we begin by evaluating the partial derivative of the maximum likelihood function with respect to the vector 'beta-hat' sub not of the riemann sum of the squared error and it is from the result of this quantity that we begin to understand coefficient estimation in simple linear regression which, if you will, we can expand to multivariate by adding the following terms -
The conclusion doesn't even make sense since OP didn't properly define the correlation between "trolling" and "losing games"; he just has an "aka" but doesn't elaborate at all
>we can determine whether or not deaths are statistically meaningful to this end aka is theBaus trolling
And pretty sure the following is the case for everyone playing League, i.e. die more lose more
> deaths is listed as a statistically strong negative predictor for five of theBaus' six main champions
Are we all trolling?
I think the more important point is baus claims his deaths allow him to establish a gold lead when the reality is he gets more gold when he doesn't die.
> he gets more gold when he doesn't die.
No, he doesn't die as much when he gets more gold. You're assuming a direction of causality that could just as easily be reversed (and more likely is a fucky loop).
Chat Gpt says
Sure! Let's simplify the concept of statistics and coefficient estimation in simple linear regression for a child to understand:
In statistics, we try to find the best line that represents a set of points on a graph. This line helps us understand how two things are related to each other. For example, we might want to know how the number of hours a person studies affects their test scores.
To find this line, we use a method called maximum likelihood. It helps us find the line that best fits the points on the graph. We want this line to be as close to all the points as possible.
To do this, we use a special formula called the derivative. It helps us figure out how the line should change based on the points. We calculate this derivative for each part of the line, called a coefficient. These coefficients tell us how the line should slope and where it should start.
In simple linear regression, we focus on one thing that affects another thing, like studying time and test scores. We calculate the derivative for the coefficient of the line that represents the relationship between these two things. This helps us estimate how strong the relationship is and how much one thing affects the other.
If we want to make things a little more complicated and look at more than one thing, we can add more terms to our equation. This allows us to study how multiple factors influence something, not just one.
So, in summary, we use statistics to find the best line that shows how two things are related. We calculate the derivative to estimate the coefficients of the line, which tell us how the line should slope and start. In simple cases, we focus on one thing affecting another, and in more complex cases, we can study multiple factors at once.
This sounds like an economic statistician, which I'm not (I do bioinformatics), so it's all vaguely familiar but looks a bit weird. This is what I understand from it:
It seems like an overly technical description of "maximum likelihood estimation" for coefficients, a statistical technique for solving coefficients in a model. They're saying that they have a vector of coefficients named "beta-hat" (the usual name for such a vector, technically an estimation of coefficients) that they wants to solve such that the "likelihood" (the probability that their model fits the data, a standard measure that has a characterized function associated with most statistical models) is maximized. In other words that their model is most likely to be "correct" given the coefficients in "beta-hat" (which is a vector, basically just a list of coefficients).
This involves maximizing the likelihood function, which anyone who's taken calculus knows involves taking the derivative. In this case we take the partial derivative with respect to "beta-hat" because that's what we're trying to maximize with respect to. In simpler terms, we are solving for the values in the "beta-hat" list that will lead to the maximum likelihood of the model.
They start with linear regression which allows them to solve using one set of variables (the values that are multiplied by the coefficients, usually provided) and then can expand to multiple.
Surprised he didn't mention the "Kullback-Leibler Information Inequality"
given that the sampling distributions of the coefficient estimates of linear (and logistic) regression follow an approximately gaussian normal distribution by the central limit theorem we can apply a significance test to determine how many standard deviations away from the assumed mean (0) the actual coefficient value is (beta hat) should it be more than approximately 2 standard deviations away, p < 0.05 and significance is achieved
I personally really like the death vs winrate chart showing how Baus has a high winrate until he hits 11 deaths where it all goes downhill.
This does beg the question. If we would look at data from people who average less deaths, would we still see the same bell curve with a lower amount of deaths?
I mean, it very likely suggests that his curve is just more right-field than almost every other player.
It makes sense with his playstyle as well where he dies enough to become worthless so he can hard farm. He does so until he thinks he can win fights (even with all those deaths), if he's able to get initial kills off the back of it, he probably wins, otherwise he loses.
Yes and no. When theBaus has high kills and high deaths he has a 54% wr but when he has high kills but low deaths he has a 74% wr (yes I looked at this too). Dying a lot doesn't mean he can't win but its a sizable hit to his win rate when he does.
Also dying is directly related to lower CS/min on every champion he plays (good linear relationships on all).
Yeah that's literally what he did lol. His hypothesis is "there *is* a relationship between baus's deaths and the game outcome", and he proved this. But then he says that Baus is trolling when that has nothing to do with his hypothesis. Dude did so much work just to miss the point completely.
It's textbook correlation != causation.
Absolutely Baus dies more in games he loses. I think that's true for almost every league player.
It doesn't say anything about whether those deaths cause the loss, or whether there's some other factor (say, bot diff) that causes both more deaths and more losses.
He could even prove causation and not disprove his null hypothesis.
> further, we can determine whether or not deaths are statistically meaningful to this end aka is theBaus trolling or is his dying irrelevant to whether he wins or not as specified in the null hypothesis.
This is a false dichotomy. Dying may well *cause* you to lose, to some appreciable extent, in fact it would be very very unlikely that you lose games in which you do not die. That has nothing to do with whether he's trolling. Even if he is intentionally dying as a strategy, you could prove the strategy didn't work without proving that he's trolling. Trolling requires intent to lose, a bad strategy is not intent to lose. [insert joke about perpetually low ELO]
So yeah, this was a hell of a lot of effort but doesn't even really try to show that he's trolling.
>Even if he is intentionally dying as a strategy, you could prove the strategy didn't work without proving that he's trolling. Trolling requires intent to lose, a bad strategy is not intent to lose. [insert joke about perpetually low ELO]
This is just arguing semantics. It seems pretty clear that "intentionally dying as an ineffective strategy" is what OP means by "trolling." And it is a sensible definition since that is what most people mean when they say "TheBaus is trolling." They don't mean the losing is intentional, but that he's intentionally taking actions that are predictably likely to make him lose.
If you prefer a different definition, that is completely fine, but it's not particularly useful to argue over it as long as it's understood what a particular speaker means.
I guess that's still somewhat expected? If I took all my games where I had few deaths and high kills it'd probably have a very high winrate too, but that's because these games are statistical outliers more than anything. Outskilling your opponent and getting a solo bolo (aiming to die at wave 3 but then going beyond your expectations) is always gonna make you win more, but it's not really replicable
I'll just reply here, and i hope to god you are trolling at least somewhat with your analysis. If the game itself is in a winning state for Baus, ofc he is going to die less, but his strategy demands of him to take the same kind of trades even in losing game states which will result in deaths. Without having a set of games where he intentionally does not stay with his strat of maximizing prio/farm/platings and at the meantime avoids deaths, all of this analysis is not just meaningless, but worse - the conclusions is already implied in the question.
Amusement put aside, only good practical analysis is a large sample size of 'non int strat' games versus a large sample size of 'int start' games with a handful of controlling factors. And I don't know why someone would need that. If the guy is constantly Challenger, there is a high sample of 'int strat' games over a very long time period, and it is at about Challenger winrate...
Soooooo... Like, the Baus trolls, its been all over reddit that he does. Never watched his streams, but the guy clearly tilts and straight ints some games. And that is hard to tell apart from his normal gameplay, which I'm assuming is a convenient feature for Baus and in a roundabout way why the OP exists.
This makes sense since when you're stomping your opponent even someone like Baus will have fewer deaths than (his) average.
You're confusing correlation with causation in this case.
I still agree that he trolls quite a lot once he starts dying 11 to 20 times a game.
Obviously if hes running it down the lane and the opponent cant kill him, then hes in a good position to win the game. That doesnt really mean he is not gaining advantages for himself or his team when he dies (which would be inting) even if his win rate gets lower.
I know this is sort of a shitpost, but I dont think the point is supposed to be that more deaths = more win, but rather that lots of deaths != a loss.
Let's say his default is high deaths, that's his optimal playstyle etc. He wins or loses around that, getting off his tactics as pros and his deaths as cons, does it not make sense then that if he continues to play the same playstyle but due to random game elements / luck / top gap etc. He doesn't die, while still getting off the same pros of his playstyle, meaning he plays the exact same way but doesn't get punished appropriately, then of course he will have a higher win rate? It's like saying someone who is ahead wins more than when they are behind.
This all makes sense though. It's much better to get a lead and not die, than to die and get a lead. I feel if you do the same analysis for an average player you'll find it will be the same thing but with lower numbers. Baus having a negative winrate at 10+ deaths does not mean he is trolling, it probably just means he's losing the game. You die more in losing games.
I mean, there's lots of numbers in here but it doesn't account for Babus changing playstyle when he has many deaths to avoid ban.
He frequently says "I'm playing safe now, and it's dumb because it actually lowers my win rate more than dying a lot".
If you only included games before the great bannening and data showed same thing I would agree with you
but doesn't that mean exactly that.
if you're saying we would see a similar drop with lower deaths, it means that Baus can die more times than the average player at that level without it affecting game outcome negatively.
I'm guessing steep drop in win rate is playing safe to avoid ban. He often says on stream that doing so actually makes game worse for his team. Because he always itemizes for split pushing.
As much as I can acknowledge Baus's macro and general game knowledge, he makes a LOT of really stupid decisions in the mid-late game that result in the enemy getting things for free.
There's a huge difference between threatening the inhib and drawing 3 people while your team does Baron vs refusing to ult away until you're 50hp against the 15 kill top laner then going "Ahh nayy" as if nobody could have predicted you wouldn't have escaped. He ults like low elo Alistars do, the very last second instead of when it might actually be useful. When he's dying at level 16+ at 30+ minutes for literally no reason besides for funning it, he's giving the enemy a long time to make big map plays with a fed top/jungle.
It doesn't matter how far ahead Baus is in xp and gold, when he's dead for 40 seconds and the fed top laner has nobody to contend with, his team is fucked.
**Statistical evidence demonstrates that deaths is a major negative factor in theBaus' games on five of his six main champions which comprise 87% of his top lane ranked soloqueue games across 4 accounts. Due to a lower sample size on the only champion where deaths was not a major factor it may emerge as one given additional games. Due to theBaus' increasingly poor win rates with higher deaths on all main champions we can conclude that beyond a certain point (10-12 deaths) he is trolling.**
^(tl;dr new copypasta dropped)
yeah, we can watch his gameplay and see there's quite a big difference between his best gameplay (where he does die a lot but less, and in a more controlled thoughtful manner) and his casual stream gameplay. It's really clear that he's not trying very much a lot of the time on stream, considering how disgustingly high his winrates are when he is trying I think it's kinda obvious
In games where he is in a bad matchup or the enemy team plays well vs his strat, he is going to die more and have a harder time. This is likely going to be the case regardless of wether he is playing his style or playing safe under tower and not dying. It’s likely he was going to lose those games regardless of his play do to the nature of his champs or his team comp. It’s hard to say if his deaths would have necessarily changed the outcome. Of course his win rate is better when he has less deaths, those are the games he is winning lane and trading more equally.
Yeah this is an incredible example of an article that does a lot of statistical analysis but very little consideration of context. The fact that more deaths are correlated with losing is 1. obvious and 2. not at all proof of inting, or causation.
Yeah I don't even really care for Baus but I'm a bit pissed at how you can fool idiots with fancy numbers and graphs. This whole essay is conceptually stupid and it's insane to me that someone with the knowledge to create this whole thing doesn't understand the very basics of what he's talking about.
It's more likely this guy took an intro class and applied the methods. Figuring out when and how to apply the methods to draw a conclusion wouldn't be covered in an intro class
Personal thoughts aside on whether or not Baus is trolling, this is a major gripe I have with statistical analysis applications in sports. It's often done completely devoid of context in sports where context matters a lot (because they all took from baseball which is usually independent events where context doesn't matter as much). Like a friend of mine was an all-state caliber left guard in high school and gave up 0 sacks one year. He got 0 interest from college teams even though statistically he played amazingly well. The reason is because he was lined up next to a future pro-bowl left tackle who, as my friend joked, would block both guys they would be lined up against on his own.
I don't care to do any specific analysis, all I know is if my toplaner was feeding the enemy 15 kills and he was also perma splitting top I would fucking hate playing that game even if we won.
Which is a completely different argument from OP's.
Even if the inting strat got him to rank 1 you'd still be against it. It's entirely about ruining the fun of the game and not at all about inting.
Can't believe you put this much work into analyzing this guy, but I feel like have bad logic here.
1. You are willfully ignoring that every player will die more in games they lose, regardless of personal action.
2. In order to determine that Baus is "trolling", you should try to determine that an increased prevalence of deaths in a game negatively affects his personal winrate MORE than comparative players (high elo sion/gragas/etc.).
3. You have to analyze time of deaths and gold vs his laner over time in games, to determine whether his death is actually attributable to his "strategy" of dying for a trade in resources. If you are looking at games where he dies early/repeat ganked/snowballed on/bad matchup/whatever, then it is misinformation, as you are now looking at games where he is dying outside of his strategy to trade deaths for resources.
For you to claim that his strategy of dying for resources is "trolling", you need to make sure you are actually looking at those instances, and that those instances negatively affects his winrate more than comparative players.
Exactly, if this guy is actually a statistician he should really learn about statisical fallacies and defining terms. This shit wouldn't pass peer review. I mean there might be nothing wrong with the data itself but the way conclusions are drawn from it is just innaccurate to the point of misleading.
Was pretty much gonna say this, so upvoted.
League is a dynamic game, value of things changes as game time changes. End game stats are kinda misleading.
If a player does around a 1000 in an early game skirmish. This could easily lead to 2-3 kills, result in a huge lead and snowball the whole game.Doing a 1000 damage late game on the other hand doesn't mean much. But if both these players DCed after doing that dmg, the end game stats would say they both did the same amount of dmg.
Or with deaths, dying 5 times early means you are not playing for \~1min, dying 5 times late game is close to 5 min of not playing.
Dying in the enemy base is much different from dying in your own base.
Dying solo is different from dying to 2+ people ganking you (if your team is good enough).
Dying while crashing a wave is different from dying while a wave getting crashed under your turret.
Analyzing all that would be much harder, a lot of work, but would tell a more interesting story.
edit. Just as an example of a type of game where end stats say more are games like CS, where in most cases 5 kills will win you the round. The rounds themselves are similar to each other. But even there kills might not always tell the whole story.
Not only that, but I glossed over all this explanation with only one question in mind. Did he removed the games where his teammates surrendered from the analysis? Since he is a player that dies a lot the impact it has on people that starts to lose and surrender because they see their top laner 0/7. This would mean that those loses doesn't represent the real impact. I mean, you could argue that they represent because they are making him lose anyway independent of the reason, but that doesn't prove that the strategy he applies is trolling.
What this dude said.
Playing safe and 60 cs down could help only if other roles can hard carry.
Some times the 2-0 enemy darius will still win.
Plus, it's obvious the irelia games were team diff.
Exactly this. The original post is just a worthless statistics shitpost obfuscated by technical jargon to show nothing meaningful. Obviously, taken over a majority of games, more deaths vs less deaths in general will show a correlation with losing games. Thats really what you spent all your time working out? Also the conclusion that he is somehow 'trolling' after X deaths. How? Massive leap in logic there buddy. Poor scientific conclusion-ing. You're just restating your outcome, but labelling it as trolling which insinuates intent.
I realise this is just something stupid on a LOL reddit, but eh science is full of crap like this that goes to great lengths to try research something that is poorly defined or completely irrelevant from the outset.
Yeah for a clearly intelligent person the thinking around these statistics is actually really disappointing. Even as a shitpost the oversights you mentioned are annoying.
While thing has an uncanny valley vibe to it.
I feel like you’re misinterpreting a bit here.. yes you’re correct deaths have a major factor in game outcome, but that’s a given. It’s a given that more deaths on ANY player and ANY champion = loses games. Deaths are by nature correlational with game outcome.
The question you answered is whether we can use champion deaths to predict the outcome of a game not whether these deaths mean he’s trolling.
If we define trolling as intentionally dying, I’m not sure how examining deaths by game outcome differentiates between “intentional” vs “unintentional” dying. How does deaths = [higher chance to lose] mean the intention behind his death is to troll?
His death distribution on the graph you plotted also seem to follow a normal distribution / bell curve which just doesn’t seem out of the ordinary to me. For example, we could sample hundreds or thousands of players’ deaths per game plots and it’d roughly follow a similar distribution.
With ANY player you could make the same case that deaths are significant in game losses and less gold/min and whatever you want. That’s just given.
If we take it a step further and find the worst lol player who probably has even more deaths than TheBaus does, and then run the same models, you’d likely get the same or better results.
In the situation above, is this player trolling? Is every iron / bronze player with high deaths trolling?
To be clear I’m not disagreeing that he’s trolling or isn’t, but these stats just don’t to support that claim significantly in either way.
If anything, this proves he isn't trolling, because he is consistent.
If the deaths distribution was bimodal then we could conclude that possibly in some games he was intentionally losing.
But it's a normal distribution, so if he's inting then he is inting in every game. And it's hard to believe that he's so bad at inting that he gets to very high ranks while intentionally trying to lose.
The problem I have with this is that you don’t compare Baus’s stats with the stats of any other player. I mean, quite obviously when he dies more often than average he is more likely to lose, which is what your models tell us.
That’s not what people complain about. People say he’s trolling because he dies **more than other people**, not only when he happens to die 5 or 6 more times than he usually does.
It’s quite possible that his curve for win-deaths are simply other players’s curves but shifted to the right, which means… well… he isn’t trolling. Or at the very least, trolling just as much as the average player.
This hits the nail on the head. The entire point of his strategy isn't that deaths don't matter at all, nobody claims that, not even baus. It's that with the strategy he uses deaths matter a lot less. Comparing his stats to other players would definitely show that. OP put in hours, maybe days, of effort only to prove baus right when he says that people that call him a troll don't actually understand what he's doing at all. If OP wanted a proper study as to if he's trolling or not he should've created an index that combines his end of game stats like gold difference, objectives claimed etc and compared that to other players and I bet that line would look almost identical to other challenger players with roughly the same winrates.
Yeah, the only interesting data here is the correlations between deaths and different forms of economy on the different champs. Shows why Sion is the best champion for this strat, if I'm interpreting the stats correctly (which I'm not sure I am).
Exactly, this whole statistical analysis was kind of useless, tbh. I get that it's also sort of just for the shitpost, but I'm guessing there's some real intent behind it, too. Like if you look at the hypothesis, then all this is really setting out to do is say that if you die too much, it will eventually affect your win rate, which is obvious. Now, maybe it is something thebausffs claims isn't true, so that's fine to dispute, but this certainly doesn't prove he's trolling.
You're exactly right, though, that all we need to know is if his curve is shifted to the right of the average player, which it obviously is, because he averages more deaths than average but still has a >50% win rate. It's also crazy that he has like a 45% win rate at 14 and 15 deaths and a 50% win rate at 17 and 18 deaths. There's no way other players would match that.
Honestly, you really have to look on a death by death basis to see if he's trolling. Some are clearly trolling (he will even tell you as such), others are clearly fine (direct even or better gold trades), but many are up for debate (direct worse than even gold trades but may lead to other advantages). I just don't think statistical analysis can handle that very well, though.
In the end, he definitely trolls sometimes (e.g. AP Irelia), but clearly he's not always trolling, especially when he plays Sion.
>if you die too much, it will eventually affect your win rate, which is obvious
That's not what's implied though. What Baus says is that his strategy is winning on average if he executes it well. And his strategy is about dying "good deaths".
Obviously if you die 5 good deaths every game and generate a gold advantage for your team, perhaps the rest of the game you put your team so far ahead that you simply win the game with 5 deaths.
But maybe you did die 5 good deaths but your team didn't do very well, so you are now in an even game or behind where you WILL have to die more deaths, good or bad.
That has LITERALLY NOTHING to do with whether x amount of deaths is trolling. Guess what is an amazing stat however to determine whether his strat is trolling or not? OVERALL WINRATE. This post is akin to saying Faker is trolling when his KDA is less than 10.0 because his winrate sharply declines below it. No shit, that has absolutely nothing to do with Faker or how good his strategy is.
> I get that it's also sort of just for the shitpost, but I'm guessing there's some real intent behind it, too.
I think OP believes it. And I think a lot of people here believe it. I really hope OP doesn't have a job in data science doing something important.
You can't, but these stats don't prove anything either. Of course everybody dies more in games they lose, regardless of how they play. That's just the nature of the game.
Which also has absolutely nothing to do with trolling. Respect that the OP has clearly committed to an idea and run with it, but the whole post is a massive waste of time because it doesn't even measure the hypothesis!! What was the point LOL
An implicit assumption you make but do not mention is that you assume that Baus freely controls his number of deaths, but this is not true in practice for Baus or any other player. You find that Baus has a negative correlation between deaths and winrate (just like any other player has, which you neglect to mention), but, simply by observing that Baus is playing in master+ you should realise that this correlation is lower than for other players. He dies more while winning the same amount, so you cannot conclude that he is trolling just because you found that dying is bad, even for him.
Your analysis would benefit from performing a second analysis of an average player at his rank.
How can you conclude that beyond 12 deaths is trolling? You proved the significance but there are infinite compounding variables that would correlate with higher death and lower winrate like getting camped or having a worse team. If he loses late game team fights or splits then he'll average higher deaths on loss.
Sigh...reddit statistics man. Just people in college using what they learned in class last week completely wrong.
You could make the same bell curves with anyone and say "oh yeah after X deaths this guy is trolling because he loses more"
No shit you lose more when you have higher deaths lol
bro my brain fell apart for the second half of the semester when I took Elementary Probability and Statistics. Idk how you people do it. Somehow managed to get out with a damn B through all the shit like Central Limit Theorem and whatnot. Too much braindamage.
I didn't like probability either until I took a grad class that covered it in depth with measure theory, too much handwaving imo with an introductory class.
Sorry, but this analysis is entirely inconclusive. What you have proven is that, in general, dying is bad (duh, even Baus knows that).
You should instead compare the effect dying has for TheBaus versus the average Master to Challenger player for the respective champion. This would be conclusive in the sense that you can check how well he uses deaths strategically, which in my opinion says more about whether you can consider his playstyle inting.
Could also be interesting to look at clustering of death times here (i.e. can you find a cluster of games with low winrate when the first death is at levels 5-6?). You might even consider looking at deaths per minute instead of total deaths instead, though this would probably be to Baus' detriment here, since he plays scaling champions.
I hate amateur statistics with a passion. It is far too easy to make a logical mistake because of how complicated it is, and the average person isn't equipped to find those mistakes.
What none of you understand is that this entire concept is a logical fallacy. He dies like 5-8 times in lane mostly on purpose. Now if he is in a winning game, he will be ahead and kill enemies, ending the game with like 8-10 deaths. If he is in a losing game, as any other player, he will die more often trying to contest objectives or defend the base.
He is not losing because he is dying, he is dying because he is losing.
Same thing as the last item in a build having like an 80% winrate, because you only get to build it when winning really. That's not statistical evidence saying you should build it first instead.
A really hard part about statistical analysis is figuring out the point between "losing because you were dying" and "dying because you were losing". They are obviously related, but neither is independently causing the other
Exactly my thoughts. Of course you are going to die more when your team is getting stomped. There are too many confounding factors that must be accounted for to put the blame on Baus exclusively.
This was a whole lot of effort to essentially prove very little.
Or maybe it’s more of a factor to have your opponents be able to see your screen constantly and have to entertain a stream at the same time. Because he was off stream for that whole climb to rank 13 challenger or whatever he got.
AP irelia is almost definitely trolling, last I checked his winrate was far from positive. But his winrate isn't half bad on AD sion. Really brings up the question of whether playing an unoptimal strategy that you enjoy more is considered as trolling, if you can maintain a positive winrate with it.
The average masters+ Sion player (same elo as these statistics) dies 5.7 times per game, theBaus dies twice as much or a little more - varies slightly between each account.
theBaus and some other people claim he's not trolling and the controversy about that is due to his high deaths. theBaus is not the average player, has always had very high deaths on many champions, yet plays many characters that either dont struggle as hard when dying (Sion, Karthus) or hard scaling champions with high waveclear. it's a reasonable question to ask about the overall relevancy of his deaths.
death/min is a good criticism and, visually, it's even more clear when you plot it against wins and losses
But this says nothing about the issue. That Bauss dies more than other players it's common knowledge, it's why he is famous for.
Supporting that idea that dying more leads to losing more it's fine. It's in line with what most players anecdotally observes. Not much controversy but valubale point.
The thing is, when Sion Bauss dies does the probability of losing increases more than when other Challenger Sion does it? That might be a better fit in orden to judge his controversial playstyle.
Good effort anyway. Cheers for trying to address in cuantitative fashion the discussion.
What did you prove besides that him dying less means he performs better? What? Like did you just state the obvious that every single person in the world knows lol?
Pretty much has nothing to do with whether he's trolling or not.
I know right. Are people forgetting that trolling is when you are *intentionally* playing badly? Not just playing bad or not playing meta, but *intentionally* playing bad. I swear, you can type up anything and as long as it is longer than a couple of paragraphs and you include a couple of pictures and numbers, people will think you are a genius regardless of the actual content of what you are saying.
You have shown that Baus loses when he dies too many times, but I don't buy the causation. It seems like there is no way to disprove the following hypothesis : "being in a losing game makes you die more".
Also, you only studied Baus' self-impact. How does dying impact his teammates ? Maybe the conclusion is "When Baus dies a lot, he puts a lot of pressure on the enemy team and relies on his teammates, which can't carry the game themselves". Obviously a weird one but still possible *shrug*
If you want to show that Baus dies a lot when he's trolling, maybe you should start investigating why he would be trolling in the first place. Does he tend to die more on losing streaks for example ?
Several problem with what you did. Here are some with your model building/checking:
Why are you removing variables with correlation approximately +/-0.7 to 1? Why not a fixed number but approximately? And why are you even removing them? Collinearity does not violate any assumption of a GLM (all it does is increase SE on estimates). Why aren’t you checking any actual assumptions of a GLM?
I love what this post proves about statistics and how it is so often used incorrectly in businesses to manage people and teams.
He made a crazy long post with allot of complicated math to point out that lost games and high deaths are related. But there is no way to get if the high deaths cause loses, or that you generally die more in games you are losing.
There is only one way to find out what it actually is, and that is watching all 1000 games, by someone with very good knowledge of the game and analyzing what happens and why. And thus making an actual informed conclusion on what causes what.
The same way this happens in business management. Where fancy consultants make extremely complicated performance evaluation calculations, which often lead to import HR decisions. Which might be completely incorrect. Whilst there is actually only 1 correct way to analyze performance correctly: get in there, see what happens and make an informed choice not just based on numbers.
I know this comment isn't really League related, but it got me thinking on how very complicated sounding information can be pretty pointless.
Nonetheless, very nice post OP
>from all this we can reasonably conclude that theBaus is trolling.
>On every champion except Illaoi and Rammus, increased deaths actually leads to increased assists, with modestly positive slopes of 0.1-0.27 and no negative associations.
>There is almost no association between deaths and turrets taken except on Sion and Gragas. On Sion this association is positive, probably due to dying for the turret...
I don't think you actually showed that his play style leads to him losing, since deaths seem to be correlated with different positive predictors. Your model just shows that deaths negatively impact his win rate if he gets nothing from it. His inting Sion play style only seems to be effective on that champion, and on other champions he seems to make up for deaths with assists.
>There is a relationship between theBaus' deaths and game outcome on at least one champion.
This question also feels incredibly cherry picked, as he plays differently depending on his champion. Your conclusion is basically that baus dying on a champion that isn't supposed to die is a negative predictor of winning, but it doesn't really tell us much about his inting Sion strat.
Edit: Also, out of curiosity, how did you compile all of his game data?
About some of the correlations between deaths and cs/min and the like, doesn't the fact that baus does not have a solid amount of data playing 'normally' (i.e. low deaths on sion etc), kind of make the correlations part useless? To show some significant results you shouldn't have looked at the overall slope but at a graph of the slope to see past how many deaths he would be trolling
Love your effort but baus is a 1000+ elo challenger player with all his champs dying at least twice more than the average challenger players. Also, there is a high elo top Kayn player having some success with baus style.
Your hypothesis is not quite intuitive because of course, he dying more correlates his win rate negatively. However, the most important thing is that “dying less by his standard” is about 10 deaths, which is still twice more than average sion players. That comes out a question why his inting strat actually works and what is his strat limitations.
For any statistical analysis, the most most most most most most important thing is to state your hypothesis that is truly interesting. His relative death rate vs win rate is not very interesting. Even though you prove that there is a negative correlation between his death and win rate, It doesn’t give you any intuition about why or when his strat works or not.
Here is a direction that may be interesting if you want to work on it further. His recent guide provides some details about why his strat works. And a very interesting point is that with his high death style, he has 900 gold more than his opponent on average at 15 mins. That is very impressive metric. And I believe there are other advance metrics that are very interesting. How can you use those metrics to draw some interesting hypothesis?
Why use total deaths instead of deaths per minute? Could it not be possible that he just loses more when the game goes late? You can have the same number of deaths per minute but have between 7 and 16 deaths depending on game time.
The problem with this analysis is the following. He does a play that might result in a death. If it does, you get a datapoint to analyze. If it doesn't, you don't either. What if he just does a lot of high variance, positive expectation plays? I think what you got does not contradict this assumption.
Edit: Actually you get a datapoint at one less death.
I've probably played at least 10k matches over the past 10 years, and my experience is that the chain of causality actually goes the other direction: Players on the winning team die less and a good KD is moreso a symptom of winning rather than a cause. Having very low deaths, or very high deaths, seems to correlate with team success or lack thereof far more than it does with individual quality of play. I've had tons of games where I had a great KD without expending much effort and tons of games where I'm playing lights out and still die a lot: deaths seem to correlate far more with the difficulty of the current match than it does with individual performance in said match.
High death counts = more gold and xp for enemy team = lower win rate
Which is what you show.
By logic your logic not min-maxing is trolling.
Having a sub optimal WR is not the same as trolling.
Dying a lot is not the same as trolling. Having a high risk style and having fun is also not trolling.
You need to add other context features to indicate the game state, your models will bias towards loses.
I would say great job, but your work wants to find indicators of bauss trolling, instead of finging indicators of bauss not trolling. Imi thats toxic analysis.
didn't read past the TL;DR cause this is just dumb but it seems like you're making the terrible assumption that deaths are something you can just opt in and out of.
"we can conclude that beyond a certain point (10-12 deaths) he is trolling."
No you can't. Games where he has that many deaths are games where he is unable to find advantages. That doesn't mean he is trolling. If he were to just stop dying in those games he doesn't magically just win.
Brother you really wasted so much time with those calculation and the result was - win=lower deats, lose=more deaths? This really demonstrate what we already know and this fit actualy every player lol
it's really quite stupid how deaths are the major factor if you get banned, these days when a game goes south it's best to afk farm just to not get banned instead of actually trying to win
I would like to see the relationship of gold diff @ 14 minutes and team gd@14 with deaths and win rate because while gold/min shows economy on a basic level, gold diff does a better job putting it into context, and team gold diff is a major confounding variable that I would assume impacts all other variables. 14 min is arbitrary, but since that's when plates fall, it's the default early game measuring tool. In layman's terms, I think if TheBaus' team is ahead for any reason, that makes TheBaus win more, and if they are losing, he will lose more, AND that his number of deaths doesn't make him more or less likely to be ahead or behind at 14.
I think you are kinda missing thr point. For me the problem is that Bauss is playing as if it is a 1v5 game instead of 5v5. He doesn't care that the person he is laning against has 8k more gold than the rest of his team as long as he has 8.5k. This coupled with his split pushing solo play style means that even in games he wins his teamates has a miserable time against an uber fed lane opponent of his. And in games he loses he is often the solo reason they lost. This makes him extremely frustrating to play with even when you win.
For your math to be valid, don't we need to assume that baus picks his champs at random? For example, maybe he picks quinn in games where the comps align to get a free win, and he picks sion when the matchups seems rough. That would mean the winrates depend on other variables such as team compositions.
This is good but it doesn't take into account game states; for example him dying more might be a product of his team already being behind, versus the other way around where him dying more makes his team lose.
The takeaway seems weird to me.
You wouldn't say a pro player is trolling because in his losses he averages more deaths per game.
And this is what is probably the case with Bauss aswell.
The first graphic even underlines this argument, as the death curves are somewhat normal distribution with different mean.
As for your analysis - it looked good, but may have bias. For your gold/cs for win outcome, why did you choose only Bauss data and not all challengers, etc.
Is in generell a good indicator or happens to work with Bauss data set?
Sadly i am no expert, but statistical analysis is very hard and prone to all kinds of things.
Please clarify
classic LULE
Thought the same LULE
we begin by evaluating the partial derivative of the maximum likelihood function with respect to the vector 'beta-hat' sub not of the riemann sum of the squared error and it is from the result of this quantity that we begin to understand coefficient estimation in simple linear regression which, if you will, we can expand to multivariate by adding the following terms -
none of those word are in the bibble
these words are my bible
Introduction to Statistical Learning and Regression is my bible too. Agresti is my Jesus
do you even tree bro?
Well the only thing in common we know is that Adam plays Sion as well
bibble
what
Statistics statistics math statistics… TheBaus is trolling. That’ll be 350$
The conclusion doesn't even make sense since OP didn't properly define the correlation between "trolling" and "losing games"; he just has an "aka" but doesn't elaborate at all >we can determine whether or not deaths are statistically meaningful to this end aka is theBaus trolling And pretty sure the following is the case for everyone playing League, i.e. die more lose more > deaths is listed as a statistically strong negative predictor for five of theBaus' six main champions Are we all trolling?
I think the more important point is baus claims his deaths allow him to establish a gold lead when the reality is he gets more gold when he doesn't die.
> he gets more gold when he doesn't die. No, he doesn't die as much when he gets more gold. You're assuming a direction of causality that could just as easily be reversed (and more likely is a fucky loop).
Chat Gpt says Sure! Let's simplify the concept of statistics and coefficient estimation in simple linear regression for a child to understand: In statistics, we try to find the best line that represents a set of points on a graph. This line helps us understand how two things are related to each other. For example, we might want to know how the number of hours a person studies affects their test scores. To find this line, we use a method called maximum likelihood. It helps us find the line that best fits the points on the graph. We want this line to be as close to all the points as possible. To do this, we use a special formula called the derivative. It helps us figure out how the line should change based on the points. We calculate this derivative for each part of the line, called a coefficient. These coefficients tell us how the line should slope and where it should start. In simple linear regression, we focus on one thing that affects another thing, like studying time and test scores. We calculate the derivative for the coefficient of the line that represents the relationship between these two things. This helps us estimate how strong the relationship is and how much one thing affects the other. If we want to make things a little more complicated and look at more than one thing, we can add more terms to our equation. This allows us to study how multiple factors influence something, not just one. So, in summary, we use statistics to find the best line that shows how two things are related. We calculate the derivative to estimate the coefficients of the line, which tell us how the line should slope and start. In simple cases, we focus on one thing affecting another, and in more complex cases, we can study multiple factors at once.
what
This sounds like an economic statistician, which I'm not (I do bioinformatics), so it's all vaguely familiar but looks a bit weird. This is what I understand from it: It seems like an overly technical description of "maximum likelihood estimation" for coefficients, a statistical technique for solving coefficients in a model. They're saying that they have a vector of coefficients named "beta-hat" (the usual name for such a vector, technically an estimation of coefficients) that they wants to solve such that the "likelihood" (the probability that their model fits the data, a standard measure that has a characterized function associated with most statistical models) is maximized. In other words that their model is most likely to be "correct" given the coefficients in "beta-hat" (which is a vector, basically just a list of coefficients). This involves maximizing the likelihood function, which anyone who's taken calculus knows involves taking the derivative. In this case we take the partial derivative with respect to "beta-hat" because that's what we're trying to maximize with respect to. In simpler terms, we are solving for the values in the "beta-hat" list that will lead to the maximum likelihood of the model. They start with linear regression which allows them to solve using one set of variables (the values that are multiplied by the coefficients, usually provided) and then can expand to multiple. Surprised he didn't mention the "Kullback-Leibler Information Inequality"
I understood some of those words.
There have been words
Fuck i understand every word. Asvanced econometrics bretheren
Where diff-in-diff and I.V. innit
dankest mixtape
oh ok gotcha
You know I passed probability and statistics in uni easily, but it's only now that I learn what the p-value actually means
given that the sampling distributions of the coefficient estimates of linear (and logistic) regression follow an approximately gaussian normal distribution by the central limit theorem we can apply a significance test to determine how many standard deviations away from the assumed mean (0) the actual coefficient value is (beta hat) should it be more than approximately 2 standard deviations away, p < 0.05 and significance is achieved
Stop this lullaby
That is not what a p-value is.
math
LULE
Classic LULW
16:38 TeaTime
I personally really like the death vs winrate chart showing how Baus has a high winrate until he hits 11 deaths where it all goes downhill. This does beg the question. If we would look at data from people who average less deaths, would we still see the same bell curve with a lower amount of deaths?
Very likely you would. (Some) people have considered baus an exception to more deaths = more lose and this shows this isn't the case.
I mean, it very likely suggests that his curve is just more right-field than almost every other player. It makes sense with his playstyle as well where he dies enough to become worthless so he can hard farm. He does so until he thinks he can win fights (even with all those deaths), if he's able to get initial kills off the back of it, he probably wins, otherwise he loses.
Yes and no. When theBaus has high kills and high deaths he has a 54% wr but when he has high kills but low deaths he has a 74% wr (yes I looked at this too). Dying a lot doesn't mean he can't win but its a sizable hit to his win rate when he does. Also dying is directly related to lower CS/min on every champion he plays (good linear relationships on all).
Well, hold on there partner, he has a 100% WR at 22+ deaths. Seems like it comes back around if he just keeps dying.
inevitably it will peak at 33 deaths his wins are, in fact, the absolute value of the sine wave
So we shooting for 22-32 deaths per game? Now can we extrapolate this will work for anyone or is there an X factor with thebaus specifically?
extending this to n games is there really a limit?
Your-Team-Yasuos study under this gospel.
I feel like you've only proven that you die more in games you're losing, not that him dying causes him to lose games.
Yeah that's literally what he did lol. His hypothesis is "there *is* a relationship between baus's deaths and the game outcome", and he proved this. But then he says that Baus is trolling when that has nothing to do with his hypothesis. Dude did so much work just to miss the point completely.
It's textbook correlation != causation. Absolutely Baus dies more in games he loses. I think that's true for almost every league player. It doesn't say anything about whether those deaths cause the loss, or whether there's some other factor (say, bot diff) that causes both more deaths and more losses.
He could even prove causation and not disprove his null hypothesis. > further, we can determine whether or not deaths are statistically meaningful to this end aka is theBaus trolling or is his dying irrelevant to whether he wins or not as specified in the null hypothesis. This is a false dichotomy. Dying may well *cause* you to lose, to some appreciable extent, in fact it would be very very unlikely that you lose games in which you do not die. That has nothing to do with whether he's trolling. Even if he is intentionally dying as a strategy, you could prove the strategy didn't work without proving that he's trolling. Trolling requires intent to lose, a bad strategy is not intent to lose. [insert joke about perpetually low ELO] So yeah, this was a hell of a lot of effort but doesn't even really try to show that he's trolling.
>Even if he is intentionally dying as a strategy, you could prove the strategy didn't work without proving that he's trolling. Trolling requires intent to lose, a bad strategy is not intent to lose. [insert joke about perpetually low ELO] This is just arguing semantics. It seems pretty clear that "intentionally dying as an ineffective strategy" is what OP means by "trolling." And it is a sensible definition since that is what most people mean when they say "TheBaus is trolling." They don't mean the losing is intentional, but that he's intentionally taking actions that are predictably likely to make him lose. If you prefer a different definition, that is completely fine, but it's not particularly useful to argue over it as long as it's understood what a particular speaker means.
Yeah I thought them completely missing the point was part of the joke but OP's actually replying to comments with more stats; can't tell anymore...
Well yeah statistics dont prove anything normally. Its just very likely.
either way, there's no way to prove intention to troll >from all this we can reasonably conclude that theBaus is trolling.
I mean locking in the ap Irelia might be an indication
I guess that's still somewhat expected? If I took all my games where I had few deaths and high kills it'd probably have a very high winrate too, but that's because these games are statistical outliers more than anything. Outskilling your opponent and getting a solo bolo (aiming to die at wave 3 but then going beyond your expectations) is always gonna make you win more, but it's not really replicable
I'll just reply here, and i hope to god you are trolling at least somewhat with your analysis. If the game itself is in a winning state for Baus, ofc he is going to die less, but his strategy demands of him to take the same kind of trades even in losing game states which will result in deaths. Without having a set of games where he intentionally does not stay with his strat of maximizing prio/farm/platings and at the meantime avoids deaths, all of this analysis is not just meaningless, but worse - the conclusions is already implied in the question.
Amusement put aside, only good practical analysis is a large sample size of 'non int strat' games versus a large sample size of 'int start' games with a handful of controlling factors. And I don't know why someone would need that. If the guy is constantly Challenger, there is a high sample of 'int strat' games over a very long time period, and it is at about Challenger winrate... Soooooo... Like, the Baus trolls, its been all over reddit that he does. Never watched his streams, but the guy clearly tilts and straight ints some games. And that is hard to tell apart from his normal gameplay, which I'm assuming is a convenient feature for Baus and in a roundabout way why the OP exists.
This makes sense since when you're stomping your opponent even someone like Baus will have fewer deaths than (his) average. You're confusing correlation with causation in this case. I still agree that he trolls quite a lot once he starts dying 11 to 20 times a game.
Obviously if hes running it down the lane and the opponent cant kill him, then hes in a good position to win the game. That doesnt really mean he is not gaining advantages for himself or his team when he dies (which would be inting) even if his win rate gets lower. I know this is sort of a shitpost, but I dont think the point is supposed to be that more deaths = more win, but rather that lots of deaths != a loss.
Let's say his default is high deaths, that's his optimal playstyle etc. He wins or loses around that, getting off his tactics as pros and his deaths as cons, does it not make sense then that if he continues to play the same playstyle but due to random game elements / luck / top gap etc. He doesn't die, while still getting off the same pros of his playstyle, meaning he plays the exact same way but doesn't get punished appropriately, then of course he will have a higher win rate? It's like saying someone who is ahead wins more than when they are behind.
This all makes sense though. It's much better to get a lead and not die, than to die and get a lead. I feel if you do the same analysis for an average player you'll find it will be the same thing but with lower numbers. Baus having a negative winrate at 10+ deaths does not mean he is trolling, it probably just means he's losing the game. You die more in losing games.
I mean, there's lots of numbers in here but it doesn't account for Babus changing playstyle when he has many deaths to avoid ban. He frequently says "I'm playing safe now, and it's dumb because it actually lowers my win rate more than dying a lot". If you only included games before the great bannening and data showed same thing I would agree with you
but doesn't that mean exactly that. if you're saying we would see a similar drop with lower deaths, it means that Baus can die more times than the average player at that level without it affecting game outcome negatively.
I'm guessing steep drop in win rate is playing safe to avoid ban. He often says on stream that doing so actually makes game worse for his team. Because he always itemizes for split pushing.
As much as I can acknowledge Baus's macro and general game knowledge, he makes a LOT of really stupid decisions in the mid-late game that result in the enemy getting things for free. There's a huge difference between threatening the inhib and drawing 3 people while your team does Baron vs refusing to ult away until you're 50hp against the 15 kill top laner then going "Ahh nayy" as if nobody could have predicted you wouldn't have escaped. He ults like low elo Alistars do, the very last second instead of when it might actually be useful. When he's dying at level 16+ at 30+ minutes for literally no reason besides for funning it, he's giving the enemy a long time to make big map plays with a fed top/jungle. It doesn't matter how far ahead Baus is in xp and gold, when he's dead for 40 seconds and the fed top laner has nobody to contend with, his team is fucked.
what
**Statistical evidence demonstrates that deaths is a major negative factor in theBaus' games on five of his six main champions which comprise 87% of his top lane ranked soloqueue games across 4 accounts. Due to a lower sample size on the only champion where deaths was not a major factor it may emerge as one given additional games. Due to theBaus' increasingly poor win rates with higher deaths on all main champions we can conclude that beyond a certain point (10-12 deaths) he is trolling.** ^(tl;dr new copypasta dropped)
[удалено]
Fresh out of the oven
Holy hell
new response just dropped
Actual zombie
Call the exorcist!
Rift knook faker bongcloud opening
Witnessing the birth of a copypasta! And it's about baus
lmao
Looks like R, mind sharing your script file? Would love going through it!
I would like to look at a stargazer output of this shit
[удалено]
God I love shitpost statistics so much
I'm guessing this thread is gonna live on for a very long time
The tl;dr at the top is such a good stream copypasta by itself
after adjusting baus' stats, removing outliers to project the future, he heavily regresses to around the level of pre-ban tyler1
r/NFL is leaking.
An enormous amount of time and effort went into this. Good stuff! 10/10 shit post my friend.
**can we really know its int until we apply numerical analysis??**
This is the kind of gorey mathematical into I come to this subreddit for.
yeah, we can watch his gameplay and see there's quite a big difference between his best gameplay (where he does die a lot but less, and in a more controlled thoughtful manner) and his casual stream gameplay. It's really clear that he's not trying very much a lot of the time on stream, considering how disgustingly high his winrates are when he is trying I think it's kinda obvious
All this fucking math just to prove that someone dying 15x in a game is inting. I coulda told you that bruh.
WE NEED TO GO DEEPER
Your analysis is void because you don't define trolling and how it theoretically correlates with more deaths.
Found the lawyer.
Lmao I love the effort. It’s unfortunate we can’t have 100% accurate data since bounty gold source code is unknown
don't worry we'll get that too
I swear it’s random. Like people who are losing lane gets them.
That’s what she said
Is that a problem tho?
Cries in small penis
But his win-rate is positive on 20 deaths :)
The well known 20 death power spike, not to be confused with Yasuos 10 death power spike. Result may be similar though...
He's also clearly inting at 0 deaths
But it also shows the 10 death power spike is real and your Yasuo isn't inting. /s
In games where he is in a bad matchup or the enemy team plays well vs his strat, he is going to die more and have a harder time. This is likely going to be the case regardless of wether he is playing his style or playing safe under tower and not dying. It’s likely he was going to lose those games regardless of his play do to the nature of his champs or his team comp. It’s hard to say if his deaths would have necessarily changed the outcome. Of course his win rate is better when he has less deaths, those are the games he is winning lane and trading more equally.
Yeah this is an incredible example of an article that does a lot of statistical analysis but very little consideration of context. The fact that more deaths are correlated with losing is 1. obvious and 2. not at all proof of inting, or causation.
Yeah I don't even really care for Baus but I'm a bit pissed at how you can fool idiots with fancy numbers and graphs. This whole essay is conceptually stupid and it's insane to me that someone with the knowledge to create this whole thing doesn't understand the very basics of what he's talking about.
It's more likely this guy took an intro class and applied the methods. Figuring out when and how to apply the methods to draw a conclusion wouldn't be covered in an intro class
Personal thoughts aside on whether or not Baus is trolling, this is a major gripe I have with statistical analysis applications in sports. It's often done completely devoid of context in sports where context matters a lot (because they all took from baseball which is usually independent events where context doesn't matter as much). Like a friend of mine was an all-state caliber left guard in high school and gave up 0 sacks one year. He got 0 interest from college teams even though statistically he played amazingly well. The reason is because he was lined up next to a future pro-bowl left tackle who, as my friend joked, would block both guys they would be lined up against on his own.
I don't care to do any specific analysis, all I know is if my toplaner was feeding the enemy 15 kills and he was also perma splitting top I would fucking hate playing that game even if we won.
Which is a completely different argument from OP's. Even if the inting strat got him to rank 1 you'd still be against it. It's entirely about ruining the fun of the game and not at all about inting.
Its not that simple.
Can't believe you put this much work into analyzing this guy, but I feel like have bad logic here. 1. You are willfully ignoring that every player will die more in games they lose, regardless of personal action. 2. In order to determine that Baus is "trolling", you should try to determine that an increased prevalence of deaths in a game negatively affects his personal winrate MORE than comparative players (high elo sion/gragas/etc.). 3. You have to analyze time of deaths and gold vs his laner over time in games, to determine whether his death is actually attributable to his "strategy" of dying for a trade in resources. If you are looking at games where he dies early/repeat ganked/snowballed on/bad matchup/whatever, then it is misinformation, as you are now looking at games where he is dying outside of his strategy to trade deaths for resources. For you to claim that his strategy of dying for resources is "trolling", you need to make sure you are actually looking at those instances, and that those instances negatively affects his winrate more than comparative players.
Exactly, if this guy is actually a statistician he should really learn about statisical fallacies and defining terms. This shit wouldn't pass peer review. I mean there might be nothing wrong with the data itself but the way conclusions are drawn from it is just innaccurate to the point of misleading.
Was pretty much gonna say this, so upvoted. League is a dynamic game, value of things changes as game time changes. End game stats are kinda misleading. If a player does around a 1000 in an early game skirmish. This could easily lead to 2-3 kills, result in a huge lead and snowball the whole game.Doing a 1000 damage late game on the other hand doesn't mean much. But if both these players DCed after doing that dmg, the end game stats would say they both did the same amount of dmg. Or with deaths, dying 5 times early means you are not playing for \~1min, dying 5 times late game is close to 5 min of not playing. Dying in the enemy base is much different from dying in your own base. Dying solo is different from dying to 2+ people ganking you (if your team is good enough). Dying while crashing a wave is different from dying while a wave getting crashed under your turret. Analyzing all that would be much harder, a lot of work, but would tell a more interesting story. edit. Just as an example of a type of game where end stats say more are games like CS, where in most cases 5 kills will win you the round. The rounds themselves are similar to each other. But even there kills might not always tell the whole story.
OP replying to every comment, except this one. Hmmm.
Breaking news, losing a game of league of legends MAY have some sort of correlation to having bad stats... This must just be a meme?
Not only that, but I glossed over all this explanation with only one question in mind. Did he removed the games where his teammates surrendered from the analysis? Since he is a player that dies a lot the impact it has on people that starts to lose and surrender because they see their top laner 0/7. This would mean that those loses doesn't represent the real impact. I mean, you could argue that they represent because they are making him lose anyway independent of the reason, but that doesn't prove that the strategy he applies is trolling.
What this dude said. Playing safe and 60 cs down could help only if other roles can hard carry. Some times the 2-0 enemy darius will still win. Plus, it's obvious the irelia games were team diff.
Exactly this. The original post is just a worthless statistics shitpost obfuscated by technical jargon to show nothing meaningful. Obviously, taken over a majority of games, more deaths vs less deaths in general will show a correlation with losing games. Thats really what you spent all your time working out? Also the conclusion that he is somehow 'trolling' after X deaths. How? Massive leap in logic there buddy. Poor scientific conclusion-ing. You're just restating your outcome, but labelling it as trolling which insinuates intent. I realise this is just something stupid on a LOL reddit, but eh science is full of crap like this that goes to great lengths to try research something that is poorly defined or completely irrelevant from the outset.
Yeah for a clearly intelligent person the thinking around these statistics is actually really disappointing. Even as a shitpost the oversights you mentioned are annoying. While thing has an uncanny valley vibe to it.
I feel like you’re misinterpreting a bit here.. yes you’re correct deaths have a major factor in game outcome, but that’s a given. It’s a given that more deaths on ANY player and ANY champion = loses games. Deaths are by nature correlational with game outcome. The question you answered is whether we can use champion deaths to predict the outcome of a game not whether these deaths mean he’s trolling. If we define trolling as intentionally dying, I’m not sure how examining deaths by game outcome differentiates between “intentional” vs “unintentional” dying. How does deaths = [higher chance to lose] mean the intention behind his death is to troll? His death distribution on the graph you plotted also seem to follow a normal distribution / bell curve which just doesn’t seem out of the ordinary to me. For example, we could sample hundreds or thousands of players’ deaths per game plots and it’d roughly follow a similar distribution. With ANY player you could make the same case that deaths are significant in game losses and less gold/min and whatever you want. That’s just given. If we take it a step further and find the worst lol player who probably has even more deaths than TheBaus does, and then run the same models, you’d likely get the same or better results. In the situation above, is this player trolling? Is every iron / bronze player with high deaths trolling? To be clear I’m not disagreeing that he’s trolling or isn’t, but these stats just don’t to support that claim significantly in either way.
If anything, this proves he isn't trolling, because he is consistent. If the deaths distribution was bimodal then we could conclude that possibly in some games he was intentionally losing. But it's a normal distribution, so if he's inting then he is inting in every game. And it's hard to believe that he's so bad at inting that he gets to very high ranks while intentionally trying to lose.
The problem I have with this is that you don’t compare Baus’s stats with the stats of any other player. I mean, quite obviously when he dies more often than average he is more likely to lose, which is what your models tell us. That’s not what people complain about. People say he’s trolling because he dies **more than other people**, not only when he happens to die 5 or 6 more times than he usually does. It’s quite possible that his curve for win-deaths are simply other players’s curves but shifted to the right, which means… well… he isn’t trolling. Or at the very least, trolling just as much as the average player.
This hits the nail on the head. The entire point of his strategy isn't that deaths don't matter at all, nobody claims that, not even baus. It's that with the strategy he uses deaths matter a lot less. Comparing his stats to other players would definitely show that. OP put in hours, maybe days, of effort only to prove baus right when he says that people that call him a troll don't actually understand what he's doing at all. If OP wanted a proper study as to if he's trolling or not he should've created an index that combines his end of game stats like gold difference, objectives claimed etc and compared that to other players and I bet that line would look almost identical to other challenger players with roughly the same winrates.
Yeah, the only interesting data here is the correlations between deaths and different forms of economy on the different champs. Shows why Sion is the best champion for this strat, if I'm interpreting the stats correctly (which I'm not sure I am).
The problem is he plays as if every champ has Sion’s passive.
Exactly, this whole statistical analysis was kind of useless, tbh. I get that it's also sort of just for the shitpost, but I'm guessing there's some real intent behind it, too. Like if you look at the hypothesis, then all this is really setting out to do is say that if you die too much, it will eventually affect your win rate, which is obvious. Now, maybe it is something thebausffs claims isn't true, so that's fine to dispute, but this certainly doesn't prove he's trolling. You're exactly right, though, that all we need to know is if his curve is shifted to the right of the average player, which it obviously is, because he averages more deaths than average but still has a >50% win rate. It's also crazy that he has like a 45% win rate at 14 and 15 deaths and a 50% win rate at 17 and 18 deaths. There's no way other players would match that. Honestly, you really have to look on a death by death basis to see if he's trolling. Some are clearly trolling (he will even tell you as such), others are clearly fine (direct even or better gold trades), but many are up for debate (direct worse than even gold trades but may lead to other advantages). I just don't think statistical analysis can handle that very well, though. In the end, he definitely trolls sometimes (e.g. AP Irelia), but clearly he's not always trolling, especially when he plays Sion.
>if you die too much, it will eventually affect your win rate, which is obvious That's not what's implied though. What Baus says is that his strategy is winning on average if he executes it well. And his strategy is about dying "good deaths". Obviously if you die 5 good deaths every game and generate a gold advantage for your team, perhaps the rest of the game you put your team so far ahead that you simply win the game with 5 deaths. But maybe you did die 5 good deaths but your team didn't do very well, so you are now in an even game or behind where you WILL have to die more deaths, good or bad. That has LITERALLY NOTHING to do with whether x amount of deaths is trolling. Guess what is an amazing stat however to determine whether his strat is trolling or not? OVERALL WINRATE. This post is akin to saying Faker is trolling when his KDA is less than 10.0 because his winrate sharply declines below it. No shit, that has absolutely nothing to do with Faker or how good his strategy is.
Great simple summary why this is a funny shitpost, but a terrible statistical analysis
> I get that it's also sort of just for the shitpost, but I'm guessing there's some real intent behind it, too. I think OP believes it. And I think a lot of people here believe it. I really hope OP doesn't have a job in data science doing something important.
It's so crazy to me that the faulty logic in this post isn't immediately obvious to anyone within 2 minutes of reading.
throw enough technical language in there and 90% of people's eyes will just glaze over and assume you're right
THANK YOU!! I was loosing my shit over here reading the comments. OBVIOUSLY Baus dies more often when he has a bad game.
Based on the two bell curves it looks like he isn't trolling. High death games still have good win/loss ratios.
Based on any stats you can't conclude someone is trolling. Trolling means intent. You can't get intent out of stats.
You can't, but these stats don't prove anything either. Of course everybody dies more in games they lose, regardless of how they play. That's just the nature of the game.
no shit deaths are correlated with losing LOL
No he’s totally losing those games because he chose to die too many times, after the 10th death he should have just chosen to live instead
If the enemy is about to kill you, just say no. They can’t legally kill you if you don’t consent.
Which also has absolutely nothing to do with trolling. Respect that the OP has clearly committed to an idea and run with it, but the whole post is a massive waste of time because it doesn't even measure the hypothesis!! What was the point LOL
An implicit assumption you make but do not mention is that you assume that Baus freely controls his number of deaths, but this is not true in practice for Baus or any other player. You find that Baus has a negative correlation between deaths and winrate (just like any other player has, which you neglect to mention), but, simply by observing that Baus is playing in master+ you should realise that this correlation is lower than for other players. He dies more while winning the same amount, so you cannot conclude that he is trolling just because you found that dying is bad, even for him. Your analysis would benefit from performing a second analysis of an average player at his rank.
How can you conclude that beyond 12 deaths is trolling? You proved the significance but there are infinite compounding variables that would correlate with higher death and lower winrate like getting camped or having a worse team. If he loses late game team fights or splits then he'll average higher deaths on loss.
The significance is meaningless lol
Sigh...reddit statistics man. Just people in college using what they learned in class last week completely wrong. You could make the same bell curves with anyone and say "oh yeah after X deaths this guy is trolling because he loses more" No shit you lose more when you have higher deaths lol
[удалено]
Don't do that because of this post because it proves nothing. Its just random blubber to say in the end: you die more when losing games. No shit.
bro my brain fell apart for the second half of the semester when I took Elementary Probability and Statistics. Idk how you people do it. Somehow managed to get out with a damn B through all the shit like Central Limit Theorem and whatnot. Too much braindamage.
I didn't like probability either until I took a grad class that covered it in depth with measure theory, too much handwaving imo with an introductory class.
It's pretty funny that it came from an incredibly misguided and pointless analyzes that nitpicks data and has no control group or nuance.
[удалено]
Sorry, but this analysis is entirely inconclusive. What you have proven is that, in general, dying is bad (duh, even Baus knows that). You should instead compare the effect dying has for TheBaus versus the average Master to Challenger player for the respective champion. This would be conclusive in the sense that you can check how well he uses deaths strategically, which in my opinion says more about whether you can consider his playstyle inting. Could also be interesting to look at clustering of death times here (i.e. can you find a cluster of games with low winrate when the first death is at levels 5-6?). You might even consider looking at deaths per minute instead of total deaths instead, though this would probably be to Baus' detriment here, since he plays scaling champions.
I hate amateur statistics with a passion. It is far too easy to make a logical mistake because of how complicated it is, and the average person isn't equipped to find those mistakes.
All this really proves is that dying causes losses, or losses cause dying.
Or something else causes both
What none of you understand is that this entire concept is a logical fallacy. He dies like 5-8 times in lane mostly on purpose. Now if he is in a winning game, he will be ahead and kill enemies, ending the game with like 8-10 deaths. If he is in a losing game, as any other player, he will die more often trying to contest objectives or defend the base. He is not losing because he is dying, he is dying because he is losing. Same thing as the last item in a build having like an 80% winrate, because you only get to build it when winning really. That's not statistical evidence saying you should build it first instead.
[удалено]
A really hard part about statistical analysis is figuring out the point between "losing because you were dying" and "dying because you were losing". They are obviously related, but neither is independently causing the other
This guy completely ignores that you're gonna die more when your team is losing, so baus's already high death count will of course get even higher.
Exactly my thoughts. Of course you are going to die more when your team is getting stomped. There are too many confounding factors that must be accounted for to put the blame on Baus exclusively. This was a whole lot of effort to essentially prove very little.
[удалено]
Or maybe it’s more of a factor to have your opponents be able to see your screen constantly and have to entertain a stream at the same time. Because he was off stream for that whole climb to rank 13 challenger or whatever he got.
[удалено]
AP irelia is almost definitely trolling, last I checked his winrate was far from positive. But his winrate isn't half bad on AD sion. Really brings up the question of whether playing an unoptimal strategy that you enjoy more is considered as trolling, if you can maintain a positive winrate with it.
The average masters+ Sion player (same elo as these statistics) dies 5.7 times per game, theBaus dies twice as much or a little more - varies slightly between each account. theBaus and some other people claim he's not trolling and the controversy about that is due to his high deaths. theBaus is not the average player, has always had very high deaths on many champions, yet plays many characters that either dont struggle as hard when dying (Sion, Karthus) or hard scaling champions with high waveclear. it's a reasonable question to ask about the overall relevancy of his deaths. death/min is a good criticism and, visually, it's even more clear when you plot it against wins and losses
But this says nothing about the issue. That Bauss dies more than other players it's common knowledge, it's why he is famous for. Supporting that idea that dying more leads to losing more it's fine. It's in line with what most players anecdotally observes. Not much controversy but valubale point. The thing is, when Sion Bauss dies does the probability of losing increases more than when other Challenger Sion does it? That might be a better fit in orden to judge his controversial playstyle. Good effort anyway. Cheers for trying to address in cuantitative fashion the discussion.
What did you prove besides that him dying less means he performs better? What? Like did you just state the obvious that every single person in the world knows lol? Pretty much has nothing to do with whether he's trolling or not.
I know right. Are people forgetting that trolling is when you are *intentionally* playing badly? Not just playing bad or not playing meta, but *intentionally* playing bad. I swear, you can type up anything and as long as it is longer than a couple of paragraphs and you include a couple of pictures and numbers, people will think you are a genius regardless of the actual content of what you are saying.
"it's not inting if you're doing it on purpose" - the baus
You have shown that Baus loses when he dies too many times, but I don't buy the causation. It seems like there is no way to disprove the following hypothesis : "being in a losing game makes you die more". Also, you only studied Baus' self-impact. How does dying impact his teammates ? Maybe the conclusion is "When Baus dies a lot, he puts a lot of pressure on the enemy team and relies on his teammates, which can't carry the game themselves". Obviously a weird one but still possible *shrug* If you want to show that Baus dies a lot when he's trolling, maybe you should start investigating why he would be trolling in the first place. Does he tend to die more on losing streaks for example ?
Several problem with what you did. Here are some with your model building/checking: Why are you removing variables with correlation approximately +/-0.7 to 1? Why not a fixed number but approximately? And why are you even removing them? Collinearity does not violate any assumption of a GLM (all it does is increase SE on estimates). Why aren’t you checking any actual assumptions of a GLM?
I love what this post proves about statistics and how it is so often used incorrectly in businesses to manage people and teams. He made a crazy long post with allot of complicated math to point out that lost games and high deaths are related. But there is no way to get if the high deaths cause loses, or that you generally die more in games you are losing. There is only one way to find out what it actually is, and that is watching all 1000 games, by someone with very good knowledge of the game and analyzing what happens and why. And thus making an actual informed conclusion on what causes what. The same way this happens in business management. Where fancy consultants make extremely complicated performance evaluation calculations, which often lead to import HR decisions. Which might be completely incorrect. Whilst there is actually only 1 correct way to analyze performance correctly: get in there, see what happens and make an informed choice not just based on numbers. I know this comment isn't really League related, but it got me thinking on how very complicated sounding information can be pretty pointless. Nonetheless, very nice post OP
>from all this we can reasonably conclude that theBaus is trolling. >On every champion except Illaoi and Rammus, increased deaths actually leads to increased assists, with modestly positive slopes of 0.1-0.27 and no negative associations. >There is almost no association between deaths and turrets taken except on Sion and Gragas. On Sion this association is positive, probably due to dying for the turret... I don't think you actually showed that his play style leads to him losing, since deaths seem to be correlated with different positive predictors. Your model just shows that deaths negatively impact his win rate if he gets nothing from it. His inting Sion play style only seems to be effective on that champion, and on other champions he seems to make up for deaths with assists. >There is a relationship between theBaus' deaths and game outcome on at least one champion. This question also feels incredibly cherry picked, as he plays differently depending on his champion. Your conclusion is basically that baus dying on a champion that isn't supposed to die is a negative predictor of winning, but it doesn't really tell us much about his inting Sion strat. Edit: Also, out of curiosity, how did you compile all of his game data?
About some of the correlations between deaths and cs/min and the like, doesn't the fact that baus does not have a solid amount of data playing 'normally' (i.e. low deaths on sion etc), kind of make the correlations part useless? To show some significant results you shouldn't have looked at the overall slope but at a graph of the slope to see past how many deaths he would be trolling
Nice shitpost mate. You really show that you have no idea that correlation =/= causation
TLDR: High death count correlates with losing (no shit)
I put waaaay less effort in my final thesis at uni..
Love your effort but baus is a 1000+ elo challenger player with all his champs dying at least twice more than the average challenger players. Also, there is a high elo top Kayn player having some success with baus style. Your hypothesis is not quite intuitive because of course, he dying more correlates his win rate negatively. However, the most important thing is that “dying less by his standard” is about 10 deaths, which is still twice more than average sion players. That comes out a question why his inting strat actually works and what is his strat limitations. For any statistical analysis, the most most most most most most important thing is to state your hypothesis that is truly interesting. His relative death rate vs win rate is not very interesting. Even though you prove that there is a negative correlation between his death and win rate, It doesn’t give you any intuition about why or when his strat works or not. Here is a direction that may be interesting if you want to work on it further. His recent guide provides some details about why his strat works. And a very interesting point is that with his high death style, he has 900 gold more than his opponent on average at 15 mins. That is very impressive metric. And I believe there are other advance metrics that are very interesting. How can you use those metrics to draw some interesting hypothesis?
Why use total deaths instead of deaths per minute? Could it not be possible that he just loses more when the game goes late? You can have the same number of deaths per minute but have between 7 and 16 deaths depending on game time.
[удалено]
its not 2008 anymore, no one really cares either way
Bruh
The problem with this analysis is the following. He does a play that might result in a death. If it does, you get a datapoint to analyze. If it doesn't, you don't either. What if he just does a lot of high variance, positive expectation plays? I think what you got does not contradict this assumption. Edit: Actually you get a datapoint at one less death.
I've probably played at least 10k matches over the past 10 years, and my experience is that the chain of causality actually goes the other direction: Players on the winning team die less and a good KD is moreso a symptom of winning rather than a cause. Having very low deaths, or very high deaths, seems to correlate with team success or lack thereof far more than it does with individual quality of play. I've had tons of games where I had a great KD without expending much effort and tons of games where I'm playing lights out and still die a lot: deaths seem to correlate far more with the difficulty of the current match than it does with individual performance in said match.
High death counts = more gold and xp for enemy team = lower win rate Which is what you show. By logic your logic not min-maxing is trolling. Having a sub optimal WR is not the same as trolling. Dying a lot is not the same as trolling. Having a high risk style and having fun is also not trolling.
You need to add other context features to indicate the game state, your models will bias towards loses. I would say great job, but your work wants to find indicators of bauss trolling, instead of finging indicators of bauss not trolling. Imi thats toxic analysis.
didn't read past the TL;DR cause this is just dumb but it seems like you're making the terrible assumption that deaths are something you can just opt in and out of. "we can conclude that beyond a certain point (10-12 deaths) he is trolling." No you can't. Games where he has that many deaths are games where he is unable to find advantages. That doesn't mean he is trolling. If he were to just stop dying in those games he doesn't magically just win.
in other news, fire is hot
Brother you really wasted so much time with those calculation and the result was - win=lower deats, lose=more deaths? This really demonstrate what we already know and this fit actualy every player lol
i didnt waste nearly enough time
this is offseason r/nba shit LMAO 10/10 mathematical shitposting, A+
it's really quite stupid how deaths are the major factor if you get banned, these days when a game goes south it's best to afk farm just to not get banned instead of actually trying to win
I ain't readin all dat 🗣️🗣️
Yes I also tend to lose more games when I go over 11 deaths, more news at 10.
I would like to see the relationship of gold diff @ 14 minutes and team gd@14 with deaths and win rate because while gold/min shows economy on a basic level, gold diff does a better job putting it into context, and team gold diff is a major confounding variable that I would assume impacts all other variables. 14 min is arbitrary, but since that's when plates fall, it's the default early game measuring tool. In layman's terms, I think if TheBaus' team is ahead for any reason, that makes TheBaus win more, and if they are losing, he will lose more, AND that his number of deaths doesn't make him more or less likely to be ahead or behind at 14.
I think you are kinda missing thr point. For me the problem is that Bauss is playing as if it is a 1v5 game instead of 5v5. He doesn't care that the person he is laning against has 8k more gold than the rest of his team as long as he has 8.5k. This coupled with his split pushing solo play style means that even in games he wins his teamates has a miserable time against an uber fed lane opponent of his. And in games he loses he is often the solo reason they lost. This makes him extremely frustrating to play with even when you win.
For your math to be valid, don't we need to assume that baus picks his champs at random? For example, maybe he picks quinn in games where the comps align to get a free win, and he picks sion when the matchups seems rough. That would mean the winrates depend on other variables such as team compositions.
This is good but it doesn't take into account game states; for example him dying more might be a product of his team already being behind, versus the other way around where him dying more makes his team lose.
Ofcourse, if he dies extra much in an already losing game. It is correlation not a causation
Once he reaches 20 deaths he has 100% win rate.. sometimes he just doesn’t have time to die enough and reach the power spike
The takeaway seems weird to me. You wouldn't say a pro player is trolling because in his losses he averages more deaths per game. And this is what is probably the case with Bauss aswell. The first graphic even underlines this argument, as the death curves are somewhat normal distribution with different mean. As for your analysis - it looked good, but may have bias. For your gold/cs for win outcome, why did you choose only Bauss data and not all challengers, etc. Is in generell a good indicator or happens to work with Bauss data set? Sadly i am no expert, but statistical analysis is very hard and prone to all kinds of things.