However, we can see general recommended strategy for this 2km flat course with a starting ramp is to:

[1] Ride at a relatively high power output until you get up to race speed, which should take you around 10-15 seconds.
[2] Then, lower your power output just enough to maintain that race speed.
[3] Finally, when you are about 15 seconds away from the finish, you should also be close to exhaustion and require ramping down your power output significantly.

This means that you should not have the ability to ride through the finish line with a sprint or even close to the power output you gave during the middle portion of the race. You should be near exhaustion about 15 seconds before the finish and just pedal on fumes for the rest of the race and coast down your speed as needed. You do not want to finish the race with anything close to what you were putting out because that means you are just wasting power to make you go fast *after* the finish line. Instead, both your power output and speed should drop as you approach the finish.

Another important thing to keep in mind, is that when starting the race, you should *not* generate so much power that you go over your race speed of the middle portion of the course. All the plots show that your speed should ramp up until you reach race speed, but not go over it because of an overzealous start.

If we take a look at the time required to finish the first half of the race compared to the last half, we can see that in all cases that first half will take longer then the second half. This means that we have a negative-split strategy here. For example, with the CCAP power metric optimization (Plot #1), it takes a total riding time of 138.8 seconds. The first 1000 m require a time of 71.9 seconds, while the second half required only 66.9 seconds.

What can we gather from the results of Plots #4, 5, and 6? The first thing that is apparent is that we can save about 1.3 seconds by using the optimized strategy generated by Optimal Cycling compared to Larsson’s raw power numbers. To put this into context, a 1.3 second time savings would have moved Larsson up from his 38th place finish to a higher 29th place finish. Utilizing the optimal pacing strategy generated won’t make him magically win the Prologue, but it gives him a good boost in ranking.

Looking at Plot #4, we can see where Larsson rode less than optimal. Compared to the optimized power pacing in blue, Larsson went too hard at the start, did not put out enough power during the middle portion of the race, and actually had a sprint left in him at the end when he should have used that power much earlier to maintain a higher sustained speed. It is not to an athlete’s benefit to be able to sprint at the end of a time trial. Instead, Larsson should have put out more sustained power beforehand so that he is near exhaustion about 250 metres away from the finish line, relying on his kinetic energy and remaining power to carry him through.

This analysis can be further confirmed by looking at Plot #5 where we graph the power on a time basis instead of by a position basis that we did in Plot #4. Plot #5 shows that at the first two corners of the course (indicated by the deep troughs in power), Larsson was actually ahead in time compared to what the optimized power produced. However, Larsson lost this time advantage when he put out too little power in the middle of the race as can be seen by the difference between the power troughs at corner 3 (about 180 seconds on Plot #5).

Plot #5 compares the speed data from Larsson’s power meter to the speed obtained by using the optimized power from Optimal Cycling. It shows that Larsson went much too hard at the start of the race. His highest speed obtained during the race was during the first 500 metres only to meet the first corner where he had to slow down dramatically. To obtain the best time, it is generally not a good idea to spike up your speed but instead, you should try and keep it steady unless the course makes you slow down or speed up.

From about 600 metres to 3000 metres, we see that Larsson did not go fast enough since the speed plot from our optimized power is above Larsson’s own. This correlates with the power plots which give the same observation. From about 3500 metres onwards, we see Larsson’s speed go up because he is sprinting with the power he held back, which is not the best overall strategy.