LeMond's Mental Toughness

Many automobiles have a "range" feature that displays the number of miles the vehicle can travel before it runs out of gasoline. This number is not open to interpretation. If the range display says 29 miles, you'd better find a gas station within the next 29 miles. The mechanism of regulatory anticipation that athletes use to control their pace in races is different. It's not a number but a feeling, and like all feelings it is open to interpretation. One of the most important and valuable coping skills in endurance sports is the ability to interpret the perceptions that influence pacing decisions in a performance-maximizing way. As an endurance athlete, you want to get better and better at reading these perceptions in such a way that your internal pacing mechanism functions more and more like an automobile's range display. You want to be as correct as you can possibly be when determining the swiftest pace you can sustain to the finish line without exceeding your perceived effort tolerance.

Setting and pursuing time-based race goals is very helpful in the process of calibrating anticipatory regulation. This practice enables athletes to interpret their effort perceptions in a more performance-enhancing way by transforming the racing experience from an effort to go as fast as possible into an effort to go faster than ever before. Validation of this approach comes from a 1997 study done by researchers at Israel's Ben-Gurion University and published in the Journal of Sports Science. High school students were subjected to a test of muscular endurance and then spent eight weeks training to increase their time to exhaustion. Some of the students were given a nonquantitative goal to "do their best." Others were given a quantitative goal to better their performance in the initial test by a certain percentage. Even though all of the students did the same training, those who pursued quantitative goals improved their performance significantly more when the muscular endurance test was repeated after eight weeks.

More recently, a team of researchers led by Eric Allen of the University of California found that finish times in marathons tend to cluster near the round numbers (such as 4:30 and 4:00) that runners typically pursue as goals. This pattern would have carried little significance if Allen and his colleagues had not also noted that those runners who end up closest to these round numbers at the finish line slow down less than other runners in the final miles of a marathon— evidence that the pursuit of these round-number goals enhances performance. Regardless of how an athlete chooses to train, her training will yield greater improvement in race times if improving race times is the explicit goal of the training process.

Paying attention to the clock reduces the uncertainty associated with reaching beyond past limits and in this way facilitates effective pacing. While it may be impossible for an athlete who completes a race of a certain distance to know if he could have tried harder, it's relatively easy for an athlete who completes a race of a certain distance in a certain time to aim to cover the next race of the same distance a second or two faster than he did the last time.

According to Samuele Marcora's psychobiological model of endurance performance, the amount of effort that an athlete puts into a race is influenced by her perception of the attainability of her goal, a concept borrowed from Jack Brehm's theory of motivational intensity. If the goal seems to fall out of reach at any point during the race, the athlete is likely to back off her effort. If the goal seems attainable, but only with increased effort, the athlete is likely to increase her effort, provided she's not already at her limit. By keeping track of, and aiming to improve, personal best times for specific race distances, athletes can exploit this phenomenon to try harder than they would otherwise be able to. The goal of improving your time for a certain distance by 1 measly second almost always seems attainable. And if that goal is attainable, then the very slightly greater level of perceived effort that an athlete must endure to achieve it is likely to seem more endurable than it would seem if the athlete were going entirely by feel. It's not the time goal itself that enhances performance but the effect that the goal has on how the athlete interprets her perception of effort.

Setting time-based goals that stretch you just beyond past limits is like setting a flag next to a bed of hot coals to mark the furthest point reached in your best fire walk. That flag says to you, "This is possible, and you know it. So why wouldn't it be possible for you to make it just one step farther the next time?"

A real-world example of this process of using time-based goals to recalibrate perceived effort in a performance-enhancing way is South African runner Elana Meyer's career progression at the halfmarathon distance. In 1980, when she was 13 years old, Meyer took her first shot at 13.1 miles, winning the Foot of Africa half-marathon in a mind-boggling time of 1:27:10. Nine years later, Meyer made her professional debut at the same distance, running 1:09:26 in Durban. In 1991, she smashed the half-marathon world record in London, clocking 1:07:59. Between 1997 and 1999, Meyer broke the record thrice more, running 1:07:36, 1:07:29, and finally 1:06:44 in Tokyo at age 32.

Obviously, Meyer's development as an athlete was responsible for much of this improvement. But her pursuit of time goals also played a role. It is interesting to note that her margins of improvement tended to get smaller as her career advanced. Her big leaps from 1:27 to 1:09 and from 1:09 to 1:07 were undoubtedly fueled principally by gains in fitness. Meyer probably wasn't even thinking about her first half-marathon when she made her pro debut, so much stronger was she by then. But her last two world records were set on familiar courses on which she had already posted fast times, and in each of these cases she set out deliberately to run faster than ever before. It's likely that Meyer was not any fitter at the 1999 Tokyo Half Marathon, where she ran 1:06:44, than she had been a year earlier in Kyoto, where she ran 1:07:29, but she had the crucial advantage of having run 1:07:29 already.

But wait: If Meyer was just as fit (not to mention a year younger) when she ran the slower time, then can it not be said that timekeeping held her back in the 1998 Kyoto Half Marathon, even as it pulled her beyond the world record of 1:07:36 she had set on the same course in 1997? There is indeed evidence that the influence of clock watching on endurance performance is two-sided. The same time goal that enhances performance when it is perceived as a target constrains performance when it is perceived as a limit.

The potential for time standards to become performance limiters is most apparent at the elite level of endurance sports. There have been many noteworthy cases in which a performance breakthrough by one athlete triggered a widespread revolution in performance and thereby revealed that previous standards had been holding the sport back. Between 1994 and 2008, for example, the women's world record for triathlon's Ironman distance was stuck at 8:50:53. Only seven women recorded times under 9 hours in that 14-year span. When Yvonne van Vlerken finally lowered the Ironman world record to 8:45:48 in July 2008, the floodgates were opened. Six other women dipped under the 9-hour barrier in the next few months. Van Vlerken's mark lasted only one year, as did the subsequent record. By the end of the 2011 season, the Ironman world record for women stood at 8:18:13, and sub-8:50 performances had become commonplace. Was the new generation of female triathletes that much more talented than the previous one? No. These women just weren't held back by a tendency to regard the time of 8:50:53 as an unsurpassable human limit.

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