probably refer back to the start list to see if there’s any relationship between wave start and performances. Regardless of changing conditions wave starts does mean later athletes would also have the benefits and disadvantages of working through more of the field.

    Russ

  • I have an unresearched hunch that tougher courses and conditions affect men worse than women. Ladies seem to cope better as it goes on longer and in general finish looking happier/stronger.

    This was also manifested in having 3 ladies in the top 20 which wasn’t the case previously, barring freakish chrissie wellington in 2011.

    Perhaps this is the resilience and pain threshold women require to deliver babies.

    Any stats to support/refute this sexist presumption?

  • Paul,

    I can’t say I’ve ever tried to look for a male/female difference in response to race conditions. Simple answer is that I suspect it would be very hard to identify, certainly with any degree of confidence with the result. The biggest issue would be the relatively small size and variability of the women’s age groups. Outside of the US then typically only 10% of the field is female and what I tend to see is that the ‘quality’ (my impression of the strength of the field) varies a lot from race to race and year to year. It makes it hard to track trends among female athletes.

    If I come up with a good way to look at how variation in races impacts variation in performance by gender I’ll give it a better look. I could perhaps simply compare changes in male/female fields by a few metrics from year to year and see which gender demonstrates the biggest shift.

    Perhaps the closest I’ve come to this is when I compared Kona performances against performances outside of Kona for qualifying athletes: . That doesn’t really identify specific differences relating to conditions and it focusses on the qualifying end of the field, but in 2012 male and female qualifiers were, on average, similarly slower in Hawaii than in other Ironmans that season; however men tended to have slower runs and women slower bikes as the main contributory factor.

    So I don’t have anything specifically addressing your idea and right now I don’t have a good method for better examining it in mind. That said I would expect to see some variation in male/female performances and responses, but the data may not be sufficient to really highlight those.

    Russ

  • michel morret

    Thank you for this analysis

  • Andrew Hibbitt

    Such great information in your analysis. Thank you for doing this. It gives great perspective when considering races for the coming season.

    Do you happen to have the info on slot allocation for 2014? With 75 slots this year I was curious as to whether some of the AGs got two slots this year that in prior years only received one?