"What if I raced?" Calculate your estimated race time

If you completed one race ("Race#1"), what might your time have been if you raced at another comparable race, "Race#2"? Think of it this way -- if both races were taking place simultaneously, and you were plucked from one course and dropped into the other, it's an estimate of how you would fare in "Race2" based on how you raced in "Race1".

To estimate a time, enter the average finishing time and standard deviation from "Race1" and the average and standard deviation from "Race2" -- these can be found on the results page. Also enter your finishing time in the "Race1" table. Press the button in the table in "Race2" to calculate an estimated time for "Race2" -- if you were to race like you raced in "Race1".

The estimated time makes use of a statistical approach using standardized scores known as z-scores. Standardized scores are important because (1) there are problems with simply comparing raw race times and (2) there are also problems comparing overall finishing places from race to race. A more complete explanation for how standardized scores solves problems with raw times can be found on this site at Taking z time to compare race results. The calculations used here takes your race time in "Race1" and converts it to a z-score. Using the average and standard deviation values of "Race2", your z-score of race1 is converted to a time of hours, minutes, and seconds for "Race2".

There are some key points to keep in mind.

1. The athletes in "Race1" and "Race2" should be comparable.
   For example, we can compare two Ironman races to each other because both races comprise essentially the same type of people -- a top 10 finisher in one race is similar to a top 10 finisher in the other; a middle of the packer in one is similar to a middle of the packer in the other, the back of the pack athlete in one is similar to the back-of-the-pack athlete in the other. People are similar in terms of their training approaches, their ability, their equipment, etc. Comparing a 5k race or a sprint tri to an IM is less meaningful because the athletes in those fields are not comparable. (IM Hawaii is a unique race, because many of those entrants qualified, and comparing the field of one IM to IM Hawaii may not be comparable).
2. Because it's assumed that the athletes are comparable, race courses can be very different.
   Differences between courses (hot/cold, hilly/flat, rainy/dry) are accounted for by the use of standardized scores (z-scores). Course conditions affect all athletes. For example, if it's unusually hot, and the heat slows down athletes in the race by about 20mins, that 20 minute difference is taken into account by the use of z-scores (and this hints at why it's not really valid to simply compare raw times of races). If there are people that especially thrive in heat/cold, hills/flats, etc. they are offset by the others that are adversely affected by heat/cold, hills/flats, etc. Thus, the average and std.deviation are not significantly affected if the number of athletes racing represents a large enough sample size.
3. Your fitness level is the same relative to the field.
   Your estimated time for "Race2" assumes the same level of fitness that you were at for "Race1". In fact, if you had a good/bad day in "Race1", it assumes you would have had an equivalent good/bad day for "Race2". Think of it this way -- if both races were taking place simultaneously, and you were plucked from one course and dropped into the other, it's an estimate of how you would fare in "Race2" based on how you raced in "Race1".
4. It's a mathematical/statistical model meant to be informative and perhaps entertaining. No guarantees about accuracy should be implied -- and it's no substitute for the experience of actually racing.