How about this? If I normalize the average interval times to a 0-1 scale, they will look sorta like percentages. I can then use them todiscountthe accuracy percentages resulting in a combination rating on a 0-1 scale.

In the example below, I have the data for 8 keys, numbered 1-8. In Col C, I have assigned each row a variable name for reference. Cols E-L contain the data for the keys. Cols M-N contain the minimum and maximum values in each row.

Row 5 contains the accuracy ratings (A). They range from .80 to .99.

Row 6 contains the average keystroke interval timings. They range from 200 ms to 900 ms. Row 7 contains the equivalent typing speed in WPM (words per minute), which range from 13 WPM to 60 WPM.

In Row 8, subtract the minimum interval timing (200) lowering the range to (0,700).

In Row 9, I divide by the (new) maximum interval timing (700) changing the range to (0,1).

In Row 10, I divide that in half because I don't want the interval timings to discount the accuracy ratings by more than 50%.

In Row 11, I subtract from 1 to reverse the range (1,0). Lower intervals are better.

And in Row 12, I discount the accuracy ratings by the scaled keystroke interval timings. This changes them from a range of (0.80,0.99) to (0>40,0.95).

Cell K11 contains the maximum discount factor (0.50), which divides the accuracy rating in K5 in half from 0.80 to 0.40. L11 contains the minimum (1.00) discount factor (1.00), which leaves the accuracy rating in L5 (0.95) intact.

I would appreciate any comments or critiques on this approach.