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On September 13 2020 10:24 Ben... wrote:I did the scatterplots for fun also (y being games played, x is MMR). They're kinda neat. For this first one, I did log scale for y axis since otherwise it's incredibly cramped. I set it ridiculously wide for this because I noticed something (spoilered because this one's kinda biggish download-wise): + Show Spoiler +Those vertical lines are interesting. A smaller scatterplot reveals the three most prominent lines on the right are around 4000, 4400, and approximately 4700-4800 MMR, which I'm guessing are cutoffs for various tiers of leagues, probably Master or Diamond 1. A bunch of accounts seem to cluster around the MMR cutoff for league tiers: + Show Spoiler +Cool stuff. edit: Yes, that giant space on the left is populated. There's someone with ~200 MMR. double edit: Cleaned up the plots a smidge and made the y axis more reasonable. I had to do it manually since 10e2 was too small and 10e3 left a bunch of empty space so I went with a range of 10 to 3500 games. When I went from 3000 to 3500 I saw one data point added so somebody has to have played a lot of SC2 this season.
That vertical line is super cool. Think those cutoffs are for d2-d1, d1-m3, and m3-m2 respectively, that's a cool feature to see.
I guess it's too dense to see the differences between the races, it would be super cool to see something like "terrans gain MMR fastest, relative to # games played, since their macro is most intuitive/similar to other games" but that's probably too hard to quantify.
Thanks again for keeping us posted dude ur awesome <3
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On September 13 2020 10:24 Ben... wrote:I did the scatterplots for fun also (y being games played, x is MMR). They're kinda neat. For this first one, I did log scale for y axis since otherwise it's incredibly cramped. I set it ridiculously wide for this because I noticed something (spoilered because this one's kinda biggish download-wise): + Show Spoiler +Those vertical lines are interesting. A smaller scatterplot reveals the three most prominent lines on the right are around 4000, 4400, and approximately 4700-4800 MMR, which I'm guessing are cutoffs for various tiers of leagues, probably Master or Diamond 1. A bunch of accounts seem to cluster around the MMR cutoff for league tiers: + Show Spoiler +Cool stuff. edit: Yes, that giant space on the left is populated. There's someone with ~200 MMR. double edit: Cleaned up the plots a smidge and made the y axis more reasonable. I had to do it manually since 10e2 was too small and 10e3 left a bunch of empty space so I went with a range of 10 to 3500 games. When I went from 3000 to 3500 I saw one data point added so somebody has to have played a lot of SC2 this season.
This is far less meaningfull than I expected 
Is it possible to plötzlich lifetime games against mmr as well?
Also thx for putting together the actually meaningfull Graph with the Log scale. That one actually Shows, how good the Balance is in Leagues with the most Balance whiners.
I m allways pleased to see them proved wrong, as for 99.99% of your average SC2 game your own mistakes are the only thing to blaue for your loss.
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On September 13 2020 14:09 dbRic1203 wrote:
Also thx for putting together the actually meaningfull Graph with the Log scale. That one actually Shows, how good the Balance is in Leagues with the most Balance whiners.
I m allways pleased to see them proved wrong, as for 99.99% of your average SC2 game your own mistakes are the only thing to blaue for your loss.
Well, one thing you can be sure with is that the whiners will never accept actual facts like the races being very well balanced and that there's no big swings at all. They also won't ever accept the logically simplest explanation that Zerg just plays differently than other races, so they are less represented in ranks below 3k MM, which was also supported by the first graph, showing the curve of Zergs is rising much slower from 2k -> 3k than that of Protoss/Terran.
Also it kinda baffles me to see people really trying to deduct anything from those charts related to balance, in a range of MMR, where people have problems with Scouting, constantly building workers+army, Supply blocks, unit compositions, unit control, macro in general and most importantly: dealing with cheese/all-ins (scouting + defending), because in those ranges, cheese simply reigns supreme and literally everyone can cheese every game and rank up very fast to like 3500 MMR within days.
Another thing would be insta-leaves: some people lose a few games to cheese from one race and then decide to just leave every game they get matched against that race again. Many people have problems holding 12pool/ling-bane allins, so they get traumatized and just leave every game they get matched vs Zerg (instead of learning how to deal with it). This also gets shown clearly that the MMRs converge very quickly around ~4k MMR, where people mostly have learned dealing with cheese/all-ins.
In the end, the whiners will also never accept that every game they lose, is because of their own errors, that's why we will still hear "ZERG OP!" in every thread, in evrey game.
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[QUOTE]On September 13 2020 18:56 suriel- wrote:
[QUOTE]On September 13 2020 14:09 dbRic1203 wrote:
because in those ranges, cheese simply reigns supreme and literally everyone can cheese every game and rank up very fast to like 3500 MMR within days.[/QUOTE]
What??? Dude dunno where you get your information from, but you have no idea what you talk about. This is only your stupid assumption and you construct the whole argument on this, which fails because the assumption fails. You have no data to back this up and your limited narrow view is bias af on this regard.
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On September 13 2020 22:14 xsnac wrote:
What??? Dude dunno where you get your information from, but you have no idea what you talk about. This is only your stupid assumption and you construct the whole argument on this, which fails because the assumption fails. You have no data to back this up and your limited narrow view is bias af on this regard.
I mean, i've played in those ranges of MMR and like every second game was cheese. You can also create a new account and go Proxy/12pool every game and you will have a huge success, ranking up to 3500 MMR fast, that's what i did when i was fed up with people cheesing me, so i cheesed back and literally had like ~70% winrate in every matchup at one point.
Didn't even think one can be "biased" in that regard? Isn't it generally known that the 3k MMR ranks are just filled with cheese and general random plays of people not understanding the game?
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only 8000 players who played at least 10 games ?
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On September 13 2020 23:09 suriel- wrote:Show nested quote +On September 13 2020 22:14 xsnac wrote:
What??? Dude dunno where you get your information from, but you have no idea what you talk about. This is only your stupid assumption and you construct the whole argument on this, which fails because the assumption fails. You have no data to back this up and your limited narrow view is bias af on this regard. I mean, i've played in those ranges of MMR and like every second game was cheese. You can also create a new account and go Proxy/12pool every game and you will have a huge success, ranking up to 3500 MMR fast, that's what i did when i was fed up with people cheesing me, so i cheesed back and literally had like ~70% winrate in every matchup at one point. Didn't even think one can be "biased" in that regard? Isn't it generally known that the 3k MMR ranks are just filled with cheese and general random plays of people not understanding the game?
If you are a 4,5k player, you can get to 3,5k easily with absolutely anything, just like pros like BeastyQT troll low master players with thor drops etc.
Remember that cheese execution and follow-up will also be at plat/lowdia level, so it is not for granted that cheesing is that much easier than playing standard at different levels.
RL example, I just offraced toss and went proxy 4gate in 5 pvzs, got 2-3. It was nothing spectacular.
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The mental gynastics being done here by Zerg players is just too funny. Wasn't it ''just Serral''? Why is Zerg dominating from bronze to pro play then?
This reminds me of 2011 when there were 20 Terrans in Code S and people said ''Its because Flash and Boxer play Terran, its only natural that BW bonjwas inspired the best players to pick Terran.
This graph might not reflect balance, it probably reflects what is common knowledge: Zerg is the easiest race to learn and be good with.
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On September 13 2020 23:11 GSTL wrote:
only 8000 players who played at least 10 games ?
No. ~8000 was the number for accounts ranked when using random with 10+ games.
I did a quick check, and there are 68055 unique entries in the dataset I have for NA for names with more than 10 games (this would only count accounts with ranked using multiple races once). There's probably some duplicates that just happened to have the same name but are unrelated that got removed so the actual number is likely higher. This data isn't from Blizzard so I don't have unique IDs, which would make this more precise. Also keep in mind this ranked only so there are likely thousands more accounts that only play unranked, archon mode, co-op, etc.. The takeaway from this can be that a good chunk of people still play SC2. Across all regions, we're probably looking at into six figures of active accounts, which is pretty good for a 10 year old game.
On September 13 2020 14:09 dbRic1203 wrote:Show nested quote +On September 13 2020 10:24 Ben... wrote:I did the scatterplots for fun also (y being games played, x is MMR). They're kinda neat. For this first one, I did log scale for y axis since otherwise it's incredibly cramped. I set it ridiculously wide for this because I noticed something (spoilered because this one's kinda biggish download-wise): + Show Spoiler +Those vertical lines are interesting. A smaller scatterplot reveals the three most prominent lines on the right are around 4000, 4400, and approximately 4700-4800 MMR, which I'm guessing are cutoffs for various tiers of leagues, probably Master or Diamond 1. A bunch of accounts seem to cluster around the MMR cutoff for league tiers: + Show Spoiler +Cool stuff. edit: Yes, that giant space on the left is populated. There's someone with ~200 MMR. double edit: Cleaned up the plots a smidge and made the y axis more reasonable. I had to do it manually since 10e2 was too small and 10e3 left a bunch of empty space so I went with a range of 10 to 3500 games. When I went from 3000 to 3500 I saw one data point added so somebody has to have played a lot of SC2 this season. This is far less meaningfull than I expected Is it possible to plötzlich lifetime games against mmr as well?
I can't do that with the dataset I have unfortunately. The site in which the data is from gets their data from Battlenet for current season only.
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On September 14 2020 01:30 Morbidius wrote:
The mental gynastics being done here by Zerg players is just too funny. Wasn't it ''just Serral''? Why is Zerg dominating from bronze to pro play then?
This reminds me of 2011 when there were 20 Terrans in Code S and people said ''Its because Flash and Boxer play Terran, its only natural that BW bonjwas inspired the best players to pick Terran.
This graph might not reflect balance, it probably reflects what is common knowledge: Zerg is the easiest race to learn and be good with.
And they won't quote statements like these that pretty clearly show what's happening. I'm sure a lot of zerg players had quite a bit of pride tied up in making it to diamond league. It must be difficult to discover that diamond zergs are as commonplace as silver protoss and silver terran players (Literally. By the numbers. Globally.)
But there's really no sense in trying to force a horse to drink water.
Can't complain about the balance in master's league though, so that's good 
On September 13 2020 10:22 Alejandrisha wrote:Show nested quote +On September 13 2020 09:42 Ben... wrote:On September 13 2020 09:31 yubo56 wrote:On September 13 2020 09:18 Ben... wrote:I saw OP filtered out people who played fewer than 10 games (I didn't in my previous post) so I did also (it's trivial since the website provides number of games played as a column) just to see the difference. It's not really all that different but for consistency's sake here's the data: The graph looks basically identical: ![[image loading]](https://i.imgur.com/oeRCStA.png) data is quite close too: Number of accounts with 10+ games by race:
protoss:31247
terran: 33855
zerg: 27118
random:8203
mean:
protoss:2848.8236310685825
terran: 2778.8631516762666
zerg: 2985.8191975809427
random:2872.1861514080215
median:
protoss:2759.0
terran: 2674.0
zerg: 2920.0
random:2818.0
overall mean MMR: 2864.1406052398356
population median MMR: 2793.0
Mean number of games played so far this season:
factoring in accounts with fewer than 10 games played: 55.53022382348439
ignoring accounts with fewer than 10 games played: 90.96791571651913
Hi, I asked for a log y axis plot but OP doesn't seem to have responded; since you seem to be checking this topic, would you be able to post one with a log y axis as well? Would be able to show the long tail at higher/lower MMR much better I definitely agree that using mean/median/mode to draw balance conclusions is extremely dubious, but it should be fun to theorize nonetheless Does this work? It's for accounts with more than 10 games. ![[image loading]](https://i.imgur.com/wpVd6Rm.png) All I did was add ".set(yscale='log')". Nothing fancy. Yeah I don't think anything meaningful can actually be drawn from this data. I just like tinkering. edit: On September 13 2020 09:31 yubo56 wrote:
How are y'all scraping the data, did you just download all of the pages and parse the HTML? Pretty much. I just used the requests library to download each page (you can use the offset GET parameter they use for pagination to hop between pages), then used BeautifulSoup to parse the HTML and then cleaned stuff up a bit before chucking it in CSVs. Nothing too advanced. thank you, this is a much better graph. still don't think we can draw real conclusion from it. but this is better in that we can actually see the differences
Also.. Log transformation on the y axis? That just collapses differences in the middle of the graph and exaggerates differences at the ends of the graphs. There's no basis for applying a log transformation to population data in that way. It's just dishonest.
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On September 14 2020 01:30 Morbidius wrote:
The mental gynastics being done here by Zerg players is just too funny. Wasn't it ''just Serral''? Why is Zerg dominating from bronze to pro play then?
This reminds me of 2011 when there were 20 Terrans in Code S and people said ''Its because Flash and Boxer play Terran, its only natural that BW bonjwas inspired the best players to pick Terran.
This graph might not reflect balance, it probably reflects what is common knowledge: Zerg is the easiest race to learn and be good with.
At top pro level, TvZ actually seems to be in a very good spot right now. The Clem vs Reynor series was a nice and very recent example.
After the last round of nerfs and a reasonable map-pool, Zergs actually have to make plays to win now, and can't win of the back of only defending harassment, macro and creep anymore. Good strategic and technical zerg play is also still rewarded.
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On September 14 2020 01:30 Morbidius wrote:
The mental gynastics being done here by Zerg players is just too funny. Wasn't it ''just Serral''? Why is Zerg dominating from bronze to pro play then?
This reminds me of 2011 when there were 20 Terrans in Code S and people said ''Its because Flash and Boxer play Terran, its only natural that BW bonjwas inspired the best players to pick Terran.
This graph might not reflect balance, it probably reflects what is common knowledge: Zerg is the easiest race to learn and be good with.
Yet 45% of GM is protoss, while only 25% of GM is zerg.
https://www.rankedftw.com/stats/races/1v1/#v=2&r=-2&l=-2
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On September 14 2020 02:02 ThunderJunk wrote:
Also.. Log transformation on the y axis? That just collapses differences in the middle of the graph and exaggerates differences at the ends of the graphs. There's no basis for applying a log transformation to population data in that way. It's just dishonest.
Hey, I'm the one who requested it. The reason one would do that isn't to make assessments of means / modes, or areas under the curve any more, but just to understand the shape of the tails of the distribution across races. It's possibly dishonest put the plot out there and say "this is the MMR distribution," since a lot of people don't know how to read log scales, but it's pretty common practice to do this when you're not interested in the peak of the distribution but the tail and scaling of the tail.
For instance, any curve with a peak looks plausibly like a normal distribution, but if you log scale it you immediately can tell whether it's quadratic and over what range it's normal. The question I was trying to answer was whether the tails of the distributions look any different between the three races, since we can already see the peaks very well, and a log plot is a great way to see both tails on the same plot. I think it's a useful tool if you know what you're trying to read
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On September 14 2020 06:55 yubo56 wrote:Show nested quote +On September 14 2020 02:02 ThunderJunk wrote:
Also.. Log transformation on the y axis? That just collapses differences in the middle of the graph and exaggerates differences at the ends of the graphs. There's no basis for applying a log transformation to population data in that way. It's just dishonest. Hey, I'm the one who requested it. The reason one would do that isn't to make assessments of means / modes, or areas under the curve any more, but just to understand the shape of the tails of the distribution across races. It's possibly dishonest put the plot out there and say "this is the MMR distribution," since a lot of people don't know how to read log scales, but it's pretty common practice to do this when you're not interested in the peak of the distribution but the tail and scaling of the tail. For instance, any curve with a peak looks plausibly like a normal distribution, but if you log scale it you immediately can tell whether it's quadratic and over what range it's normal. The question I was trying to answer was whether the tails of the distributions look any different between the three races, since we can already see the peaks very well, and a log plot is a great way to see both tails on the same plot. I think it's a useful tool if you know what you're trying to read
Fair enough
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On September 13 2020 23:22 Slydie wrote:Show nested quote +On September 13 2020 23:09 suriel- wrote:On September 13 2020 22:14 xsnac wrote:
What??? Dude dunno where you get your information from, but you have no idea what you talk about. This is only your stupid assumption and you construct the whole argument on this, which fails because the assumption fails. You have no data to back this up and your limited narrow view is bias af on this regard. I mean, i've played in those ranges of MMR and like every second game was cheese. You can also create a new account and go Proxy/12pool every game and you will have a huge success, ranking up to 3500 MMR fast, that's what i did when i was fed up with people cheesing me, so i cheesed back and literally had like ~70% winrate in every matchup at one point. Didn't even think one can be "biased" in that regard? Isn't it generally known that the 3k MMR ranks are just filled with cheese and general random plays of people not understanding the game? If you are a 4,5k player, you can get to 3,5k easily with absolutely anything, just like pros like BeastyQT troll low master players with thor drops etc. Remember that cheese execution and follow-up will also be at plat/lowdia level, so it is not for granted that cheesing is that much easier than playing standard at different levels. RL example, I just offraced toss and went proxy 4gate in 5 pvzs, got 2-3. It was nothing spectacular.
That was also a RL example of mine: when i started playing the game in Fall of 2019, i got placed into Plat3. Playing games there, i got cheesed very much, so i just started to cheese back.
I'm currently a ~3900-4100k player, but it doesn't take great effort to cheese someone. You can name 20 other former GMs that smurf their way into masters, it doesn't change the fact that cheese is easier to execute than it is to defend:
- you need to scout cheese
- after having scouted, you need to know what kind of cheese it is
- after knowing what kind of cheese it is, you need to know how to react to it
- after knowing how to react to it, you need to know how to handle it (micro)
things needed to know for executing cheese:
- learn the build order, which only covers the first ~3 minutes most of the time
- learn to handle it through repetition (micro, multiple games)
Cheese is so strong, that even highest pros have success with it (see Scarlett throwing out Rogue of GSL, or the countless ProxyRax games, or Stats/Trap losing to a few lings in GSL, because not having a proper wall)
Your anecdotal sample size of 5 games is cute, but it doesn't change the fact that doing this a few times more, you'll have a high win rate. I mean, people literally get GM with just cannon rushing (printf, DemusZero for example).Likewise, it's very trivial to go for a 12pool or a banebust every game and collect free wins. That's a RL example, because i did just that: 13/12 every game against Protoss and Zerg and i had about a ~70% win rate and got to 3.5k really fast.
And please, let's not shit outselves here: 3k MMR is basically garbage since people have huge other problems other than balance, like proper macro and 0 understanding of the game.
If you want a Pro to confirm how ridiculous it is to bring the "imbalance" argument into 3000 MMR range, check out some of Harstem's "Is it IMBA or do I suck" - series, there are even some "low masters" players sending in replays, but during the analysis, you can clearly see they still make Gold league mistakes. For example the "Spines are IMBA" one
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On September 14 2020 17:22 suriel- wrote:
Your anecdotal sample size of 5 games is cute, but it doesn't change the fact that doing this a few times more, you'll have a high win rate. I mean, people literally get GM with just cannon rushing (printf, DemusZero for example).Likewise, it's very trivial to go for a 12pool or a banebust every game and collect free wins. That's a RL example, because i did just that: 13/12 every game against Protoss and Zerg and i had about a ~70% win rate and got to 3.5k really fast.
This is true. I just got back in the game 2 months ago and I went up to 5k3 by just 1base allining all my games with WoL units.
Ladder shouldn’t be used to determine balance. Mid GM and under players are just not good enough, and high GMs don’t even ladder seriously. Objective Pro feedback and High level tournament results is the best data for balance imho.
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On September 13 2020 12:33 yubo56 wrote:Show nested quote +On September 13 2020 10:24 Ben... wrote:I did the scatterplots for fun also (y being games played, x is MMR). They're kinda neat. For this first one, I did log scale for y axis since otherwise it's incredibly cramped. I set it ridiculously wide for this because I noticed something (spoilered because this one's kinda biggish download-wise): + Show Spoiler +Those vertical lines are interesting. A smaller scatterplot reveals the three most prominent lines on the right are around 4000, 4400, and approximately 4700-4800 MMR, which I'm guessing are cutoffs for various tiers of leagues, probably Master or Diamond 1. A bunch of accounts seem to cluster around the MMR cutoff for league tiers: + Show Spoiler +Cool stuff. edit: Yes, that giant space on the left is populated. There's someone with ~200 MMR. double edit: Cleaned up the plots a smidge and made the y axis more reasonable. I had to do it manually since 10e2 was too small and 10e3 left a bunch of empty space so I went with a range of 10 to 3500 games. When I went from 3000 to 3500 I saw one data point added so somebody has to have played a lot of SC2 this season. That vertical line is super cool. Think those cutoffs are for d2-d1, d1-m3, and m3-m2 respectively, that's a cool feature to see. I guess it's too dense to see the differences between the races, it would be super cool to see something like "terrans gain MMR fastest, relative to # games played, since their macro is most intuitive/similar to other games" but that's probably too hard to quantify. Thanks again for keeping us posted dude ur awesome <3
Is there any correlation between amount played and mmr? this graph seems to indicate that no.
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On September 13 2020 00:22 yubo56 wrote:Show nested quote +On September 12 2020 22:47 Dangermousecatdog wrote:
By the way those numbers aren't the node either. That can only be shown from the actual data table. Like I said, the more I look at the graph, the more nonsensical it appears. I'll have to see the data myself, but if it's from that same link then what we have is just a bullshit graph. There is only 7 datapoints per race so how could he make such a graph to present the data? Wait, why does rankedftw only give 7 datapoints per race? https://www.rankedftw.com/ladder/lotv/1v1/mmr/?f=eu If you go here, there are 160239 datapoints for EU alone, it seems plausible that that OP generated the plot from rankedftw.com Edit: your argument seems to be that the graph doesn't represent the 7 leagues correctly. Yes, indeed, if you want the % of gold players, you should integrate the curve between min(gold MMR) to max(gold MMR), and you'd get the correct percentage. But that's just b/c the transformation between leagues and MMR isn't linear, which makes sense since they're based on percentages and you have long tails. In other words, the statement "most protoss players are gold" is wrong, but "most protoss players are in the range 2300-3100 MMR" is perfectly correct, one is based on a league PDF and the other is based on an MMR PDF.
Compare this graph and the ones posted by ben.... ...
...The difference is astounding. One looks like an artifact produced by low data points and smoothing with it's near poisson distribution which is not what whould be expected from what we know of MMR, which is why I say it looks like 7 data points or super smoothed out. The other look like a graph. i;ll be interested to see when EU looks like as produced by ben... .
As for " "2300-3100 MMR" is perfectly correct" you basically wrote that at least half the players are between silver and plat MMR.
No shit sherlock! Blizzard has consistently stated that Silver-Diamond are 20% each since WoL. You don't need to look at a graph to work out that any three leagues between Silver and Diamond will be at least 50% of a population. I could be blindfolded and shown any randon graph and I could say Silver- Plat MMR will be 60% of the population or Gold- Diamond MMR is 60% of the population. Because it's a fact irrelevant of whatever you think the graph may or may not be showing.
On September 14 2020 20:41 skdsk wrote:Show nested quote +On September 13 2020 12:33 yubo56 wrote:On September 13 2020 10:24 Ben... wrote:I did the scatterplots for fun also (y being games played, x is MMR). They're kinda neat. For this first one, I did log scale for y axis since otherwise it's incredibly cramped. I set it ridiculously wide for this because I noticed something (spoilered because this one's kinda biggish download-wise): + Show Spoiler +Those vertical lines are interesting. A smaller scatterplot reveals the three most prominent lines on the right are around 4000, 4400, and approximately 4700-4800 MMR, which I'm guessing are cutoffs for various tiers of leagues, probably Master or Diamond 1. A bunch of accounts seem to cluster around the MMR cutoff for league tiers: + Show Spoiler +Cool stuff. edit: Yes, that giant space on the left is populated. There's someone with ~200 MMR. double edit: Cleaned up the plots a smidge and made the y axis more reasonable. I had to do it manually since 10e2 was too small and 10e3 left a bunch of empty space so I went with a range of 10 to 3500 games. When I went from 3000 to 3500 I saw one data point added so somebody has to have played a lot of SC2 this season. That vertical line is super cool. Think those cutoffs are for d2-d1, d1-m3, and m3-m2 respectively, that's a cool feature to see. I guess it's too dense to see the differences between the races, it would be super cool to see something like "terrans gain MMR fastest, relative to # games played, since their macro is most intuitive/similar to other games" but that's probably too hard to quantify. Thanks again for keeping us posted dude ur awesome <3 Is there any correlation between amount played and mmr? this graph seems to indicate that no.
It only take into account of the one season. It doesn't have total games played. Looking at the scatter plot, playing 1 game a season to keep the rank is still a thing. Anecdotal experience has shown the fastest way to improve is to play lots of ladder games.
Logically, you can't physically improve MMR unless you play ladder. No matter what you think your real skill level is, your MMR is nonexistent till you ladder and MMR can only be increased by laddering. Has anyone ever seen a master player with less than a hundred games? A GM with less than a thousand games? The actual mean of games plays of those ranks would be vastly higher than that. I would expect there is a very strong correlation between laddering and MMR until the higher end.
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Mexico2170 Posts
I just want to comment on two things that have been bothering me for a while.
People at 3k understand the game. I'd go as far as saying most people in gold and silver have a base good understanding of the game. People that play StarCraft nowadays don't play it super casually. Most of the people I know in those levels are aware of tournaments, Build Orders, pros etc. There are other things that can impact MMR, things like the time you have available to play. You can watch GSL and read TL every day but if you can only play 1 game a day your MMR will improve more slowly. Also mechanical ability. Some people just have a lower skill ceiling than others, and might not be able to move their hands as fast , that's a fact. So how about we stop the snobery and stop discriminating lower leagues and feeling superior?
Second point: balance problems are real and they affect every league.
Sure, if you played better you could win more games. But you don't play better. Not yet. You improve over time.
If a unit, Build order or strategy is overpowered and an equally skilled openent uses it, you will lose games that you wouldn't have lost otherwise.
Yeah you can always improve and if you suddenly have 400 apm you could beat your opponent. And improving is something you can control, whereas balance is something out of your hands, so you should focus on getting better. But that doesn't mean balance doesn't affect players from every league.
There's also the fact that balance is not a constant. Some things that aren't very strong at one skill level can be slightly stronger at other MMR.
Even strategies have an impact. In parts of WOL and Host for example protoss had a good or even great winrate in PvZ, mainly due to cheeses and all ins. If you were a macro protoss? Though luck. Likewise other races. Muta ling might have a different winrate than roach Hydra. Mech has a different winrate than bio. So if you don't like a particular style or can't play it for some reason your winrate will vary.
To give a pro example, Mvp couldn't play bio anymore due to shoulder problems. If mech wasn't strong at that point in time he would do badly even if Terran as a whole was doing good.
Depending on how many people play different styles it could mask balance problems. For example maybe Terran has 40% winrate in lategame TvP but since they have a 60% winrate with early all ins the overall winrate looks "balanced".
Balance is much more nuanced than it appears and even overall winrates may be missleading.
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TL-DR: zerg is the easiest race
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EPT![[image loading]](https://i.imgur.com/kHr47aH.jpg)
![[image loading]](https://i.imgur.com/P7k89Wc.png)
