2018 NCR PAX Index
What is PAX?
The PAX (Professional Auto-X) Index has been used by SCCA® and other clubs for years. It is a handicapping system that attempts to account for performance differences between car classes allowing the drivers' performances to be compared. A PAX factor is assigned to each class; the faster the class, the higher the factor. The fastest cars have a PAX factor of 1.000; other PAX factors are a percentage based on performance potential relative to the fastest cars. Each driver's actual time around the course is multiplied by their car's PAX factor to calculate their PAX time. This PAX time is also called their indexed time or factored time. PAX times can then be compared across classes.
It is impossible to come up with a PAX index that is perfect just as it is impossible to come up with a class system that is perfect. Everyone believes that someone else has a softer(i.e. easier) PAX factor.
What is an Indexed Class?
An indexed class is a class that combines several classes into one class and uses factored times to compare the results. We do not get enough entries to populate the individual classes so we need to combine multiple base classes to offer competetive classes. By forming indexed classes. the factored (aka indexed) times provide a more equitable comparison of the results than the raw times.
2018 NCR PAX Index
The NCR PAX Index is based on the PAX/RTP Index developed by Rick Ruth that is based on hundreds of autocross events nationwide. The NCR Porsche Street Category is separated into base classes with Porsches that map to the same SCCA® class. The PAX factors for those SCCA® classes are used for the NCR base classes. The exception is Street Class 9 which contains the street Porsches that are excluded from the SCCA® Street Category. For class 9 we average the PAX factors for SCCA® Super Street (SS) and SCCA® Super Street Prepared class (SSP) classes.
|NCR Class||SCCA Class||PAX Factor|
For the NCR Porsche Race Category and for all non-Porsche classes, we use SCCA® classes as base classes so we use factors.