Ironman Australia 2016: Results and Analysis
I spent my weekend in a wifi and data wilderness so I’m late to the analysis of results for Ironman Australia 2016. The race took place on Sunday. At over 30 years old it’s one of the longest standing Ironman races on the calendar. It’s a small affair compared to some of the US and European events, typical drawing in 1300-1500 athletes. The cancellation of this year’s championship race in Melbourne did bring an additional 15 Kona slots to the event; meaning 55 were on offer on Sunday.
This is going to be a quick analysis. I’ll let the charts do the talking and keep my own comments brief. You can see in the distributions above that the 2016 race trended slower than usual, particularly on the bike. The one thing to bear in mind in this and any of the other comparisons is the amalgamation of 11 years of previous race data may hide some patterns in the past. This year trends slower, but it’s not hugely out of line with expectations for this race.
| Listed Athletes | Swim Finish | Swim DNS/DNF | Bike Finish | Bike DNF | Run Finish | Run DNF | Overall DNS/DNF | |
|---|---|---|---|---|---|---|---|---|
| 2005 | 1619 | 1539 | 4.9% | 1092 | 29% | 1366 | % | 15.6% |
| 2006 | 1580 | 1510 | 4.4% | 1475 | 2.3% | 1448 | 1.8% | 8.4% |
| 2007 | 1620 | 1521 | 6.1% | 1493 | 1.8% | 1458 | 2.3% | 10% |
| 2008 | 1543 | 1460 | 5.4% | 1432 | 1.9% | 1410 | 1.5% | 8.6% |
| 2009 | 1400 | 1323 | 5.5% | 1300 | 1.7% | 1282 | 1.4% | 8.4% |
| 2010 | 1482 | 1458 | 1.6% | 1422 | 2.5% | 1384 | 2.7% | 6.6% |
| 2011 | 1070 | 1048 | 2.1% | 1038 | 1% | 1016 | 2.1% | 5% |
| 2012 | 1468 | 1342 | 8.6% | 1323 | 1.4% | 1298 | 1.9% | 11.6% |
| 2013 | 1603 | 1423 | 11.2% | 1389 | 2.4% | 1352 | 2.7% | 15.7% |
| 2014 | 1699 | 1505 | 11.4% | 1480 | 1.7% | 1451 | 2% | 14.6% |
| 2015 | 1530 | 1365 | 10.8% | 1325 | 2.9% | 1282 | 3.2% | 16.2% |
| 2016 | 1355 | 1345 | 0.7% | 1325 | 1.5% | 1294 | 2.3% | 4.5% |
The DNS and DNF data also suggests it was a fairly typical year for Ironman Australia. There is some variance in numbers from the swim which leads me to suspect the reporting of starters has changed over the years. This boosts the drop off in numbers finishing the swim as registered athletes who didn’t make the start line are still included.
| Count | Percentage | |
|---|---|---|
| Australia | 1205 | 88.9 |
| New Zealand | 31 | 2.3 |
| China | 17 | 1.3 |
| Japan | 15 | 1.1 |
| United States | 10 | 0.7 |
| Ireland | 7 | 0.5 |
| United Kingdom | 6 | 0.4 |
| Hong Kong | 4 | 0.3 |
| India | 4 | 0.3 |
| Philippines | 4 | 0.3 |
A new table – in early form. A break down of the top 10 nationalities at the event. Unsurprisingly it’s mostly Australians at Ironman Australia. I want to see how these numbers vary with different races (a shame not to be able to see how a championship event like Melbourne might compare) and also how many slots go to local athletes.
Median numbers give another view of the race and it’s history. Again the bike trending slower is the main difference to note.
Comparing times for specific places over the last 12 years allows us to check for trends. This year’s race doesn’t look to be the slowest on the course, but it’s slower than the last 3-4 years of results. Not universally across the age groups, but for many of the largest.
| Slots | Winner | Average Kona Qualifier | Final Qualifier | |
|---|---|---|---|---|
| M18-24 | 2 | 10:03:26 | 10:13:34 | 10:23:42 |
| M25-29 | 3 | 9:10:32 | 9:14:34 | 9:18:57 |
| M30-34 | 4 | 9:05:38 | 9:22:48 | 9:29:02 |
| M35-39 | 5 | 9:09:38 | 9:21:29 | 9:33:17 |
| M40-44 | 6 | 9:22:45 | 9:38:09 | 9:46:33 |
| M45-49 | 6 | 9:27:38 | 9:44:31 | 10:03:11 |
| M50-54 | 4 | 9:52:20 | 9:56:36 | 10:02:00 |
| M55-59 | 3 | 10:17:56 | 10:27:09 | 10:39:18 |
| M60-64 | 2 | 10:33:21 | 10:48:58 | 11:04:35 |
| M65-69 | 1 | 11:53:28 | 11:53:28 | 11:53:28 |
| M70-74 | 1 | 13:58:42 | 13:58:42 | 13:58:42 |
| M75-79 | 1 | 15:41:39 | 15:41:39 | 15:41:39 |
| F18-24 | 1 | 10:50:26 | 10:50:26 | 10:50:26 |
| F25-29 | 2 | 10:54:38 | 11:05:12 | 11:15:47 |
| F30-34 | 2 | 10:07:41 | 10:10:00 | 10:12:19 |
| F35-39 | 2 | 10:23:55 | 10:28:19 | 10:32:44 |
| F40-44 | 2 | 10:06:06 | 10:19:58 | 10:33:51 |
| F45-49 | 2 | 10:50:10 | 10:51:35 | 10:53:01 |
| F50-54 | 2 | 11:31:49 | 11:32:19 | 11:32:49 |
| F55-59 | 1 | 12:31:24 | 12:31:24 | 12:31:24 |
| F60-64 | 1 | 14:30:26 | 14:30:26 | 14:30:26 |
| F65-69 | 1 | 15:21:15 | 15:21:15 | 15:21:15 |
| F70-74 | 1 | 15:08:17 | 15:08:17 | 15:08:17 |
These are my estimate for the Kona slot allocation based on the start list. The actual allocation may differ, but I’ve not seen a copy. The times give assume no slots rolled down, they’re what would have granted an automatic qualification with this slot distribution.
While the race as a whole trends slower at the front times aren’t that different from average. It appears younger age groups faired more poorly and came, but somewhere over 30-34 top twenty times fall close to the average. In some of the older age groups this year came out ahead of the average.
You can access a spreadsheet of the full results and splits from Ironman Australia 2016 on my Google Drive.
