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On March 28 2014 05:23 Sufficiency wrote:Show nested quote +On March 28 2014 05:12 TheYango wrote:On March 28 2014 05:05 Sufficiency wrote:
If you wish, we can argue about the merits. No models are perfect, and there are always trade offs. A simple model for an exploratory analysis is very useful, in particular, before a more complex model is applied. The exploratory analysis is a lot less useful than you make out because in general the amount of rigor needed for something to be established within this sphere is far less than in formal scientific investigation. You need far less than a formal theory with significant data backing it up to convince a bunch of nerds on the internet playing video games of anything. Which in turn means the practical usefulness of such an approach is far less. You are saying my model is an oversimplification so much as to be useless. Unfortunately, doctors prescribe medicine based on statistical evidence that is even more oversimplified. Bankers invest money based on statistical models that barely make sense. Yet I am just here analyzing data from a video game.
We all know that most financial models are total garbage results of retrofitting, as is most social science. The fact that people believe them doesn't make your use of retrofitting and more "useful" in some way.
As for medicine, my prolific experience with biotechnology and clinical pipelines means that however "simplified" analysis may be it stems from a causative base rather than data mining and retrofitting.
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On March 28 2014 05:27 xes wrote:Show nested quote +On March 28 2014 05:23 Sufficiency wrote:On March 28 2014 05:12 TheYango wrote:On March 28 2014 05:05 Sufficiency wrote:
If you wish, we can argue about the merits. No models are perfect, and there are always trade offs. A simple model for an exploratory analysis is very useful, in particular, before a more complex model is applied. The exploratory analysis is a lot less useful than you make out because in general the amount of rigor needed for something to be established within this sphere is far less than in formal scientific investigation. You need far less than a formal theory with significant data backing it up to convince a bunch of nerds on the internet playing video games of anything. Which in turn means the practical usefulness of such an approach is far less. You are saying my model is an oversimplification so much as to be useless. Unfortunately, doctors prescribe medicine based on statistical evidence that is even more oversimplified. Bankers invest money based on statistical models that barely make sense. Yet I am just here analyzing data from a video game. We all know that most financial models are total garbage results of retrofitting, as is most social science. The fact that people believe them doesn't make your use of retrofitting and more "useful" in some way. As for medicine, my prolific experience with biotechnology and clinical pipelines means that however "simplified" analysis may be it stems from a causative base rather than data mining and retrofitting.
I'm getting my doctorate in clinical psychology and I will fight u irl
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On March 28 2014 05:26 ZERG_RUSSIAN wrote:Show nested quote +On March 28 2014 05:22 Nos- wrote:On March 28 2014 05:21 Carnivorous Sheep wrote:On March 28 2014 05:18 Kyrie wrote:
i took precalc as a high school freshman, put me in coach
it seems that for alpha > .05, an overcompensating beta will create a charlie foxtrot of poorly fitted regressions when a simple montecristo simulation would have sufficed to reveal an inherent meta/data dissonance Can we all pause a moment and talk about how amazing this post is? i think he needs to add the Rivington Regression to make that model work more accurately for the target audience on the backside
What Kyrie is saying are the things I am trying to avoid.
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On March 28 2014 05:27 xes wrote:Show nested quote +On March 28 2014 05:23 Sufficiency wrote:On March 28 2014 05:12 TheYango wrote:On March 28 2014 05:05 Sufficiency wrote:
If you wish, we can argue about the merits. No models are perfect, and there are always trade offs. A simple model for an exploratory analysis is very useful, in particular, before a more complex model is applied. The exploratory analysis is a lot less useful than you make out because in general the amount of rigor needed for something to be established within this sphere is far less than in formal scientific investigation. You need far less than a formal theory with significant data backing it up to convince a bunch of nerds on the internet playing video games of anything. Which in turn means the practical usefulness of such an approach is far less. You are saying my model is an oversimplification so much as to be useless. Unfortunately, doctors prescribe medicine based on statistical evidence that is even more oversimplified. Bankers invest money based on statistical models that barely make sense. Yet I am just here analyzing data from a video game. We all know that most financial models are total garbage results of retrofitting, as is most social science. The fact that people believe them doesn't make your use of retrofitting and more "useful" in some way. As for medicine, my prolific experience with biotechnology and clinical pipelines means that however "simplified" analysis may be it stems from a causative base rather than data mining and retrofitting.
Can you clarify what you mean by retrofitting here?
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On March 28 2014 05:31 ZERG_RUSSIAN wrote:Show nested quote +On March 28 2014 05:27 xes wrote:On March 28 2014 05:23 Sufficiency wrote:On March 28 2014 05:12 TheYango wrote:On March 28 2014 05:05 Sufficiency wrote:
If you wish, we can argue about the merits. No models are perfect, and there are always trade offs. A simple model for an exploratory analysis is very useful, in particular, before a more complex model is applied. The exploratory analysis is a lot less useful than you make out because in general the amount of rigor needed for something to be established within this sphere is far less than in formal scientific investigation. You need far less than a formal theory with significant data backing it up to convince a bunch of nerds on the internet playing video games of anything. Which in turn means the practical usefulness of such an approach is far less. You are saying my model is an oversimplification so much as to be useless. Unfortunately, doctors prescribe medicine based on statistical evidence that is even more oversimplified. Bankers invest money based on statistical models that barely make sense. Yet I am just here analyzing data from a video game. We all know that most financial models are total garbage results of retrofitting, as is most social science. The fact that people believe them doesn't make your use of retrofitting and more "useful" in some way. As for medicine, my prolific experience with biotechnology and clinical pipelines means that however "simplified" analysis may be it stems from a causative base rather than data mining and retrofitting. I'm getting my doctorate in clinical psychology and I will fight u irl
Please, behavioral psychology and clinical psychology are almost real sciences. There's like, actual empiricism!
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On March 28 2014 05:34 Sufficiency wrote:Show nested quote +On March 28 2014 05:27 xes wrote:On March 28 2014 05:23 Sufficiency wrote:On March 28 2014 05:12 TheYango wrote:On March 28 2014 05:05 Sufficiency wrote:
If you wish, we can argue about the merits. No models are perfect, and there are always trade offs. A simple model for an exploratory analysis is very useful, in particular, before a more complex model is applied. The exploratory analysis is a lot less useful than you make out because in general the amount of rigor needed for something to be established within this sphere is far less than in formal scientific investigation. You need far less than a formal theory with significant data backing it up to convince a bunch of nerds on the internet playing video games of anything. Which in turn means the practical usefulness of such an approach is far less. You are saying my model is an oversimplification so much as to be useless. Unfortunately, doctors prescribe medicine based on statistical evidence that is even more oversimplified. Bankers invest money based on statistical models that barely make sense. Yet I am just here analyzing data from a video game. We all know that most financial models are total garbage results of retrofitting, as is most social science. The fact that people believe them doesn't make your use of retrofitting and more "useful" in some way. As for medicine, my prolific experience with biotechnology and clinical pipelines means that however "simplified" analysis may be it stems from a causative base rather than data mining and retrofitting. Can you clarify what you mean by retrofitting here?
When a hipster tries on clothing, we call that retrofitting.
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The first, and (imo) relatively simple application of the data i would try, which reddit would probably like too (more then just raw statistics and p values) would be a "what should i pick" style program.
Just choose a p value to use as a cutoff, then calculate all the counters/synergies of each individual champion. This'll give you two lists for each champion, 117 entries long (or however many champions there are -1.) delete all data with p values above your cutoff.
Now each champion has an associated list showing what it's strongest with, and what it's best against. Now write a program where you can enter between 0 and five champions on the enemy team, and 0-4 champions on your team. The program will then calculate the probabilty of each available champion of winning in this situation, by adding the synnergy chances of your team and the "counter" chances of the other teams champions, (potentially weighting by some inverse function f(p)->x so lower p values are more important), and spit out 4-5 champions which have the highest chance of winning.
Should be codeable in a day or two (plus however long creating data for each champion takes) and would be pretty interesting, plus reddit tends to love those kind of things, especially when the statistics behind it's creation are easily understandable. You can add specific roles if you want, or weight your lane opponent more heavily then the rest of their team or whatever.
I'm not really a statistician, but find more "practical" applications like that much more interesting, even if they wont be 100% reliable.
On March 28 2014 05:50 krndandaman wrote:
I'm legitimately confused whether some people are parodying or actually serious.
plz stop i want my league discussion back
Imoperator and roffles get temped, and GD immediately turns to discussing the merits of various statistical models for analyzing league meta-data.
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i think the whole point is that statistics paint an incomplete picture no matter how rigorous your model is
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Can someone tell me why the competitive scene always get Elder Lizard on Evelynn? It seems to me that the true damage DoT only applies when you deal physical damage, but her Q and R (her only AOE spells) deal magical damage?
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On March 28 2014 06:07 Sufficiency wrote:
Can someone tell me why the competitive scene always get Elder Lizard on Evelynn? It seems to me that the true damage DoT only applies when you deal physical damage, but her Q and R (her only AOE spells) deal magical damage?
Well her q and e both have ad ratios equal or better then their ap ratios. You get 20 more ap from wraith then you get ad from lizard, so if you can proc the elder lizard with an auto or e once then you'd need like 5-6 more q's (without managing to auto or e once to reproc lizard) to get even the same damage with wraith as lizard would have given.
Also While clearing you'll be autoing a bunch, using the extra ad + proccing the DoT.
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Are you guys really having this big of an argument over Sufficiency's statistics thing?
I don't remember anybody being all "THIS IS THE ONE TRUE GOSPEL FOR CHAMPION SELECT", because that would be dumb.
What I do remember is him posting some findings that, more or less, aren't very surprising and corroborate stuff that we already know. Yi gets pentakills. Leona doesn't do well vs. Janna and Thresh and does well vs. Sona and ADCs that don't have any escape tools. This is not particularly jaw dropping information.
And when the data has shown something weird I haven't seen anybody being all "OH MY GOD WE WERE ALL WRONG" they've been more like "Huh, that's weird."
It's a fun little project, and is far and beyond more interesting than 9/10ths of the shit I see in GD threads. If you want to say it's not a perfect way to learn about the game, I think everybody would agree with you. But to say it's not worth doing at all I think is somewhat dismissive and even a little petulant.
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man im awful at gragas wtf.
how do people manage to insta-delete someone with R+Q? do you need good latency or something to make them blow up at the same time?
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On March 28 2014 06:21 arb wrote:
man im awful at gragas wtf.
how do people manage to insta-delete someone with R+Q? do you need good latency or something to make them blow up at the same time?
It's a lot easier if you body slam, q q r them.
If they're long range and you're fed I guess you just double tap q on them, then wait like half a second and r (if it looks like they aren't going to dodge.) latency shouldn't have anything to do with it, as the trick to getting them to pop at the same time is just the length of the gap between the qq and the r.
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On March 28 2014 06:12 killerdog wrote:Show nested quote +On March 28 2014 06:07 Sufficiency wrote:
Can someone tell me why the competitive scene always get Elder Lizard on Evelynn? It seems to me that the true damage DoT only applies when you deal physical damage, but her Q and R (her only AOE spells) deal magical damage? Well her q and e both have ad ratios equal or better then their ap ratios. You get 20 more ap from wraith then you get ad from lizard, so if you can proc the elder lizard with an auto or e once then you'd need like 5-6 more q's (without managing to auto or e once to reproc lizard) to get even the same damage with wraith as lizard would have given. Also While clearing you'll be autoing a bunch, using the extra ad + proccing the DoT.
I see. It seems that her AD ratios are mostly the same as her AP ratios (same on E, AP ratio is only 0.05 smaller on Q). I guess Lizard gives her a quicker early game spike.... which makes sense.
On March 28 2014 06:02 killerdog wrote:The first, and (imo) relatively simple application of the data i would try, which reddit would probably like too (more then just raw statistics and p values) would be a "what should i pick" style program. Just choose a p value to use as a cutoff, then calculate all the counters/synergies of each individual champion. This'll give you two lists for each champion, 117 entries long (or however many champions there are -1.) delete all data with p values above your cutoff. Now each champion has an associated list showing what it's strongest with, and what it's best against. Now write a program where you can enter between 0 and five champions on the enemy team, and 0-4 champions on your team. The program will then calculate the probabilty of each available champion of winning in this situation, by adding the synnergy chances of your team and the "counter" chances of the other teams champions, (potentially weighting by some inverse function f(p)->x so lower p values are more important), and spit out 4-5 champions which have the highest chance of winning. Should be codeable in a day or two (plus however long creating data for each champion takes) and would be pretty interesting, plus reddit tends to love those kind of things, especially when the statistics behind it's creation are easily understandable. You can add specific roles if you want, or weight your lane opponent more heavily then the rest of their team or whatever. I'm not really a statistician, but find more "practical" applications like that much more interesting, even if they wont be 100% reliable. Show nested quote +On March 28 2014 05:50 krndandaman wrote:
I'm legitimately confused whether some people are parodying or actually serious.
plz stop i want my league discussion back Imoperator and roffles get temped, and GD immediately turns to discussing the merits of various statistical models for analyzing league meta-data.
Oh wtf lol http://www.teamliquid.net/forum/closed-threads/32696-automated-ban-list-latest-theanarchy?page=1699#33965
What happened?
Anyway, yes I have a similar idea in mind as well. But to do this, I need to be able to at least predict, given all 10 champions in the game and which side they are on, who has a higher chance to win and what exactly is the chance. This is most likely straight forward to do, but takes a bit of time to construct. Not 1-2 days kind of work. More like at least a week, if not more.
I am a little worried about the actual predictive power once I do construct the model... which makes the project risky. I could be doing everything right but still can't make the correct prediction more than 55% of the time - which would suck really hard. This is why I have not totally committed to this yet.
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Lizard is just the better item overall at the moment...
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On March 28 2014 06:35 cLutZ wrote:
Lizard is just the better item overall at the moment...
Perhaps, but I think Golem isn't too bad.... admittedly it gives different kinds of stats.
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On March 28 2014 06:07 Sufficiency wrote:
Can someone tell me why the competitive scene always get Elder Lizard on Evelynn? It seems to me that the true damage DoT only applies when you deal physical damage, but her Q and R (her only AOE spells) deal magical damage?
Because they're all doing tank builds. The extra AP will only be beneficial if you're going for more of an AP build with sorc shoes/abyssal/liandry's.
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EPT
