• Check out the relaunch of our general collection, with classic designs and new ones by our very own Pissog!

How Should We Be Counting for Usage Stats?

So right now, we calculate usage stats the following way:
  • count up the occurrences of each species on each player's team, weighting using our weighting function
  • empty slots get counted as well
  • duplicate mons (or multiple empty slots) get multiply counted (so a team with one Magikarp and five empty slots will produce 5x the count of empty slots as Magikarp counts)
  • At the end, you divide by the total and multiply by 6
I don't like this, and here's why: it's not how we assume usage stats behave with regards to tiering policy. Our tiering policy (3.41% cutoff) is based on the premise that if a Pokemon's usage number is below 3.41%, then if you were to play 20 battles in a row, there'd be less than a 50% chance of encountering that Pokemon.

As an example, imagine you're playing a tier without species clause. 1 in 100 teams consists of six Magikarp. Otherwise, no one uses Magikarp. Using the above system, 'Karp's total usage would be 6% (OU threshold), even though the odds of encountering a Magikarp in 20 battles is significantly less than 1 in 2.

So what I propose is this:
  • count the number of teams on which each Pokemon appears, weighted by our weighting function
  • divide by the sum of the weights of all teams
For tiers with species clause (read: all the usage-based tiers), I *think* the two methods are equivalent, so maybe this is a distinction without a difference. But I still think it's important to be clear about this.
 
I should also explain how this translates to other metrics:
  • Leads: how many teams lead off with X? For Doubles/Triples we do not double-count
  • Moveset stats: how many X run Y? Here, you DO count every member of a team. This means usage stats will not be directly computable from moveset stats, as they are now
  • Teammate stats: how many teams that run X also run Y? No double-counting, but there's also a special case: how many teams with X run a second X?
What I also like about this schema is that it generalizes in some cool ways: how many teams with Snorlax run a Dark-type? How many teams with a Stealth Rocker user run a second Stealth Rocker?
 
Back
Top