UNDERSTANDING PAX FACTORS
(borrowed from http://www.azsolo.com/)


The PAX factors are derived from comparisons of the best drivers in the different open SCCA classes in a selected series of events. Thus a PAX factor is a sort of handicap with a PAX of 1.000 being for the fastest class of cars (A-Modified). Let's look at an example.


RAW TIMES FOR SAME DRIVER IN CARS IN 3 CLASSES

To understand PAX factors consider what would happen if one of the best drivers in the country practiced in three different cars, which were prepared to the limit of the rules for their class and then competed in each car on the same course. That driver would achieve the raw times in an AM, SS, and HS car shown at the right.


PAX FACTOR CALCULATION FOR CARS IN 3 CLASSES

Therefore the fastest car is the AM car and the slowest is the HS car. If we were to divide the raw time for the fastest car (AM) by the raw time for each car we would get the PAX Factor relative to the fastest car as shown to the right.


PAX TIME CALCULATION FOR CARS IN 3 CLASSES

If we now MULTIPLY the raw time for each car by the PAX Factor we will get the PAX Time for each car as shown to the right.


PAX TIMES FOR 3 DRIVERS IN 3 CARS

So, the PAX Time for each car is the same, which is what we would expect if the same driver drove them with ample practice in each car. But, what would happen if a different driver now drove each car? The process is the same...MULTIPLY the Raw Time received by each entrant by the PAX Factor for the car's class. Suppose the results were as shown to the right.


As you can see in this example the car actually winning the class would be the HS car because the driver turned in Raw Time which gave a PAX Time better than the others. The driver of the SS and AM cars did not extract the same potential as predicted by the PAX Factors which says they should have received faster Raw Times.

Since it is not possible to get the same driver trained in the best prepared cars in every class, PAX Factors are derived from analyzing the results of top drivers in the best prepared cars in several selected events across the country to try and determine the predicted performance of fully prepared cars in a given class.


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