Hey everyone, I think it is time for a "how to use overbuff" thread

Pretty please don’t turn this thread into an argument about current stats

First things first, Overbuff is a site which walks over peoples public profiles, and gathers data from them, which it aggregates, and displays.

When forumers talk about overbuff, they USUALLY mean the heroes screen on it.

It is at Hero Statistics - Overbuff - Overwatch 2 Statistics

Useful points about the data it gets.

  • It gets data from more than just the people who are signed up.
  • It gets ENOUGH data, and you can see that because the data doesn’t bounce around a lot, which you would expect if the sample was too small.
  • It can’t see private accounts, but, there is no reason to believe that private accounts are biased in a particular direction.
  • It gets the same data you see on your own stats page, and is subject to the same limitations of the data on that page - if Blizzard messes up, then Overbuff will mess up. If Blizzard doesn’t show enough data, then Overbuff will just have to work with what they can get. (See Mei’s damage/g stat)

Overview

At the top of the dashboard, you can select over how long you want to aggregate the data. Which platform it is for, if it is QP or comp, and a role filter (which you should ignore as it very out of date)

Under that, there is which rank you are filtering for. All of them, or some particular rank.

Under it, is the tabs - which people tend to not notice. But there is 3 more tabs than overview - 2 of which is useful. (Medals isn’t)

Stats on the overview tab

Pick rate - It is what it says on the box, how much a hero is being picked.

  • it is pick rate by slot, you need to multiply it by 6, to see the pick rate per side.
  • 16.666… is the max pick rate possible (in theory, but like, sometimes it shows higher, no I don’t know why…). It means the hero is picked every game, on both teams.
  • ISN’T weighted by number of heroes in a role. So, Tanks / Supports will have inflated pick rates compared to DPS, just because of less choices to be had there.
  • Pick rates have to be seen in context!!! A hero may only be heavily picked because it is countering another heavily picked hero for instance. A particular stand out is Mercy mains have a history of being crazy about their hero, and will pick Mercy totally regardless of anything. (This is what killed hero bans, since, when Mercy was banned, they just didn’t play for the week) - You can thank them later for killing it.
  • Context aside, it is a reasonable proxy for how strong a hero is. People pick what works at their rank, and “it is only because they are popular” heroes, tend to be not popular when they are weak. It is funny how that works.

Win rate - How likely a hero will win in a game, subject to a large number of caveats.

  • Win rate is influenced by SR, because the games player base is set out on a bell curve, low ranked players TEND to play against people higher ranked than they are on average, and the reverse is true. So, you need to compare it to the base line of that rank.
  • Even within a rank, that same bias comes into play to a less of a degree.
  • Hero which are swapped to, to counter, have a lower win rate, JUST because they tend to be picked when you are already losing.
  • Win rate is weighted by how long the hero was played in the match. This means heroes which are played on defensive more than attack, tend to have over inflated win rates. After all, if they do well, defense lasts a long time, and has a higher weighting. If an attacking hero does well, the attack phase is MUCH shorter, so they have the reverse effect, artificially pushing their win rate down.
  • Heroes which have a lot of mirroring tend to push the hero towards the middle of the rank. Since for every win there is a loss. (but middle of the RANK, rather than towards 50%, because the win is still more likely to go to the higher SR person) (see Moth Mercy for a VERY good demo of this)
  • Heroes which are one tricked a lot, ALSO get pushed towards rank average, the players are typically stable in their rank, so, run the rank average. This means the win rate is MOSTLY made up of people who don’t run the hero all the time. They will be winning on one hero, and losing on another.

The last point is a VERY interesting one, since, it means that their win rate is heavy biased towards “how easy is a hero to get value from for people who play more than one hero” - they are represented in the win rate WAY WAY more than the one tricks. The more someone one tricks, the less they are represented in the win rate.

An Example of biases in the data on this screen

McCree.

  • He is highly picked as a counter, so, his high pick rate in ranks where Ball / Tracer are played shouldn’t be a surprise, since he counters them. So, his high pick rate doesn’t by itself mean he is Over Powered.
  • He is highly picked as a counter, so, his low win rate shouldn’t be a surprise, since often he will be swapped to, it doesn’t mean he is Under Powered.

Sym

  • She is typically played for a very short time on attack (tele to win, or swap), and for a long time on defense, so, her win rate is artificially high.
    etc etc.
  • It is easy for a non Sym main to try the tele attack thing, so there is an easy way for a non main to get value, so her win rate would push up even more. It doesn’t mean the same person would do well, if they had to run her all the time.

Stats on the primary tab

This gives things like Elims per game, etc. objective kills, whatever.

  • Mei’s stat damage/g stat is bugged - it is 10x out.

But like, the tab… just isn’t hugely useful. The Eliminations Tab what you are looking for.

Stats on the Eliminations tab

Ok, first things first, what is an Elim? If you do damage to a target, and they die within a few seconds after that, you are credited with an Elim.

  • This means that small damage to a lot of people TEND to get credited with a lot of elims, even though it likely didn’t do much towards that person actually being killed.
  • The reverse is also true, Heroes which are pretty heavily focused towards killing a single target TEND to have lower elims, because, hey, they have very little trash damage.

E:D - Mostly a measurement of spam - an abjectly AWFUL measure of power.

  • Heroes which are very assassin based have awful E:D, since they don’t tend to have any kind of spam damage to push it up, unlike other heroes. See Widow and Doomfist for good examples of this.
  • Heroes which don’t die much, or have good escapes tend to also have good E:D.
  • Heroes which can get back to the fight QUICKLY tend to have bad E:D.

Like, don’t use this in any kind of argument, it is just a bad measurement of… well everything.

Elims / G similarly useless by it’s self- it measures spam more than anything. But, between this and E:D you can measure deaths per game, which is interesting.

Solo Kills - More useful than it first looks. Multiply it by Elims/G to get solo kills by game.

Final Blows - This is the king of stats on this page. It measures how deadly a hero is.

  • Multiply it by Elims/G to get number of final blows.
  • It is VERY good indicator of effective damage.
  • It does get influenced by “clean up heroes” a little. Who clean up after the fight is over, so you have to remember that.

Ok, that should be a pretty good primer on overbuff.

It is a pretty good data source, has more than enough sample size (don’t make me have the sample size talk to you all again).

Just remember it’s limitations, and everyone should be all good.

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Actually I don’t think this is true. If I recall correctly, Hog made it to 18% pick rate back in mid 2020

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They should sticky this, maybe people would then start looking up stats before crying “This hero is OP nerf it now!” threads
Nah who am I kidding it wouldn’t change anything if they did

Still, good explanation regardless

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It is 100/6 :slight_smile: Like, you can’t get over this, unless you get more than one hog on a team.

I wonder if Echo could push it up though, I don’t know how her ult is allocated towards pick rate.

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Great thread. Nice work.

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That was caused by people swapping who played hog within the same game I believe
So say tank 1 played hog first half, then dva and ball for the other half
Then tank 2 played rein and zarya first half and only hog for the next half
Then Overbuff counted those two players as having played Roadhog within the same game

Regardless, anything above 13% is ridiculously high, I’d argue a healthy meta sees no character over 10%

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It is scaled by time played in the game. If you are hog for 1/2 a game, then you have hog gets only 1/2 a game allocated towards pick rate.

It isn’t touched the hero, it is weighed by how much they are played. Blizzards stats DO get messed up sometimes though (See Mei’s damage/g) so, it wouldn’t surprise me if they messed something up.

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I wish everyone would read this and understand.

But I doubt they will.

Good work though

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I thought Overbuff only used the “games played” stat for determining pickrate, in which case it’s awarded to the hero you spent the most time on in the match, which is why you’ll have different win percentages if you compare Overbuff to Overwatch’s built in stat screen, but I haven’t really looked into it so you’re probably right

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can we get this pinned guys?

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Well, a lot of it is from talking to other people. It isn’t all my own work as far as working out different effects.

Like, I hadn’t put together all of the crazyness which was win rates by myself, there is a lot which influences it, and some I didn’t get into (because, hey, small effects, and complex to explain).

Mostly, I wanted people to understand that, there is context, and the stats do get pushed around by a bunch of effects. It doesn’t make them useless, far from it, but it does mean you how to keep them in mind.

Overbuff is… well, a bit opaque in how it generates it’s stats. I’m working off when I ran my own scraper, and what processing I had to do to make it look like overbuffs data, but, again, we were sampling different populations, so… it is a bit of guesswork on my part.

For my sins, I am trying to have a writeup on all of the stats in the upcoming OWL viewer which will make the processing on how they are generated painfully clear so people will be replicate the work.

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You can still see a bit of data from the Super Hog days. Here’s a pic of him reaching 20% in GM.

Hog-over-16-pc-pickrate

Super Hog’s also interesting for the line that regularly gets put about: “A character that’s picked every game will have a 50% win rate”. You’ll notice that Hog has times where he’s >15% and also >50% win rate.

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Huh, that is just weird. I may have to change my post :slight_smile:

Yeah he is being picked in GM, there but, like, the GM’s are playing a lot of NOT GMs so, you would expect him to have average GM win rate, NOT 50% win rate. (they are different! :))

But a 20% pick rate looks like broken Blizzard stats.

I’m going to update the post.

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Amen! Outside of glitches and bugs, Overbuff is an excellent data source, and every single time we’ve gotten concrete statistics from Blizzard they have nearly perfectly tracked what Overbuff said.

Awesome post!

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I think too many people forget the difference between sample statistics and population statistics.

It is basically impossible to properly gather the entire set of stats from a population. Blizzard probably can with the player data, but outside of them releasing that data we never will. So, we rely on these sample stats.

Overbuff is the sample data of people with public profiles. Is it indicative of 100% of the playerbase? Hell no, a lot of people have private profiles and many of them are one tricks who skew play rates of some heroes, even if only slightly.

Its hard to know the best sample size for OW since the population size is not public data to my knowledge. But Overbuff almost certainly gets data from a minimum of 6 digit figures (100,000 is by far the lowest estimate I could make, this is super conservative btw). That is easily a big enough sample size to make broad claims about patterns in the community even without the full data set.

I think more often than not, people pull out the ‘Overbuff isnt the whole population!’ as a last resort because they dont wanna admit their argument is wrong (we’re all guilty of abusing stats, dont feel bad). Im not saying this is the only reason people make this argument, but it seems to be the most common reason. For example, Ana used to have spent a huge amount of time as the most picked hero period (not just support), but when people brought this up to suggest Ana nerfs it was shot down because OB wasnt reliable enough.

TLDR: People who say Overuff isnt reliable because not everyone has a public profile dont understand that all statistics use only samples of the whole pop

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Players who set their profile to public tend to be proud of their stats or have stats that are viewed as being acceptable by the community or they would face prejudice if they had it on public

You say that, but there is a massive amount of people with public accounts at all ranks.

It VERY much will slant it towards the higher ranks, but, since the stats are broken up by rank anyway, and the samples sizes are big enough… I don’t think it is a thing we have to worry about.

It WILL mean lower ranks may have less people public, but, that is a sample size thing rather than a stats thing.

now… SMURFS may not run with public profiles, and they may not be counted as much, but that is a good thing for balance discussions.

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Although OB’s raw data is useful I find the more applied information on Overpicker more useful. I just put in the rank, map, our team comp and (ideally, if I know it) the enemy team comp and it tells me who I should play.

Although in practice the answer is always Rein unless the other tank is playing Rein already, then I should play Zarya. (Also there’s the 1% chance the enemy team comp is one that recommends I pick a different MT).

It’s sad that you post this in a “how to use overbuff” thread since you can’t know if these are true.

These two bullet points are not facts necessarily, and as such you don’t know if your sample is truly random so I take all Overbuff stats with a huge grain of salt.

You just say “there is no reason to believe private accounts are biased in a particular direction”

This is bad data science

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Yes, because resampling with too smaller sample size would give the data a lot of jitter, which it doesn’t have.

There isn’t, if you think there IS reason to believe that private accounts are biased in a certain direction, now is the time to explain why, and in which direction.

Because currently, there is no reason to think that the unsampled data is materally different from the sampled data.

You think a post explaining the biases of each stat in great detail is made by a person who doesn’t understand data science?

LITERALLY it is a post about biases in stats.

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