Daytona International Speedway / GTLM / Race

The Sorted Lap Time Chart arranges and plots each car's N-th fastest lap times from left to right ...

• Each car's 1st fastest lap time is plotted at x = 1,
• Their 2nd fastest lap time at x = 2,
• etc.

Since the vertical axis is ordered with greater lap times towards the top, every car's plot will extend from the lower left and rise towards the upper right. This sorted visualization allows us to see and compare the capabilities of various the competitors in the session.

Plots at the far left are a good indicator of the ideal capabilities of the car/driver combination during the session.

Plots at the far right right are most likely slow laps due to yellow flag periods.

The lower envelope indicates the car with the N-th fastest lap time. The more often a given car is at or near the lower envelope, the greater its ability to drive fast laps. The Yellow Band percentage allows you to easily see how much slower various cars are, relative to the lower envelope.

The Pace Gap Chart allows you to both see each car's pace as well as the gaps between cars.

• Imagine a virtual car that travels at the adjustable Pace lap time. This line chart plots the cumulative gap between each car and this imaginary car. Williams Martini Racing's has titled their static variation of this chart with the rather vague name Race History.
• You can study if the pace of a car is faster or slower than the Pace by seeing if its successive points are above or below the horizontal (representing the reference pace).
• Initially the reference pace is automatically set to the winning car's average lap time, including yellow flag laps, pit stops, etc. This results in the winning car's final plot ending at y = 0.
• If you set the Pace to your average green lap time, you will should see the plots flatten. The plots drop when you are off pace, usually due to traffic, tire degradation, yellow flag laps, pit stops, etc. You may need to Scroll downwards ↓ to see later stints.
• Besides comparing each car's pace, you can see if the gaps between cars are closing or widening. Notice that while the actual gap to the virtual car (at y = 0) is probably generally not terribly significant, this interactive visualization allows us to simultaneously study pace as a horizontal series of points and gap to competitors.