Starting this up early cause there's a lot of talk about it in the current process.
So sweepiness currently doesn't fit our understanding of Pokemon. Currently its nearly flat at high speed-factors (sf), whereas in reality we know that going from outrunning Stratagem to outrunning Dragapult is a huge increase in overall power. For example, with t=2.25 and 145 SpA, going from 129 to 144 speed increases BSR by 2. Not 20, 2. This needs to be fixed. Speed factor is also for all mons, not all relevant mons, which has causes some issues.
Let me make some assumptions:
1) Sweepiness should depend on your ability to get KOs, and your ability to outrun mons. That is, it should be some function of SpA and speed.
2) Each additional mon you outrun is more valuable than the last. This is not strictly true, but its approximately true and that's all we need.
3) There should be some user-tunable parameter that we can adjust to account for trying to use the same formula for both Obliteryx and Chuggalong.
How then can we model speed.
The current formula is (sf+t) / (1-sf +t) where t is a "turns parameter", intended to be the average number of turns before 'speed matters' for our role. In practice this has been set between about 1.75 and 3 for all the CAPs I've ever seen. sf is just the fraction of pokemon in the meta we outrun, ignoring evs and any speed modifiers. To turn this into words. Speed only matters on the turn a KO happens.
One approach would be to keep sf, as its a decent "probability of outrunning a randomly selected mon" and just use it differently. I've proposed "probability of outrunning at least k of 6 mons on an opponent's team". I like that one as it exhibits the exponential increase in sweepiness as sf => 1 for high k, but is it ideal?
I'd appreciate thoughts from anyone with experience in both mons and any kind of mathematical modelling, as well as practical approaches to modifying all parts of the formula. I know there was an internal approach to modifying BSR, but its been years hence making this post.
Currently I'm not trying to propose any changes, but more just looking for the functional forms we may want to explore, as well as any challenges to the assumptions I've made.
Edit: Keep in mind that any formula we eventually use should be easy to add into an excel sheet.
So sweepiness currently doesn't fit our understanding of Pokemon. Currently its nearly flat at high speed-factors (sf), whereas in reality we know that going from outrunning Stratagem to outrunning Dragapult is a huge increase in overall power. For example, with t=2.25 and 145 SpA, going from 129 to 144 speed increases BSR by 2. Not 20, 2. This needs to be fixed. Speed factor is also for all mons, not all relevant mons, which has causes some issues.
Let me make some assumptions:
1) Sweepiness should depend on your ability to get KOs, and your ability to outrun mons. That is, it should be some function of SpA and speed.
2) Each additional mon you outrun is more valuable than the last. This is not strictly true, but its approximately true and that's all we need.
3) There should be some user-tunable parameter that we can adjust to account for trying to use the same formula for both Obliteryx and Chuggalong.
How then can we model speed.
The current formula is (sf+t) / (1-sf +t) where t is a "turns parameter", intended to be the average number of turns before 'speed matters' for our role. In practice this has been set between about 1.75 and 3 for all the CAPs I've ever seen. sf is just the fraction of pokemon in the meta we outrun, ignoring evs and any speed modifiers. To turn this into words. Speed only matters on the turn a KO happens.
One approach would be to keep sf, as its a decent "probability of outrunning a randomly selected mon" and just use it differently. I've proposed "probability of outrunning at least k of 6 mons on an opponent's team". I like that one as it exhibits the exponential increase in sweepiness as sf => 1 for high k, but is it ideal?
I'd appreciate thoughts from anyone with experience in both mons and any kind of mathematical modelling, as well as practical approaches to modifying all parts of the formula. I know there was an internal approach to modifying BSR, but its been years hence making this post.
Currently I'm not trying to propose any changes, but more just looking for the functional forms we may want to explore, as well as any challenges to the assumptions I've made.
Edit: Keep in mind that any formula we eventually use should be easy to add into an excel sheet.
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