Hi La Mer

The simplest way to calculate variants is to start by creating a set of average winning times for every distance(segments)/Class combination at a track. Then after each meeting is finished, take the actual winning time for every race on the card, and divide it by the average winning time for that distance(segments)/Class. Then I take the average of those numbers. That gives you the variant for the day. It should be a number very close to 1.000. If the number is below 1.000, it indicates the track was slower than average that day. If greater than 1.000, the track was fast. Then, you take the finish time(sectional) for every Horse that ran that day, and you multiply that finish time(sectional) by the daily variant.
Once this is applied to each runners LTD performances his average will have a lower standard deviation than an average of regular times without a Track Variant, if you've done everything correctly.

To have good results with the variant-adjusted times, you must be a bit careful with your distance(sectional)/Class averages, and your database maintenance. It's important to create a good set of standard averages. If you ever change your standard average winning times, you must re-process your entire database and recalculate the daily variants and re-apply the new variants to every single past performance line in your database. Many people mess things up by changing their standard averages and not reprocessing all of their historic data.
Testing your procedure for creating variant-adjusted times is very easy. Pick out about 20 Horses at random from your database, each of which has at least 20 past performance lines. Calculate the standard deviation of each Horses raw times, and of their adjusted times. If a strong majority of your 20 Horses (say 15 of them) have a lower standard deviation on the adjusted times than the raw times, then you are probably doing things okay. If 10 or less of the Horses have a smaller standard deviation on the variant-adjusted times, you probably have a problem.
This is one procedure where it's not possible to "over-fit" the back data. The better you minimize the standard deviation, the better your handicapping results will be.
If your thinking of using any times other then winners times, i have completed numerous studies on placgetters etc The standard deviation for Class X winners was .151951 seconds. The standard deviation for Class X second-place finishers was .157107 seconds, which is about .005 seconds greater than for the winners. So this analysis confirms for me that putting place finishers into a variant adjustment will increase the resulting runners standard deviations versus using only winners and thats not our goal.

The other issue of track degradation does have some effect but it can work in both directions, The above variant as it been described is quite good at removing daily variations in the racing surface. But if you want it to be even better, you could apply a secondary variant. Take the average of the averages, and then adjust each race for the difference between the average for that race number (over a long time period) and the average of the variants. That would give you a daily variant that was adjusted for track degradation as well.