I have established class adjusted standard times for every Australian race track at every distance based on data going back to 1996.

The best approach I have found is to take a trimmed average...and then compare this against the median as a sanity check.

Take the dataset for each distance, take the fastest and slowest 10% of records away and average the rest. Then compare this against the median. If they are close to each other this implies your data is normally distributed which in practical terms it should be if looking across a large enough sample size.

Hope this helps.