The search for the optimal pace
A reassuring mathematical approach
Finding the optimal pace in any competition is no easy task. It is not the Holy Grail either, but we must recognize the enormous difficulty of knowing if we could have done better (except in those circumstances in which it is flagrantly yes).
In a fairly old article on performance evolution indicators I wrote about the concept of decoupling heart rate and pace or power. To quickly refresh your memory, this is the degree of parallelism that both lines have as the competition progresses. The fact that they lose parallelism indicates that the management of the competition has not been adequate or we have exceeded the length of the competition. However, the fact that they are parallel does not assure us that the choice of intensity has been the most suitable, since if we go below our real possibilities of performance, it is logical that we will be able to sustain the effort without any problem.
For this reason, finding that exact point of suffering is certainly complicated and more so the more variable and the longer the competition. Is not the same manage the intensity in a 10k on asphalt, a vertical kilometer of trail, a time trial in cycling, a sprint triathlon or a short race of cross-country ski they all have in common that you go flat out) than an ultra trail, a marathon of asphalt, a cycling stage in line or an Ironman. It is also not the same to manage a race for a leading competitor, than one who is going to look for his best time or one who is going to simply finish.
The selection of intensity is multifactorial and due to this, it is highly complex. This is one of the reasons why we are more nervous before facing a competition. The uncertainty of knowing how to find the right point of suffering and whether we will be able to sustain it until the end is what generates the most tension in us during the previous days or even weeks.
Power and pace as the most valid references
In another old article titled Stryd power meter on trails and ultra trails, I wrote about how well I was going to use the gps and/or the potentiometer to be able to correctly manage competitions. To do this, we simply needed to have a correct baseline for the functional pace/power threshold. From that point on, we had to modulate our effort according to the length of the race. In this way, we made sure that we could sustain the intensity from start to finish without melting down beforehand and arriving on foot or crossing the finish line without having given away performance.
However, and as I pointed out before, this is not that simple. A runner who aspires to win the competition will not move only by watts or pace, he will also assess what his rivals do. In addition, if we are in a sport in which going in a group “helps”, management according to pace and watts (in consistent ranges) will be even more stochastic and circumstantial, less constant and more adaptive to race circumstances.
This strategy gives a better result than looking for a power according to the distance of the cycling section and riding alone until T2. In fact, the average power and the amount of energy spent will be higher in the second of the two scenarios and therefore, in the race it will suffer this wear.
On the other hand, in time trial competitions, and even being a professional runner who aspires to win the Tour time trial, the management of the competition will be the same as that of a runner who is looking for his best time, no matter how mediocre it may be. Here it will be convenient to study exactly in which intensity ranges you should move to reach your best version. You must also take into account technical aspects related to the activity itself. All for performance.
At this point, it is necessary to point out that the competitor who is looking for his best version, disputes a test in which “going on a wheel, riding in a group or going on foot” is better than going alone and does not compete in a time trial or in the one that explicitly prohibits “drafting”, will manage in a certain way as the one who seeks to win but making war with the competitors of his level, those who are in his positions.
However, I do not want to take a mechanistic approach to this article based on precise references in order to achieve the best performance. With this one, I’m looking for a more psychological approach so that, to the objective tools with power/rhythm data, one can add a more positive and reassuring frame of mind.
The optimum race pace chart
Imagine that you are a car that has to do the 500 miles of Indianapolis without stopping to refuel at any time. According to the engineer, this means riding at 50 miles per hour.
If you go over those 50, you will not cross the finish line, if you go slower you will cross it but with a worse time.
And what it’s all about is finding that sweet spot of speed. Therefore, you pay attention and the graph of the competition would be like this:
On a bodily level, this is complicated to execute the longer and more variable the competition is because we are not a machine and many other aspects come into play that make us such a special mix of perfectly imperfect.
Many factors influence how we are going to face our 500 miles with our corporeal vehicle and all of them together will allow us to achieve a slightly higher performance than those 50 miles per hour that the engineer has given us as a reference or stay below.
The most curious thing about the case is that it can happen that, having followed the instructions to the letter and being constantly at 50 mi/h, we don’t get to cross the finish line despite still having gas in the tank! What it said… perfectly imperfect.
In an asphalt marathon, a paradigm of regularity in a sports competition, we try to reproduce a graph that is as similar as possible to the optimal pace as “our” car that has served as an example. Very few chosen ones, like Kipchoge, can enjoy those 20-21 km/h approximately on average to reach the goal and others settle for a more than worthy 15 km/h. But tell Pheidippides if he hadn’t agreed to run at that pace.
However, the competitions are much more variable and more so if they are mountain races. That is where one must decide at each precise moment what intensity to select to reach the goal without giving away performance but ensuring that we are not going to run out of gas.
If you are Kilian or someone similar, it is simple. Your optimal graph is always above the optimal graph of the rest of the participants and therefore, you settle at a pace below yours, force yourself in the final part and win the easy race. However, similar optimal graphs must already compete with each other and therefore, intensity management ends up being like a game of poker and the interaction with mental, nutritional, technical factors,… ends up being crucial to prevail over the others. rivals.
In this situation, what is very important to understand, both for top runners and runners looking for their best performance, is that “visits” to the top of the optimal pace have a cost and that cost is paid.
Graphically it could be represented as follows:
As a result, we would have that the average speed obtained following the constant rhythm would be 50 miles per hour, while in the second case it would be 49.81 miles per hour. Consequently, the result would be worse.
It is very important to point out that each person “pays” the price of these “visits” differently and that even that same person, depending on the moment, can also pay it differently depending on the circumstances.
Here are some examples of that variability:
A triathlete who has run and won a competition many times. His degree of activation and motivation is lower than expected, he goes at the optimal rhythm but due to excessive relaxation he does not take proper care of nutrition and ends up not being able to reach his optimal rhythm. This occurs because he sees himself outside the podium and cannot activate himself motivationally in the final part.
A veteran trail runner who knows himself perfectly. He makes a prudent exit, in the middle part he forces the machine knowing that in the end he will have to suffer. Since he knows exactly his performance possibilities, he plays in the final part so that the performance does not drop excessively. However, as it is the last race of the season, he ends up settling for a position that if it had been in a race at the beginning of the year, he would have forced more.
The reassuring mathematical model
Going back to the subtitle of the article where I used the word “reassuring” when looking at intensity management from a mathematical point of view and summarizing everything said above, one should think of the graph above as lines and areas .
Those lines draw some areas with a specific extension. You have to be aware that:
- Areas generated above optimal pace/power are ALWAYS smaller than those generated below.
- The above areas that are carried out at the beginning of the race, do not usually give good sporting results.
- The more area you gain above, the worse the end result will be.
- Starting the competitions “giving away” areas, allows certain rhythms to be saved above the optimal rhythm in the final part and therefore, to recover part of that lost area.
Graphically it would look like this, where the ellipse on the left contains a smaller area than the one on the right.
The graph above is certainly a simplified model where the runner goes out fast, the pace that is set intersects with the optimal pace and ends up falling to an average below the optimal average pace. However, this is not the case, since the real pace goes up and down depending on the circumstances of the race. Therefore, when it comes to knowing if we have done well, we must look at the speed averages. If, in the end, the average reached is very close to the theoretically optimal average, it means that we have correctly managed the competition and, most importantly, we have a reference value for the future in case we want to propose a more aggressive strategy.