X-Act
np: Biffy Clyro - Shock Shock
The old algorithm to generate the OU list was used to create the current OU tier in early January, but I feel that the algorithm has a few shortcomings. These are the following:
1) It relies on the amount of times each Pokemon WAS used previously only. That means that the OU list is obsolete practically as soon as it is posted.
2) Its 75% cut-off point is not only arbitrary, but also lacks meaning. A more meaningful cut-off point would improve things.
Hence I set out to try to overcome these shortcomings in time for the tier list update due for the 1st of April.
To address point 1), I used a form of linear extrapolation to predict how the OU list would look like in the seventh month given the amount of percentage usage each Pokemon had in the previous six months. The recently added Wobbuffet and Deoxys-S would have only information from the previous 2 months and the previous 3 months respectively, and hence predicting their future usage is less accurate.
To address point 2), instead of "listing the Pokemon within the first 75% of the cumulative frequency distribution" (which lacks concrete meaning), I list the Pokemon having a high probability of featuring in a team from the predicted list generated above, which threshold we can agree upon. Yes, this threshold will still be arbitrary, but at least the phrase "probability of a Pokemon featuring in a team" is much more understandable than "a Pokemon is within the first 75% of the cumulative frequency distribution", and hence our familiarity with the term provides us with a better opportunity of finding a good threshold.
Okay, so here's the new algorithm:
1) Take the weighted usage lists of the previous six months and convert them into percentage weighted usages.
2) For each Pokemon, predict what percentage usage it will have in the next month.
3) Convert each predicted percentage usage into the percentage probability of how much likely each Pokemon will feature in a team.
4) Those Pokemon that have more than x% probability of featuring into a team make it into the OU list.
I'll leave out the function that does the prediction in step 2) for the time being. I'll just say that I've been experimenting with various methods of prediction, and finally I settled to one which is both good and simple. Here's a graph of what the predicted values of Garchomp, Gengar, Blissey, Gyarados and Tyranitar are (this only uses the previous 5 months instead of 6):
To find the probability that a Pokemon will feature in a team, I used the formula:
P = 6*p*(1-p)^5 where p is the predicted percentage usage.
When applied to Garchomp, this would be 21.1%, meaning that Garchomp is predicted to be featured in more than 1 out of every 5 teams (unless it's banned, lol).
To conclude, I'm asking two things:
1) Do you agree with this new way of considering OU?
2) What should be the minimum percentage probability of a Pokemon being featured in a team to allow it in OU? This new threshold can be used even for the old system if you don't agree with the new one.
1) It relies on the amount of times each Pokemon WAS used previously only. That means that the OU list is obsolete practically as soon as it is posted.
2) Its 75% cut-off point is not only arbitrary, but also lacks meaning. A more meaningful cut-off point would improve things.
Hence I set out to try to overcome these shortcomings in time for the tier list update due for the 1st of April.
To address point 1), I used a form of linear extrapolation to predict how the OU list would look like in the seventh month given the amount of percentage usage each Pokemon had in the previous six months. The recently added Wobbuffet and Deoxys-S would have only information from the previous 2 months and the previous 3 months respectively, and hence predicting their future usage is less accurate.
To address point 2), instead of "listing the Pokemon within the first 75% of the cumulative frequency distribution" (which lacks concrete meaning), I list the Pokemon having a high probability of featuring in a team from the predicted list generated above, which threshold we can agree upon. Yes, this threshold will still be arbitrary, but at least the phrase "probability of a Pokemon featuring in a team" is much more understandable than "a Pokemon is within the first 75% of the cumulative frequency distribution", and hence our familiarity with the term provides us with a better opportunity of finding a good threshold.
Okay, so here's the new algorithm:
1) Take the weighted usage lists of the previous six months and convert them into percentage weighted usages.
2) For each Pokemon, predict what percentage usage it will have in the next month.
3) Convert each predicted percentage usage into the percentage probability of how much likely each Pokemon will feature in a team.
4) Those Pokemon that have more than x% probability of featuring into a team make it into the OU list.
I'll leave out the function that does the prediction in step 2) for the time being. I'll just say that I've been experimenting with various methods of prediction, and finally I settled to one which is both good and simple. Here's a graph of what the predicted values of Garchomp, Gengar, Blissey, Gyarados and Tyranitar are (this only uses the previous 5 months instead of 6):
To find the probability that a Pokemon will feature in a team, I used the formula:
P = 6*p*(1-p)^5 where p is the predicted percentage usage.
When applied to Garchomp, this would be 21.1%, meaning that Garchomp is predicted to be featured in more than 1 out of every 5 teams (unless it's banned, lol).
To conclude, I'm asking two things:
1) Do you agree with this new way of considering OU?
2) What should be the minimum percentage probability of a Pokemon being featured in a team to allow it in OU? This new threshold can be used even for the old system if you don't agree with the new one.