Ironman New Zealand 2025: Age Group Stats and Qualification
Two weeks ago the first Ironman of 2025 took place in New Zealand. This is little late, but it’s been five years since I last reviewed race results and statistics. I’ve had to dust off and update some very old code to work with the changes made in that time. There’s a lot of relevant data in the links above, but this review allows for a deeper dive and comparison.
I’m limiting all comparisons to the last 5 races in New Zealand. This is for manageability and to reduce the impact of historical results when considering current performance.
Let’s begin with finisher distributions, charting the percentage of the field finishing within specific times. The main takeaway: there isn’t a huge variance in this year’s results compared with previous events. Overall this year was slightly faster at the average and slightly slower at the front (top 5%). Differences are small and appear to be the result of a faster average bike. Front runners were comparable at every stag, just a little slower on swim and run. Nothing here feels out of line with expectations for the course.
There are no surprises in the DNF numbers. Levels are comparable with previous years of racing. There’s a shift to more DNFs on the run course and a lower DNF rate on the bike course, but the overall figure remains around expected levels.
Comparing median splits across age groups always highlights how varied performances can be. While we may note a faster average bike from the race distributions this isn’t true for all age groups. It appears that the faster averages are mostly in women’s and older male age groups. Other variances show less of a pattern. I’d emphasise that these are relatively small variations in the majority of.cases.
Given its remoteness New Zealand always does a good job of drawing a wide range of nationalities to its race. The majority of qualifying slots appear to stay in the home country. Note that roll down is not factored into this calculation.
Tracking changes in finishing time for age groups over a number of races is another way to highlight the variations hidden in the bigger statistics. Lower numbers of female competitors lead to a more fluctuating set of results. My best conclusion is that this year doesn’t stray far from the average. It’s definitely not the slowest or the fastest. This would fit with a slightly faster average when looking at the distributions. It’s not uniform of course – M40-44 results lean more consistently slower than the previous years.
Based on starers and the slot numbers for New Zealand I’ve calculated an expected slot allocation and from that automatic qualifying times. This doesn’t factor roll down. With the split of Nice and Kona qualification roll down may be more of a factor now. You can find lots more statistics on qualification at New Zealand on its qualification page.
The final set of graphs look at the top 20 finishers in each age group and how times vary over recent year. As we’ve already observed the fastest athletes were a little slower than usual. M40-44 stand out for being much slower than recent years but for most age groups this isn’t the slowest year at the front of the pack.
Final conclusions: a slower year for the front of the race but condition appear to have supported mid and back of pack athletes bringing up the race average a little. It was mostly business as usual for the course.
You can browse the data for this race using the links below. Work to make more of these graphs dynamic is ongoing!