Analyzing speed data

While speed is a basic channel provided by all systems, and a channel to which many other channels are related, in isolation is does not provide much information for improvements. Part of the reason is that speed itself is not what is being optimized; lap times are what are important rather than speed, and more speed does not necessarily equate to a quicker lap time. Consider driving from New York to Indianapolis at 50 mph. If you drive straight there, you’ll get there quicker than someone driving at 75 mph but going by way of Detroit. Always remember that time is the variable to be minimized.

Two speed traces for the same rider

These speed traces for one rider show little difference, even though one lap is more than one second quicker than the other. Finding improvements from speed traces alone is a difficult task.

Another part of the reason speed on its own should not be heavily relied upon is that riders are remarkably consistent, and improvements in lap times can be realized from surprisingly small changes in speed. Consider the attached data of a rider at Thunderhill Raceway. Two laps are shown, with a lap time difference of more than one second between the two laps. Speed is consistent over almost the entire lap, with just a couple of areas with any noticeable difference. It’s clear that there is an improvement one lap to the other, but without other data it’s almost impossible to know the reasons behind the difference.

Two speed traces for two different riders

In contrast, the traces for two different riders on the same bike at the same track show significant differences, even though the lap times are just a half-second apart. Things to work on for both riders can be found in this graph.

That said, speed on its own can be a revealing channel if you have another rider’s data to compare it to. The second graph shows two riders at the same track on the same bike, with an almost identical lap time. In this case, there are some startling differences between the two riders even though the lap time is almost the same. Both riders could learn from this data, and this emphasizes one important aspect of data acquisition: Comparing data from different riders is the quickest way to find improvements, and the benefit is not only for the slower riders.

With no other rider’s data for comparison purposes, and no channels other than speed, there are still options available. GPS-based systems provide a host of additional, useful channels that can be accessed. And sector times can be used to break down laps and display how changes in speed relate to time improvements.


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