Darth Vader Rides the Teams Pursuit
Maximal Accumulated Oxygen Deficit (MAOD)
MAOD is the theme of today’s chat.
This is something I first learned about via The Book (Training and Racing with a Power Meter) and also in subsequent analysis of power meter data kindly undertaken for me by Dr Andy Coggan last year. It’s pretty funky stuff, so hang on for the ride if you can.
For those interested in delving further, Andy has also prepared a Powerpoint presentation on the topic of the demands and preparation for individual pursuiting which is available for download at the Fixed Gear Fever download page. It's worth a look.
First, let me go back a step or two…
As some would know by now, I’m targeting two predominantly aerobic events, which have an anaerobic twist – the individual pursuit and points racing.
Along the way, I get the chance to ride in one of my favourite events, the Teams Pursuit.
A description of all these events can be found here. A quick glance at my recent posts and you’ll see that my team had success this past weekend, winning the NSW State Master’s Championship.
Two members of the team (Phil & myself) used power meters during the qualifying and final rides.
We also both have power meter data from previous individual pursuit efforts.
So, what can we learn from such data, in particular what can it reveal that may assist us?
As is already explained in a discussion about the Individual Pursuit in the book (pp 189-192), the performance of a rider in an Individual Pursuit is primarily determined by the combination of their aerobic and anaerobic work capacities.
The discourse demonstrates that power meter data from an individual pursuit can be used to estimate the proportion of a rider’s power that is being generated from each of their aerobic and their anaerobic energy systems.
In particular, it is possible to use this data to estimate a rider’s Maximal Accumulated Oxygen Deficit (MAOD) – the best measure of a rider’s anaerobic capacity.
Based on this information, conclusions can be drawn about a rider’s individual capacities and it can help decide the type of training specific to that individual which is most likely to optimise performance (i.e. what specific training leading into the event will make me go the fastest I can go?).
Of course, in an individual pursuit, a rider typically accelerates up to speed and then settles into a quasi-steady state power output, typically at a level equivalent to their power at VO2 Max. See example here. The time taken to reach that VO2 Max power level does vary by rider and is proportionally longer for athletes with higher anaerobic work capacities.
In a Team Pursuit however, the demands are subtly different.
While the overall aerobic and anaerobic demands are similar to an individual pursuit, the Team Pursuit also requires a greater degree of technical skill (for riding at 55+kph in an aero pursuit position just inches from the wheel in front, riding a good line in the bends and to effect smooth change overs of the lead rider).
It also places a greater emphasis on neuromuscular power (as the power demands are significantly variable compared to an individual pursuit – e.g. going from following a wheel to being on the front without changing pace demands a significant & rapid change in power).
So in a sense, not all aerobic monsters will necessarily make good team pursuiters.
Riders like Brad McGee, Stuart O’Grady and Graeme Brown however all possess sensational aerobic engines and have the skill and top end power required for success in such an event.
Meanwhile, back in the Death Star....
So can we apply the MAOD analysis to Team Pursuit power meter data given that you never reach a quasi-steady state in such an event?
Well originally I didn’t think it would be valid but as is his way, Dr Coggan showed it was possible (there are a couple of caveats which I won’t go into here) and he came up with some pretty interesting results.
Let’s start with Phil’s data.
Rather than rewrite what Andy has already written, let me simply quote him here:
"In a laboratory setting, the gold standard for measuring anaerobic capacity is maximal accumulated O2 deficit (MAOD), i.e., the summed difference between the energy you produce aerobically and the overall energy demand. While we obviously don't know Phil's VO2 during his efforts, his VO2 kinetics, his VO2max, or his efficiency, it is possible to make some reasonable estimates and thus to estimate MAOD, as I did for Phil last year.
Evolution of O2 Deficit
As you can see in the graph titled "evolution of O2 deficit", during the individual pursuit his O2 deficit (the dark blue line) increased progressively for the first ~2 min of the event, after which it apparently became strictly "pay as you go", i.e., all of the power was apparently being generated aerobically.
This is exactly what you expect and what you typically find, with the only real difference between individuals of differing ability being the absolute values and the time point at which all of anaerobic capacity is expended (e.g., for me, it only takes ~1.5 min, whereas for my wife it takes 2.5 - 3 min).
So, what happens when you extend the same logic to analyze the team pursuits? Interesting stuff, that's what! :-)
Specifically, during the qualifier Phil's O2 deficit (the purple line) grew rapidly during the first 40 seconds, then held steady while he was on the wheels, then grew again when he took a pull, recovered a bit, and so on. Notably, however, at no point did it achieve the same value as during his individual pursuit last year. Assuming that he's in roughly the same shape now, this implies that he was never completely at his absolute limit, and thus was able to call upon his anaerobic reserves when he had to elevate his power above his aerobic maximum while taking his turn at the front and then getting back on again.
In contrast, during the final the power requirement was significantly higher from 40 seconds on, such that his cumulative O2 deficit (the yellow line), while flucuating a bit due to being in a paceline, essentially followed the same time course of that seen during the individual pursuit. IOW, in this case he *did* appear to be at or near his absolute limit throughout almost the entire race, so he simply couldn't recover after taking that final pull."
~ Andy Coggan
Now I should add that the final was ridden at a pace ½ second per lap faster than the qualifier and that Phil played the role of lead rider (I knew Phil had the experience to pace the start to schedule).
In the final after his third pull, Phil had reached his limit and withdrew from the pace line, leaving the three remaining riders to complete the final three laps (in team pursuits, it is the elapsed time of the third rider across the line that determines the result – assuming you don’t catch the other team).
½ second quicker per lap may not sound like much but as you can see from the chart, it can quickly take someone from being “comfortable” to being right on or over a their limit.
Use the Force, Luke
OK, Andy has shown us something pretty funky with Phil’s data, so what did mine look like? Click/right click on pic to see an enlarged version:
Well at first glance it looks similar to Phil’s chart, however there are some significant differences:
- My cumulative O2 deficit in an individual pursuit (the dark blue line) is of a lower overall magnitude than Phil’s
- In the Team Pursuit qualifier (the purple line), it is apparent that I never fully depleted my anaerobic reserves, whereas Phil did slightly during the initial laps (Phil was the lead rider, so that is not unexpected).
- Indeed looking at the O2 deficit line, it is apparent that I was recovering quite rapidly when back in the pace line.
- In the Final (the yellow line), once again I did not exceed my anaerobic capacity until it was time to do a pull on the front.
But note my recovery when back in the paceline compared to Phil’s. While Phil’s cumulative O2 deficit effectively kept climbing (indicating a depltion of anaerobic reserves), I was recovering sufficiently to enable another two strong pulls on the front, especially the final effort on the last lap and a bit (which took us from behind to in front of the other team).
- So it appears that I too am in at least as good a shape as last year
one should never discount the positive impact that motivation has on one’s ability to find a little more from somewhere within. I have always been a highly motivated rider in a group scenario.
In summary, once again this demonstrates the value of power meter data. Would have I done anything differently armed with such information? Perhaps. With data from all riders I may have decided on a different rider order. Certainly we rode as hard as we could but could have we used our resources more effectively and achieved an even faster time?
Next year I expect all squad members will have power meters and perhaps I’ll be able to back up my intuitive assessment with a more objective look at the data.
One thing is for sure, be careful when you ask a sprinter to provide sideline-pacing instructions to a team pursuit squad!
Photo courtesy of Action Snaps photography