Predictive Power of vV·O2max
To begin to comprehend the lack of predictive power of V·O2max in contrast to that of vV·O2max, consider an extremely well-trained runner who happens to have large, clunky feet. Such a runner will tend to have a high V·O2max because of the demanding training he or she has been undertaking, and the clunky feet will add to V·O2max, driving it higher compared with a similarly trained runner with small feet. Having to move those large feet down the road at high rates of speed will call for extremely high rates of oxygen production. However, large feet will not make the runner competitive; in fact, they will cause this runner to reach V·O2max at a rather modest speed since so much oxygen is being used to move the big feet along. Thus, this runner will have a high V·O2max but relatively poor running economy, and thus a moderate vV·O2max and moderate performances. As usual, vV·O2max will be more reflective of performance potential than V·O2max.
This big-foot scenario is an extreme example of why vV·O2max predicts performance quite well. It is important to bear in mind that the same situation prevails for runners in general who have modest to poor running economy for reasons other than big feet. Such athletes might have high levels of V·O2max. If running economy is subpar, however, any particular running speed will elicit an unusually high rate of oxygen consumption, and V·O2max will be reached at relatively mediocre running speeds. Thus, performance potential will be below what might be expected from the determination of V·O2max alone.
The power of vV·O2max to predict performance is illustrated in a study carried out at Lynchburg College in Virginia in which 17 well-trained distance runners (10 males and 7 females) underwent physiological testing and then competed in a 16K race. Laboratory tests determined V·O2max, vV·O2max, running economy, percentage of maximal oxygen uptake at lactate threshold (%V·O2max at lactate threshold), running velocity at lactate threshold, and peak treadmill velocity. The Lynchburg researchers found that among all the measured physiological variables, vV·O2max had the highest correlation (r = –.972) with 16K performance, while %V·O2max at lactate threshold had the lowest correlation (r = .136). Overall, vV·O2max was found to be the best predictor of 16K running time, explaining all but just 5.6 percent of the variance. The Virginia scientists concluded that vV·O2max is the best predictor of endurance-running performance because it integrates maximal aerobic power with running economy.
In a separate study carried out at Fitchburg State College in Massachusetts, 24 female runners from four different high school teams competing at the Massachusetts 5K State Championship Meet were tested in the laboratory. These tests revealed a high correlation between vV·O2max and 5K performance (r = .77). In contrast, the correlation between V·O2max and 5K speed was lower, and running economy at a slow velocity (215 m per minute) was poorly correlated with 5K outcome. Note that economy at race-like speeds is predictive of race competitiveness, while economy at slow velocities is not necessarily linked with racing capacity (another argument against conducting a lot of training at medium to low speeds).
In a classic study carried out at Arizona State University in Tempe, vV·O2max was found to be a primary determinant of 10K performance in well-trained male distance runners. Among these runners, the variation in 10K running time attributable to vV·O2max exceeded that due to either V·O2max or running economy.
Impact of Training on vV·O2max and Running Economy
French researchers Veronique Billat and Jean-Pierre Koralsztein have concluded that vV·O2max predicts running performances very well at distances ranging from 1,500 meters to the marathon. They also noted that vV·O2max has similar predictive power in cycling, swimming, and kayaking; of course, vV·O2max would have to be determined for each sport since running vV·O2max does not carry over to other activities. Billat and Koralsztein also discovered that training that emphasizes intervals conducted at vV·O2max can be extremely productive for distance runners.
In one study, Billat and Koralsztein asked eight experienced runners to take part in 4 weeks of training that included one interval session per week at vV·O2max. The athletes specialized in middle- and long-distance running (1,500 m up to the half marathon), and their average V·O2max was a fairly lofty 71.2 ml • kg-1 • min-1. This program included six workouts per week, including four easy efforts, one session with work intervals at vV·O2max, and one session at lactate-threshold speed with longer intervals. Total distance covered per week was about 50 miles (~ 80 km). Over the 4-week period, the runners’ weekly training schedules were formatted in the following way:
- Monday: One hour of easy running at an intensity of just 60 percent of V·O2max.
- Tuesday: A 4K warm-up and then vV·O2max interval training consisting of 5 × 3 minutes at exactly vV·O2max. During the 3-minute work intervals, the runners covered an average of 1,000 meters (.62 mi; their vV·O2max tempo was 72 seconds per 400 meters). Recovery intervals were equal in duration (3 minutes), and the cool-down consisted of 2K of easy running. Overall, the workout was a 4K warm-up, 5 × 3 minutes at vV·O2max, with 3-minute easy jog recoveries, and a 2K cool-down.
- Wednesday: 45 minutes of easy running at an intensity of 70 percent of V·O2max.
- Thursday: 60 minutes of easy running at 70 percent of V·O2max.
- Friday: A session designed to enhance lactate threshold composed of a warm-up and then two 20-minute intervals at 85 percent of vV·O2max; for example, if vV·O2max happened to be 20 kilometers per hour (5.55 m per second), the speed for these intervals would be .85 × 20 or 17 kilometers per hour (4.72 m per second). A 5-minute, easy jog recovery was imposed between the 20-minute work intervals, and a cool-down followed the second work interval.
- Saturday: Rest day with no training at all.
- Sunday: 60 minutes of easy running at an intensity of 70 percent of V·O2max.
After 4 weeks, the results were amazing, to say the least. Although maximal aerobic capacity (V·O2max) failed to make any upward move at all, vV·O2max rose by 3 percent from 20.5 kilometers per hour to 21.1 kilometers per hour. In addition, running economy improved by a startling 6 percent. This enhancement of economy was probably behind most of the uptick in vV·O2max since it lowered the economy line on the graph of oxygen consumption as a function of running speed and thus pushed vV·O2max out to the right for the French runners.
After the 4 weeks of training, lactate threshold remained locked at 84 percent of vV·O2max. However, since vV·O2max was 3 percent higher at the end of the training period, running velocity at lactate threshold had also increased by a similar amount. Most of the key variables associated with endurance performance—vV·O2max, economy, and lactate-threshold speed—had advanced in just 4 weeks.
The 6 percent gain in economy associated with vV·O2max training was particularly impressive. A handful of training manipulations have been linked with upgraded economy, and the gains in economy have usually been far below the one documented by Billat and Koralsztein’s research. A classic Scandinavian hill-running study (see chapter 25) detected only a 3 percent increase in running economy, even though the hill training was conducted for three times as long (12 weeks versus the 4 weeks needed by the French runners in Billat and Koralsztein’s study). Similarly, improvements in economy associated with strength training have usually been in the 3 percent range, also after fairly long periods of training. It appears that vV·O2max training can work economy magic in as little as 4 weeks, especially for those runners who have not carried out vV·O2max work previously.