Well…
With How hearthstone is nowadays a meta that don’t has consistent finishers would make games Go to fatigue atleast.
So my personal problem with your view is that it is so fixated on power reseting the game that it does 0 Sense to the game we have now.
Getting hit by a high amount of damage by a “semi OTK” is not only the standard but necessary in the game that is played today.
Atleast 10/15 damage Burst or some form of persistent damage between turns like corpsicle.
When you have historical decks hitting 20+%, the play rate of paladin is pretty meh despite being a strong deck.
I get that it’s the sixth most played in your data, but that still isn’t very much representation in the meta when 95%+ of the game is not paladin.
I doubt you see a deck with that low play rate get nerfed unless it does some toxic, infinite thing too early.
It only means something in context, and it doesn’t mean much to be the sixth most at that low a play rate.
Pretty sure noone in the top ranks thinks like that. That sounds like what I do in real life, but definitely not something i would be doing for a game xD
This is where you are wrong.
That method is called weighing and its used in engineering (acoustics, electromagnetism…), economy (econometry, microeconomy…) and statistics to analyze two or more variables at the same time
It works. The fact that you dont understand it doesnt change it.
And the reason why i know it works, is because i play in top 1k. And then i look at VS tier list and compare it to my experience and tracker data. Thats not it.
And then i look at that weighted meta score and compare it to tracker data and experience. Suddenly it works.
Look, i appreciate a good theory and i love theorizing. However, sooner or later comes a time when things need to be done in practice and thats when things get messy and theory doesnt work as you imagined.
Thats when you should revisit that theory because you cant change what happens in real life, but you can change what you imagine in your head.
I suggest you try it sometimes.
I literally cant drop to 2k if i played a loaner deck and lowrolled. The only thing that can get me so far below is a month or two of break or a big change in meta. I’m slow to adapt
I do often briefly derank to like 1100, 1200 but that lasts for 2 hours at most
Schylla was simply desperate to discredit me because i had all the arguments and proofs
But then i posted the proofs of rank, as well, whicj you might have seen if you hadnt put me on ignore that day
Winrates are negative because its top 500 stats and ive played against better players a lot
Top 1k stats are 57-58% winrates
Yes, thats how big the skill difference is between rank 200 and rank 800.
And wanna know something funny?
It’s even bigger between ranks 20 and 200. I literally lose 90% of games against top 20 players. I have played them a lot, as well.
I am partial to a good comedy but alas a greek tragedy is all you can deliver.
If i want to feel doom and gloom i have countless current day news to throw my pity at.
All this circus would be unnecessary if only you were able to answer simple questions…
Doesnt get more simple than a name , and if a man cant deliver his made up card game identity theres not much else to say.
I rather dance with the other court jesters in this halls , you bore me dear.
Nothing but apathy and apathy is death, worse than death, because at least a rotting corpse feeds the beasts and insects.
I strongly suggest therapy.
This feels like a gish gallop to me. You probably assume, correctly, that I’m not an expert in literally every field, so you named four of them. I am, however, pretty competent at economics and, no, they don’t just multiply two numbers together for no good reason in any economics I know of.
I’m not going to chase down multiple subjects. Provide specific examples, or it didn’t happen.
No it doesn’t. It merely aligns with your subjective feelings. If it actually “worked” you could post the mathematics showing that it works. Again, prove it.
Your arguments are weak and you don’t have proof at all.
So at the end of the day all you really have is “just trust me bro” which is essentially using your rank as some form of authority. I guess he might wish to discredit that. I’d just say that it doesn’t matter what your rank is, because your arguments are weak and you don’t have any proof at all.
Would you please stop projecting? I know you’re being devious a lot of your time, but don’t just assume others do the same just because you do.
Bwah. I’m sorry, but that won’t fly with me. You just happened to pick my field of expertise where I’m literally a published scientist.
And if you know it as well as you say you do, what’s so special about economics?
It’s not even a science on its own. It’s something like medicine and engineering - it’s a composite, applied scientific discipline consisting of multiple other main sciences, in this case mathematics, statistics, psychology, sociology…
It starts from statistics:
There are several kinds of weight variables in statistics:
* **Frequency weights:** A frequency variable specifies that each observation is repeated multiple times. Each frequency value is a nonnegative integer.
* **Survey weights:** Survey weights (also called *sampling weights* or *probability weights*) indicate that an observation in a survey represents a certain number of people in a finite population. Survey weights are often the reciprocals of the selection probabilities for the survey design.
* **Analytical weights:** An analytical weight (sometimes called an *inverse variance weight* or a *regression weight*) specifies that the *i*_th observation comes from a sub-population with variance σ2/*w* i, where σ2 is a common variance and *w* i is the weight of the *i*_th observation. These weights are used in multivariate statistics and in a meta-analyses where each "observation" is actually the mean of a sample.
* **Importance weights:** an "importance weight" is a STATA-specific term that is intended "for programmers, not data analysts." The developer says that the formulas "may have no statistical validity" but can be useful as a programming convenience. Although I have never used STATA, I imagine that a primary use is to downweight the influence of outliers.
Source: https://blogs.sas.com/content/iml/2017/10/02/weight-variables-in-statistics-sas.html
What I did is I used popularity as a frequency weight, because how big a sample is determines how strong/reliable the winrate stat is. The lower the sample, the higher the variance, thus, the weaker/less reliable the winrate stat is. Since we’re talking statistics here, not engineering, we’re not trying to be precise, but we’re trying to determine how something is on average, right? Well, on average, the lower the sample, the less reliable the statistic.
Other uses:
The Dow Jones Industrial Average (DJIA) is a price-weighted average that compares each security based on the stock’s price relative to the sum of all the stocks’ prices. The S&P 500 Index and Nasdaq Composite Index, on the other hand, are based on market capitalization, where each company is measured relative to its market value.
Where the DJIA and Nasdaq indexes utilize weighting in their calculation to more closely approximate the effect that changing stock prices will have on the overall market, weighting can also be used to help evaluate the past and current prices of individual instruments through technical analysis.
Source: https://www.investopedia.com/terms/t/technicalanalysis.asp
On a survey from a car brand, 700 females and 300 males were asked about what type of car they drive to work. This group of 1000 respondents is called the sample.
However, the car brand knows that the market is comprised of 50% male and 50% female. This 50/50 makeup is called the target population.
Because of this discrepancy between the sample and the target population, the respondents must be weighted so that males have an equal representation as females. This math can be quite complicated, but it will result in an output that more accurately represents the market.
Source: https://www.appinio.com/en/blog/market-research/weighting-survey-data
So basically, in marketing, in macroeconomics and investing, in labour markets…
But the point is, it’s not an economic tool. It’s a statistical tool, largerly applied in different applied sciences - you know, the ones that actually work in practice and are not just useless theorizing?
You are, again, being devious and manipulating what others think. Or at least, trying to. No, that’s not something that merely aligns with my subjective feelings. It’s factual.
There’s not enough mathematics in the whole world to make anyone, including you, on this forum to accept an argument. I have tried way too many times. Also, you know yourself how basic the mathematics behind what I did was. It’s literally the simplest example of weighing two variables you could find other than the men vs women survey analysis example provided above.
Much stronger than you, who never posts proofs, just talks crap. And if, by any case you do post proof, noone will be able to understand it. I’m done thinking it’s because we don’t know as much as you do, sorry, but no, you wasted all your credit with me.
Nope. You intentionally make it that way so noone could check it and call you out on your crap.
As far as anything useful and applicable coming from you, I’m yet to witness that. It hasn’t happened yet. Probably never will.
I’m yet to see anything resembling strength my arguments have, or anything resembling proof in a more objective and visible way than I provide.
Trying to discredit me has a much higher chance of working, due to my ego, than trying to discredit my arguments. I know what I’m doing and I know what I’m talking about, and I know how to recognize those who don’t.
Good luck with both 
P.S. This is 2nd, 3rd or 4th time I literally write essays and papers with citations and sources for you, to prove my arguments. How many times have you done that to prove yours when arguing with me?
How many times did you bring out an excel sheet which also aligns with your experience, subjective as it is? How many times did you post screenshots of things you claim?
How in the world do you even think I can take you seriously when I do all of the above every time it’s possible, and you never do?
Why do you insist on getting ignored forever?
P.P.S. I just played the 1st game against Pally in 3 days. 1st game in 30 on this deck, + 20 or 30 games on other decks. I don’t know why this isn’t nerfed with such playrate, wow, just wow.
What about that quote led you to believe i even play Paladin decks? Point of fact i don’t because they are extremely linear and boring. I was just pointing out that more decks have popped into the meta that are very good at beating Paladin.
You didn’t, because you didn’t add anything. You don’t even seem to understand what weighting is.
While increasing sample size does decrease margin of error, it is critical to understand that this effect is not linear. If a sample has a margin of error of 10% — so 90% is outside the margin — and you double the sample size, you don’t get 180% outside the margin, that’d be silly. Again, the core issue here is that you’re not finding the right formulas. You can’t just say that deck frequency is related in some vague way to X, so because X and Y are important you’re going to multiply Y by deck frequency. In this case, the reliability of the data is related to sample size but it is NOT equal to sample size.
Sum. So a formula that involves an operation that isn’t ×. So already more complicated than the Meta Score crap you’re defending.
This is exactly why and how Vicious Syndicate uses estimated winrate instead of raw winrate.
But what you are not understanding is that the way that a weighted average works is that it is NOT a raw product. It is the sum of products. In this case, if you take % of men and multiply it by men survey results, that number by itself means NOTHING. You need the entire target population, which includes women. On the other hand, if you take % men × men survey results + % women × women survey results, that DOES mean something.
Weighting isn’t about simple products. It is about the sums of products.
No and yes, in that order.
The men vs women example is NOT simpler than what you did. What you did is so simple that doesn’t even qualify as weighting at all. What you did is as if you started the process of the most simple weighting possible, then you inexplicably stopped halfway through, before the math could mean anything.
I have always included links to the spreadsheets where I do all my calculations, which include formulas. Because I understand that it is possible, albeit unlikely, for me to get formulas wrong.
That’s because you’re full of yourself and think your crappy arguments are good.
If I was a professor I would fail all of your papers. You cite nonsense to support nonsense. Get real and stop being proud of this
Much more than the average forum goer.
Literally never. I’ve always taken data from sources other than myself.
I’m not going to self censor myself to appease your overgrown ego.
Team 5 is completely off base, and they have been for years.
I didn’t say you played them (it was a general figure of speech “you shouldn’t play it after…”).
I wouldn’t say they are exactly linear because there are several alternative cards to play,
it’s just that the draw and mulligan impacts are too similar so choice is less potent.
So basically, you’re saying that what I did is nonsense, even though it shows literally the exact same result as VS meta score? And you’re saying that despite understanding their methodology and supporting their data and their methods?
Just for the reference, here is VS Meta score:
https://www.vicioussyndicate.com/drr/vs-meta-score/
Their order, by score, was:
…and here’s my list (table on the right):
https://ibb.co/FHKPQYz
Even though it’s the same?
OK. That’s it. We’re done.
You may believe what you want, but if you’re going to suggest people to play Rainbow Shaman even though the deck is unplayable, because their made-up tier list says it’s tier 1, then it won’t be long before everyone puts you on ignore.
I’m not to blame that you choose to believe the wrong statistic because you don’t play the game. That’s on you, your useless theorizing and lack of playing the game you’re trying to teach others about.
And, as promised, it’s gonna be a long time before you and I interact again.
Lol never being played good one made me laugh for a sec.
Idk why you’re laughing. It’s less than 5% of the meta, which is not much in a world where mage has been literally more than 30% of the meta in the past.
I’m saying VS Meta Score is complete trash. So yes if your results are the same as theirs, they’re also complete trash.
Ok now that’s being deceptive don’t matter if it’s the 6th or not.
Complete lie… i even showed videos with stats.
Druid has 5000+ games to paladins 500ishs games recorded. Dk has 3000ish games in t1000 to paladins 500ish and this is not even counting the variations. If we just look at the 5000 to 500 thats legit 1/10 of a play rate in just ONE SET OF DATA shpwing a significant lower play rate than other decks.
Breakfast Hunter has a higher play rate in t1000 thats saying ALOT right there.
You point fingers at other people yet your not doing proper reasearch or even unbias statistics. NOTE I SAID UNBIAS STATISTICS you quote VS like its Jesus Christ himself coming to give the world the cure for cancer.
You dont look subjectively into there data you just belive whatever they say without question
Meta score is complete bull and you used legend data NOT T1000 DATA which is what this conversation is about.
At this point you are making yourself look like a fool.
This…
This my stats show i run into paladin in about 4.87% of my games.
This
You know the whole reason I go so hard on this its because
Is legit on some crusade to get paladin nerfed. Its simple as hell to counter. Multiple decks and every class has a way to counter. Unless your draw is dog poop or maybe your play the few archtypes that do bad against it the only way you can loose is from being bad at the game or bad draw.
The more you keep going on this the more your credibility of skill at this game tanks.
Also, its legit solitare and boring as heck to play. The last almost fun one was librum paladin. Its win rate and play rate started dieing at d5-legend as well too for the same reason paladin does now.
It was funny when that top steamer started promoting it I watched its live win rate tank on HS replay for 3 days. It went from like 53~54%ish win rate to 38% lmao in d5+ for a damn good reason. I showed that data too in another thread.
Again Linear easy to predict and easy to counter.
I doubt that any of you are capable of actually understanding this, but I try anyway.
The number of games recorded is NOT directly representative of the play rate of a deck.
For example, let’s imagine a very simple meta with 4 decks. The actual play rate of the decks is 40% A, 30% B, 20% C and 10% D. However, there is a smaller subset of players who have the deck tracker software installed, that records the games. Let’s say that the deck preferences of the tracker software players is 35% A, 35% B, 25% C and 5% D. For every 200 games played, you’re going to record, on average, games according to the chart below.
| ↓tracker opponent→ | A | B | C | D |
|---|---|---|---|---|
| A | 28 | 21 | 14 | 7 |
| B | 28 | 21 | 14 | 7 |
| C | 20 | 15 | 10 | 5 |
| D | 4 | 3 | 2 | 1 |
Then for the matchup winrates, they’re going to add the games where tracker A played opponent B, to the games where tracker B played opponent A. So in the matchup winrate chart published by VS, you’re going to see something like this for games played:
| A | B | C | D | |
|---|---|---|---|---|
| A | 56 | 49 | 34 | 11 |
| B | 49 | 42 | 29 | 10 |
| C | 34 | 29 | 20 | 7 |
| D | 11 | 10 | 7 | 2 |
| total | 150 | 130 | 90 | 30 |
| % | 37.5% | 32.5% | 22.5% | 7.5% |
If you actually ever bother to count the games in a VS matchup winrate table, you’ll notice that, like this chart, the overall sum is about double the total number of games recorded. Slightly less, because not every deck fits the archetype definitions. This is because most matchups are presented twice, and mirror matches are doubled (always an even number).
So when you take a deck’s games played as a percentage of total games played, you are not getting the popularity of the deck. You are getting the average of the actual popularity, and the tracker player popularity. For D in this example, 7.5% is the average of 10% and 5%.
In VS Report #302, Handbuff Paladin was in a D type situation. The deck was between 4% and 5% popularity with the overall playerbase, and BELOW those numbers in popularity for players who had the tracker software installed — for example, in Legend overall, Handbuff Paladin had 4.09% overall popularity but only 2.91% tracker player popularity, therefore coming in at 3.5% of overall games played within the sample.
The tracker side of data is marred by selection bias. Best practice is to only look at opponent side data for overall deck popularity. You don’t accomplish this by counting games played. Games played is essentially a 50/50 mix of good opponent side data and contaminated tracker side data.
By the way, here’s a fun little chart.
https://i.imgur.com/SpjypEZ.png
Rogue, Druid, Insanity Warlock, Overheal Priest, Reno Warrior and Frost DK were overrepresented by tracker players in Legend. Pretty much everything else was underrepresented.
About 0.11% of tracker players in Legend played Elemental Shaman. Data drought.
Sonya Rogue is/was a very “I have tracker installed and I think I’m better than everyone else” deck, lol
After the oatch is 2% of the meta in legend also not even top performer. Nerfung it is pointless as it’s the only viable paladin deck because the vards from the newest set are unplayable trash.