Fatigue Curves

Fatigue Curves

AC_head-1As long course athletes, we have some unique fitness requirements when it comes to race day performance — requirements that may or may not be accurately expressed by the plethora of short duration fitness tests that fill the popular training literature: Functional Threshold Tests (that we abridge because the full 60 minutes hurts too much J), CP5s, VO2max tests, VDOTS, Lactate Threshold tests, etc, etc. While these tests are a good indicator of how fast an athlete is, they don’t deal very well with the other element of the ironman performance equation — endurance. Put another way, how long can the athlete hold a given speed/percentage of his or her max fitness?

Gordo wrote an article about this key limiter some time ago in his piece on training in the fourth dimension. He concluded that, “If you are experiencing significant fade (power or pace) then you are endurance limited (regardless of what your FT performance indicates).” This article will be about how to go about quantifying just “how limited” you are when it comes to endurance for your respective event. In my previous series on “what it takes” I concluded that finishing an ironman requires pretty modest fitness but very good endurance. Similarly, winning an ironman requires very good fitness coupled with superior endurance. So let’s delve into this a little more, what constitutes good, bad or superior endurance?

Coaches such as Joe Friel and George Dallam have looked at this problem of quantifying endurance in some depth. Dallam’s concept of the athletic fatigue curve is a useful way of expressing the relative endurance strengths and weaknesses of two athletes who may have the same short term numbers. Simply, a fatigue curve looks at the rate of pace/power degradation over increased duration in a given athlete. A couple examples from two athletes that I currently work with are shown below:

Fatigue Curves

Power (in watts) is expressed on the y-axis. Duration (in hours) is expressed on the x-axis. Athlete 1 is a middle of the pack age-grouper (IM best of 12:23) with better than average results over sprint and short course races. Athlete 2 is an established long course athlete — a Kona qualifier with an ironman best of 10:03.

As you can see, in addition to exhibiting significantly different long course results, these two athletes also exhibit different fatigue curves, with Athlete 1 leading the way through to ~20 mins and Athlete 2 taking over at that point and widening the gap as the duration increases. If we were to compare these two athletes at FTP (one hour duration), very little difference is shown (about 7 watts; 283 versus 290W). However, if we look further down the curve, the difference at six hours increases to about 50 watts! Same aerobic power but significantly different aerobic capacity.

You’ll see the formula for the best fit equation in the top right hand corner of the diagram. Athlete 1 exhibits a fatigue index of -0.151, while athlete 2 exhibits an index of -0.109. An easier way to express these differences may be in the form of percent fade. Athlete 1 loses 10% power as the duration doubles. Athlete 2 only loses 7%. Despite very similar FTPs, this difference in fade has marked implications on each athletes respective Ironman race performance!

So, what’s a good level of fade?

For a long course athlete, the answer would be as little as possible. However, this may not be the case for athletes who race over a shorter duration, where a fine balance of aerobic and anaerobic capacity is required. Here are some typical numbers for different athletes/events:

Fatigue Curve Table_0

Obviously, these numbers speak to the level of aerobic basework required for different events. Even a 1500m runner requires substantial fatigue resistance to complement their speed/anaerobic capacity in order to be successful. Likewise, an elite sprinter requires more than pure 100% sprint training. A certain work capacity is a pre-requisite before the specific training hits full speed.

To put these numbers into better “iron-perspective,” in order to hold AeT intensity (approximately 60% VO2max) over the course of a 10 hour ironman requires a fatigue rate of better than 8%. Until the prospective ironman athlete has reached this level, there is little cause for specific preparation designed to raise the VO2max or FTP. For most athletes there is much greater upside in minimizing the swing at the end of the curve. Put another way, from our first example, Athlete 1 would need either a (massive) 75W increase in VO2 watts (~1L/min!) or a (measly) 3% shift  in the fatigue curve to create the same 10 hour power as Athlete 2.

Okay, so maybe ‘”measly” is a bit of an over-statement but the salient point is that while for many already well trained athletes, an increase of 75 watts may be a pipe dream, an improvement of 3% in the fatigue curve over multiple years of basework is bordering on expected. Coyle, et al. (1988, 1991), showed differences in one hour TT performance and LT relative to max power output indicative of a 6% change in the fatigue curve (improving from 10% to 4%) when comparing new cyclists (2.7 years) with those cyclists with a 10 year training history. On the other hand, the difference in VO2 power between the two groups was only in the range of 25W!

Hopefully this article has helped to answer the question of what “type” of fitness you most need. By looking at individual fatigue curves in the context of the athlete’s ability and event, we can readily determine potential weak spots that may help to guide the upcoming phase of training. With very few exceptions, most long course athletes have significant upside to building more base.

Train smart.

Categories: Training

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Alan Couzens

You can contact Alan at alan.couzens@gmail.com