I have a theory about computer game statistics and i wanted to see how i could proove it.
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I have an idea that keeps bothering me last few days, and i am looking for a way to check, if it makes any sence.
I posted it on reddit/math, but there must be a better place to ask this type of question.
I studied math analysis of data for psychologists in university, i wasn't good student and it was few years ago, but i still think that some of concepts or ideas i learned could help me right know.
So lets imagine that there is an online computer game, many many peoples are playing it every day, and there is like 100 heroes, who obviously can have certain winrate in general. This is session- based game, so we can have millions and millions of games played every month. Take LoL of DoTA for example, if you are familliar with those.
We have tools that could help us tracking winrates: considering that there is two options, win or lose, with general winrate of 50%, some hero can have 45 %, 50.43% , or even 68% winrate. Game is always changes, and with those changes and patches some heroes can receive a buff or nerf, so their winrate could go higher or lower.
So, considering that we have huge number of games played, we can claim that winrate data that we have is relevant, and even 0.5% winrate change for a certain hero is not a statistical error, but there must be a reason behind this change.
But what if we also have a different game with same mechanics and significantly slower playerbase? Lets say that we have 1000 games played on certain hero, for example. And lets say that after a new patch, hero's general winrate goes higher from 45 to 55 percents. Also, tool we use shows us that in lowest skillbracket winrate does not change, but in highest bracket his winrate goes significantly higher, lets say from 48 to 58.
Question is, how do i know that this data is representational? How much data (number of games) do i need to conclude, that even small winrate changes are affected by actuall ingame changes, not by random statistical error? If i have access to this data, what tool should i or anyone else use to verify my theory?
Please dont be mad at me if anything i wrote makes no sence. Have a nice week.
statistics
asked Nov 20 at 13:42
Alex
6
add a comment |
up vote
0
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I have an idea that keeps bothering me last few days, and i am looking for a way to check, if it makes any sence.
I posted it on reddit/math, but there must be a better place to ask this type of question.
I studied math analysis of data for psychologists in university, i wasn't good student and it was few years ago, but i still think that some of concepts or ideas i learned could help me right know.
So lets imagine that there is an online computer game, many many peoples are playing it every day, and there is like 100 heroes, who obviously can have certain winrate in general. This is session- based game, so we can have millions and millions of games played every month. Take LoL of DoTA for example, if you are familliar with those.
We have tools that could help us tracking winrates: considering that there is two options, win or lose, with general winrate of 50%, some hero can have 45 %, 50.43% , or even 68% winrate. Game is always changes, and with those changes and patches some heroes can receive a buff or nerf, so their winrate could go higher or lower.
So, considering that we have huge number of games played, we can claim that winrate data that we have is relevant, and even 0.5% winrate change for a certain hero is not a statistical error, but there must be a reason behind this change.
But what if we also have a different game with same mechanics and significantly slower playerbase? Lets say that we have 1000 games played on certain hero, for example. And lets say that after a new patch, hero's general winrate goes higher from 45 to 55 percents. Also, tool we use shows us that in lowest skillbracket winrate does not change, but in highest bracket his winrate goes significantly higher, lets say from 48 to 58.
Question is, how do i know that this data is representational? How much data (number of games) do i need to conclude, that even small winrate changes are affected by actuall ingame changes, not by random statistical error? If i have access to this data, what tool should i or anyone else use to verify my theory?
Please dont be mad at me if anything i wrote makes no sence. Have a nice week.
statistics
asked Nov 20 at 13:42
Alex
6
Something along the lines of a logistic regression of win rate with the time of the patch introduced as a dummy explanatory variable.
– user121049
Nov 20 at 17:34
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have an idea that keeps bothering me last few days, and i am looking for a way to check, if it makes any sence.
I posted it on reddit/math, but there must be a better place to ask this type of question.
I studied math analysis of data for psychologists in university, i wasn't good student and it was few years ago, but i still think that some of concepts or ideas i learned could help me right know.
So lets imagine that there is an online computer game, many many peoples are playing it every day, and there is like 100 heroes, who obviously can have certain winrate in general. This is session- based game, so we can have millions and millions of games played every month. Take LoL of DoTA for example, if you are familliar with those.
We have tools that could help us tracking winrates: considering that there is two options, win or lose, with general winrate of 50%, some hero can have 45 %, 50.43% , or even 68% winrate. Game is always changes, and with those changes and patches some heroes can receive a buff or nerf, so their winrate could go higher or lower.
So, considering that we have huge number of games played, we can claim that winrate data that we have is relevant, and even 0.5% winrate change for a certain hero is not a statistical error, but there must be a reason behind this change.
But what if we also have a different game with same mechanics and significantly slower playerbase? Lets say that we have 1000 games played on certain hero, for example. And lets say that after a new patch, hero's general winrate goes higher from 45 to 55 percents. Also, tool we use shows us that in lowest skillbracket winrate does not change, but in highest bracket his winrate goes significantly higher, lets say from 48 to 58.
Question is, how do i know that this data is representational? How much data (number of games) do i need to conclude, that even small winrate changes are affected by actuall ingame changes, not by random statistical error? If i have access to this data, what tool should i or anyone else use to verify my theory?
Please dont be mad at me if anything i wrote makes no sence. Have a nice week.
statistics
asked Nov 20 at 13:42
Alex
6
I have an idea that keeps bothering me last few days, and i am looking for a way to check, if it makes any sence.
I posted it on reddit/math, but there must be a better place to ask this type of question.
I studied math analysis of data for psychologists in university, i wasn't good student and it was few years ago, but i still think that some of concepts or ideas i learned could help me right know.
So lets imagine that there is an online computer game, many many peoples are playing it every day, and there is like 100 heroes, who obviously can have certain winrate in general. This is session- based game, so we can have millions and millions of games played every month. Take LoL of DoTA for example, if you are familliar with those.
We have tools that could help us tracking winrates: considering that there is two options, win or lose, with general winrate of 50%, some hero can have 45 %, 50.43% , or even 68% winrate. Game is always changes, and with those changes and patches some heroes can receive a buff or nerf, so their winrate could go higher or lower.
So, considering that we have huge number of games played, we can claim that winrate data that we have is relevant, and even 0.5% winrate change for a certain hero is not a statistical error, but there must be a reason behind this change.
But what if we also have a different game with same mechanics and significantly slower playerbase? Lets say that we have 1000 games played on certain hero, for example. And lets say that after a new patch, hero's general winrate goes higher from 45 to 55 percents. Also, tool we use shows us that in lowest skillbracket winrate does not change, but in highest bracket his winrate goes significantly higher, lets say from 48 to 58.
Question is, how do i know that this data is representational? How much data (number of games) do i need to conclude, that even small winrate changes are affected by actuall ingame changes, not by random statistical error? If i have access to this data, what tool should i or anyone else use to verify my theory?
Please dont be mad at me if anything i wrote makes no sence. Have a nice week.
statistics
statistics
asked Nov 20 at 13:42
Alex
6
asked Nov 20 at 13:42
Alex
6
asked Nov 20 at 13:42
Alex
6
asked Nov 20 at 13:42
Alex
6
asked Nov 20 at 13:42
Alex
6
6
Something along the lines of a logistic regression of win rate with the time of the patch introduced as a dummy explanatory variable.
– user121049
Nov 20 at 17:34
add a comment |
Something along the lines of a logistic regression of win rate with the time of the patch introduced as a dummy explanatory variable.
– user121049
Nov 20 at 17:34
Something along the lines of a logistic regression of win rate with the time of the patch introduced as a dummy explanatory variable.
– user121049
Nov 20 at 17:34
Something along the lines of a logistic regression of win rate with the time of the patch introduced as a dummy explanatory variable.
– user121049
Nov 20 at 17:34
add a comment |
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Something along the lines of a logistic regression of win rate with the time of the patch introduced as a dummy explanatory variable.
– user121049
Nov 20 at 17:34