- FT frequency = FTM / FGA
However, there are severe problems with the equation – in fact so severe that the FT factor should be split into two.
One of the problems with Oliver’s equation is that negative occurrences may cause FT frequency to rise. I.e. if the shooter misses a FG shot where he gets fouled it affects the FT frequency more positively than if he gets fouled and makes the shot. That is because a missed foul FG shot will not add to the number of FG attempts, as a made foul FG shot does, and because a missed foul FG shot provides the offense with two FTA, whereas a made foul FGS will only provide one.
Example: Say you have made one 2-point FG shot where there has been no foul. Then you take a second one, and this time there is a foul. If you make the FG shot, you earn a bonus FT. Make it, and the equation becomes:
- FT Frequency = 1 / 2 = 0.5
Should you instead miss your second FG shot and make one of the subsequent FT attempts, the equation is:
- FT frequency = 1 / 1 = 1.0.
So, now the FT frequency is higher even though your FT% is lower and even though you have drawn the same number of fouls as in the previous case.
The other problem with Oliver’s FT frequency equation is practical. A team’s FT frequency will not tell how they have done regarding the two basic aspects of free throws: earning FTA and making them. Hence they must have separate indicators.
This is hardly surprising since in 2007 Kubatko, Oliver, Pelton and Rosenbaum wrote: “This would imply Five Factors, but this one term [FT frequency] tends to capture the most important elements of both.” As shown above, their second claim was incorrect.
To measure a team’s ability to hit FT’s there is no better tool than FT%.
To measure a team’s ability to earn FT’s I suggest this equation:
- FT frequency = FT Sets / Plays
As shown above, neither FTA nor FTM should be the dividend since getting fouled and missing the FG shot would lead to more FTA and FTM than getting fouled and making the FG shot. I.e. a less positive outcome would have a more positive effect on the FT frequency.
So, the only options left for the dividend are the number of number defensive fouls or the number of FT sets. The context here is Four Factors where the independent variables cover endings of plays. Since a defensive foul will not necessarily be the ending of play but a FT set will be, it makes sense to choose the number of FT sets as the dividend. Also, FT sets are more directly linked to FT frequency than the total number of defensive fouls is. In a previous blog I already turned Four Factors into Five Factors.
This splitting the FT frequency into two factors turns Five Factors into Six Factors. And this is where it ends. Hence the Four Factors turned into Six Factors are:
- Clean effective field goal percentage
- Foul effective field goal percentage
- Turnover percentage
- Offensive rebounding percentage
- Free throw frequency
- Free throw percentage