18 August 2015
The Convict 100 MTB marathon is a classic Australian race, with the tenth edition having just been won by Today’s Plan ambassador, and Specialized Racing Australia team member Andy Blair, in a time of 3 hours and 54 minutes.
In this article, we’ll use Today’s Plan analytics to compare Andy’s data with that of a Masters rider from the same race to highlight just what it takes to win a 100km MTB marathon. In contrast to Andy, our Masters rider completed the 100km in 5 hours and 6 minutes.
Firstly let’s have a look at the comparative heart rate distribution charts. These show us the percentage of time the athlete spent in at each heart rate BPM. Both athletes had a threshold heart rate set to 168 BPM, so these charts can be compared side by side.
By looking at these charts it is quite clear that Andy Blair’s heart rate distribution is skewed to the right and more tightly grouped. He spent a greater percentage of the race between 160 – 170 BPM at or around his current threshold. When we compare this to the master’s ride you can see that the spread of heart rate distribution is greater and that a higher percentage of time was spent more in the low threshold/tempo range of intensity as well as a fair spread of heart rate in the low endurance zones as well. This give us an insight into the ability of the elite rider to maintain the intensity throughout the race and workout at a very high percentage of his threshold for long durations.
This is a product of both experience and training. Elite athletes have developed the ability to sustain threshold power/heart rate for long periods of time. This is often achieved during training with repeated 8 – 30 minute efforts at or around threshold intensity. By completing efforts in what we call sweet spot training (SST) a greater length of time can be spent at an intensity that creates a huge amount of adaptation without creating as much fatigue as full threshold intensity.
This can be observed more easily when relating the percentage of time spent at each zone when comparing the heart rate zone pie charts.
The heart rate zone pie charts show just how much percentage of time Andy spent in his threshold and VO2 zones compared to the master’s rider. Races are won and lost by the ability to produce large amounts of power in repeated efforts to attack on climbs or over small rises. With over 1700 vertical meters of climbing in the Convict 100, it is clear to see that Andy was really riding the climbs hard and at a very high percentage of his threshold. Targeting the VO2 energy system in training is hard and requires great focus and effort. It represents a range between 105 – 120% threshold power and above threshold heart rate. It requires the athlete is fresh enough to hit and maintain the power/heart rate associated with this energy system.
More often than not the more novice rider finds it hard to complete efforts at this intensity as heart rate lags behind the actual demands of the effort and most riders go out too hard in the first minute and then struggle for the remainder of the interval. These are best completed with the use of a power meter where possible and give huge adaptation to the aerobic energy system. Another reason for Andy’s ability to hit and maintain such a high percentage of threshold could also come down to freshness and getting the taper just right for the event. Most more novice riders don’t get the taper right and often leave their best race in the training done leading up to the event.
These comparative tables show the difference in average heart rate 159 BPM vs 134 BPM for the event as well as actual calorie cost of completing the race. Although Andy was over an hour quicker to cover the 100km his increased intensity meant he burnt more calories. The calorie formulas are based off average heart rate and time and do not reflect a truly accurate measure of energy expenditure. To get accurate caloric expenditure a power meter would need to be used where the actual mechanical energy could be measured. This would have more than likely shown a greater amount of calories used by the Masters rider over the course of the 5 hours.
The next set of charts look at the heart rate distribution over time during the race in a 3D format. These incredible charts allow us to really delve into the heart rate distribution and pacing of the riders through the race.
These charts are broken into 30 minute rows of data with the red row showing 0 – 29 minutes and the corresponding heart rates through to the last 30 minutes of the race. Andy’s data shows as expected a tight cluster of columns around the 160 – 175 BPM range and gradually increasing during the event. This could be due to attacks or cardiac drift through the race. The elite rider will have usually paced well and consumed the correct amount of carbohydrates to maintain the intensity of the effort throughout the race. This means that when the final attacks and efforts are needed there is enough energy left in the tank to make the winning move.
It is also clear to see that during the first 30 minutes that the race must have been quite controlled as there is a good percentage of data points in the 130 – 140 BPM range. Not going out to hard and sitting in with the group allowed Andy to be at or near the front of the race, but save energy and strength for the important section of the course.
If we compare Andy’s 3D chart to the Masters rider we can see a large distribution of very low heart rate in the first 30 minutes of the race. There could be a number of reasons for this, but this is more than likely to be this rider being held up at the start within a large group of riders. It is also clear to see that as the race goes on the heart rates for the Masters rider increase more rapidly. This could be due to lower levels of fitness and greater heart rate drift over time.
Being able to dissect rider performance and understand the demands of an event allow us to fine tune the training needed to produce results like Andy Blair. It is clear to see that to race at the highest level a rider must be able to sustain a very high percentage of their current threshold as well as a large percentage of time in or around VO2 above threshold.