In regard to numbers getting nearer to 50% as time goes on, if we look back to overwatch, heroes can hit 59%. Like I said, that’s including matches where both teams use the same hero. After accounting for that, I wouldn’t doubt it if we had top Pokémon hit 65%. Even Pokémon hitting 60% is significant. We have actual data to off of here. Just like top players in Pokémon, top players in overwatch use the same hero everytime. Even moreso than smogon players using the same team. Yet we still have noticable differences in win%.Not to put words into Antar 's mouth here, but I suspect he is working based on the assumption that people use the same teams for extended periods of time, in which case what he's saying should be pretty much true - there'd be a small positive in the wr as you first used the team, but then you'd just be ranked higher and therefore playing stronger players, and the wr would slowly go back towards 50%, according to Antar's maths.
I think you're also right about there being a noticable difference in win rate with better pokemon, though, but that this doesn't mean that this statistic would give you what you want to know. I'll explain in detail; alternatively there's a tl;dr below if you only care about the conclusion.
Antar is working under the assumption that, after playing enough games on the ladder for you to get to the correct ranking, that every game you play is against someone of equal level to you. However, the ladder doesn't work exactly like that. There's a range of rankings that you can play against at any one time - maybe anyone between 50 points above or below you, though obviously it's a little more complex than this as you can play someone significantly further away if you have to wait for someone to show up, etc.. I could give a more detailed description if I could be bothered to read zarel's code, but +-50 points of you will be a good enough estimate for this.
How players are ranked should be a gaussian distribution, or "bell curve", which looks something like this:
View attachment 154360
(I'm aware that Elo assumes a modified gaussian distribution with an extended tail, but as far as I'm aware, the actual ranks people have follow a gaussian, at least well enough for our purposes here.)
As you can see, if you're perfectly average, if you pick a random player +-50 ranking points of you, you're just as likely to get someone better than you than worse. But if you're a better player, towards the right of the curve, then you're far more likely to face an opponent worse than you than one who's better, because there aren't all that many who are better than you, and there's a whole lot who are worse (even within just those 50 points). If you're playing people worse than you, you can expect to have a win ratio of >50%. Similarly, those towards the bottom of the ladder would see a lower win rate. I don't know if this is the same in overwatch or not, but at the same time I'll bet you £1000 that it is.
tl;dr I don't think a win ratio for pokemon would display how good they are, but rather how popular they are among good players relative to among worse players. And it would do a less accurate job of this than higher-weighted usage stats.
Another issue would be that this rating would be highly manipulable. With other ranking systems, there are built-in mechanisms to stop them being abused, which basically boil down to "if you manipulate the ladder into only pairing you with bad players, when you eventually get bad enough hax that you lose, you'll lose a vast number of rating points", which stop this from being worthwhile. (For the record, I've seen people manipulate the ladder in this way, and stop bothering once they lost an extremely unfortunate game to someone 300 points below them. The system works.)
If you wanted a pokemon to have a higher win-rate, this is not the case. You could just make new alts, ladder to 10-0 with the pokemon, rinse and repeat. Even if you set a minimum ranking to count, players who wanted the pokemon banned could just /forfeit when they saw it, and not use the pokemon themselves. Each of these would be far more effective than, say, using a pokemon you want removed from the meta below, although I haven't calculated whether it would be effective enough to actually bother with either.
I was hoping to finish this reply with "and here's how to get the statistic you want", but I honestly can't think of a way to get an accurate winrate statistic for a pokemon, without somehow keeping track of what teams pokemon people are using, as well as what they previously used. That would be an option, perhaps, but it would be a harder thing to compute than standard usage stats for sure, and would need a fair amount of programming just for it as well. That's not to say there isn't a way I haven't thought of yet, though.
Personally, I think the best metric would be adjusted win% for 1825 players in OU, and 1750 everywhere else. But that’s not really relevant to the discussion.