It's easy to present data, but to explain it is in an another realm of complexity

its because the general public is stupid but yet they somehow have power

But LS is wrong in that "stats are useless". No, stats are useless WITHOUT CONTEXT. But stats are not useless. His example was Kassadin. Ok, what is the winrate delta when the opponent has say >60% of magic damage dealt. How about the winrate delta when Kass is against an AP top and mid vs just AP mid. How about vs immobile? Its not useless. It just needs context and he's out of his mind, either dishonest and in bad faith or just ignorant if he thinks data is useless

@@jordanhelton1675 if you're typing this then you clearly did not watch or listen to anything he said

Sorry data noob here. What is ANOVA?

@@fr1iend let's say you were comparing the winrates of champions (with data from different ranks and regions), you would have variables like Ryze, Leblanc or Azir. They would all have means and variance, on a boxplot you could see the percentiles (IQR) and start making assumptions on their differences. However, without checking through ANOVA, we cannot discern if the differences were due to pure luck, resulting in a false positive, or actually different. ANOVA tests, gives us significant power, the ability to test for false positives for the entire dataset and between variables. So if the mean winrate was 50 +- 0.7 and azir was 52 +-0.2, ANOVA might say Azir is significantly different. 50.5 +- 0.1 would not be. 51 +- 0.08? Not likely. 51.2 +- 0.06? Maybe, this requires ANOVA.

@@alanc6468 im wondering how anova could be this powerful and check for false positives and luck? What would determine a lucky win vs champion power based win?

@@lekken560 Power is a term in stats for identifying the likelihood the results are a false positive. It's based on probabilities and distributions, usually we want the percent chance that the results are a false positive to be lower than 5%. We won't know for sure if a win was pure luck or due to draft but we would have a good idea of how likely the results are due to chance. If the p-value was 0.01, we would say that there was a 1% chance of a better result, the result is a part of the upper echelon of results (99th percentile). ANOVA is just a good statistics calculation, you could do it through a calculator (but that require a lot of hand work). We need ANOVA because other tests would not be accurate in determining the chance of luck.

Yeah, he's complaining about bad data and analysis and the reasons he gives are based on better/newer data but he calls it "information" instead. The 2010 Starcraft player has a better understanding of the game because over time more data has been analyzed and play-styles changed based on that. Picking Rammus into anything is dumb because people are using a very basic dataset to analyze his win rate. Extending that dataset, to factor in matchups and team comps, will give you better data and a better understanding of when rammus is a good pick. I think he's trying to say that intuition is more important, but a lot of the time intuition is based on past experience. A veteran player who's played more games will better understand good/bad match ups because he's experienced them, but just because that information is in his head, instead of on a spreadsheet, doesn't mean it isn't data.

​@@pearce05 You guys are still both missing the point. Obviously he understands the argument about scope, he's not saying that is the sole reason stats have limited utility compared to more hardcore analysis--LS is just giving a simple example of how stats are often misinterpreted. The point about incomplete information is not in reference to a missing statistical data point. It's that the statistics themselves are inherently limited by the context they are in. Example: Tic tac toe meta--The original tic tac toe meta states that X is completely overpowered because it goes first. Everyone including professional Tic tac toers agree! In fact O has 0% winrate and loses every game. What we have to ask ourselves, when determining whether or not X or O has a "real" advantage, has nothing to do with the statistics... yet this is what the League community reaches for, first and foremost. League players say, "X has 100% winrate--it's broken!" Statistics do nothing but synthesize what we already know into a mathematical format. They say basically nothing regarding whether what we know about that subject is right or wrong at a deep level. For this Tic tac toe example, the way we draw a bonafide conclusion, involves rather understanding the rules of the game, analyzing the decisions of both X and O, and finally analyzing the possible, yet unmade decisions, of X and O. These possible, yet unmade decisions, are precisely what LS is referring to when he talks about "information." In this case, upon analysis, players with X and O simply raced independently in their own respective vertical lines, leading to a situation where the player going first would always win. Understanding the rules of tic tac toe, we can safely say that O is not actually underpowered--their strategy sucks, they don't understand the game, nor do they understand the real reason they have 0% winrate. X also has no reason to adapt their strategy, it works every time. Actual progression in the tic tac toe space would come from this sort of analysis, not saying pick X every time you can, and play like this, even if it works. Ultimately, LS in my opinion, is someone who understands that we don't know everything, values questioning our underlying assumptions (which are baked in to any statistic), and pushing for real progression in the League space, by analyzing and expanding on what we know or believe to be true.

August 14. Link in description.

No more videos I'm p sure :(

That sucks cause he's not uploading all the games@@EravohnRname

Yeah but sadly he doesn't want me to and I'll respect that