About the 1200 Indices

Leaderboard Information
General Information

TrialVault computes a number of 1200 indices for JRTCA-registered terriers. Each index is designed to balance the average performance of a terrier with the number of trials that the terrier attends. High-scoring terriers may either perform very well at a few trials or attend a lot of trials, but ideally both.

To achieve this balance, TrialVault computes two scores internally for each terrier:

  1. A performance score (perf) that reflects the average skill of the terrier across trials as based on placement in classes.
  2. An experience score (XP) that reflects the number of trials that the terrier has attended recently. The impact that trial attendance has to a terrier's XP diminishes with time since the end of the trial. This means terriers lose XP with time if they do not attend any new trials.
TrialVault averages these two numbers to determine a terrier's index score.

Implementation Details

For each dog, the index is computed as follows:

  1. Assign points to the dog's placements in each class: Champion/Reserve: 12/10, Best/Reserve: 12/10, 1st: 8, 2nd: 7, 3rd: 6, 4th: 5, 5th: 4, 6th: 3, participation: 1
  2. Determine the dog's single largest (V1200) or top two largest (R1200, C1200, E1200, N1200, A1200) scores within each relevant division category for each event.
  3. To get the dog's points score (points): Add the points received for each division.
  4. To get the dog's average performance score (perf): Multiply points by 100, divide by the average number of divisions of the type considered offered by trials, divide by the number of trials attended, and round to the nearest whole number.
  5. To get the memory factor (mem) for each event in which the dog participated: Calculate 0.999^days where days is the number of days elapsed since the end of the trial.
  6. To get the experience score (XP): Multiply each mem by 100, add all the results, and take the minimum of this number and 1200 (1200 is the maximum value of the performance score, so we use it as the maximum here as well).
  7. Finally, to get the index: round the weighted average 0.7*perf + 0.3*XP to the nearest whole number.