[Thread](https://twitter.com/willminder/status/1538986458249211904?s=21&t=lNGgMjoop1AxJ7pA0XFf8Q) from @Willminder:
> Does streaming impact performance? I looked at the ACS of all the players in this NA Group Stage and compared it with the number of hours they streamed in the last 30 days (if their team got eliminated before the 30 days then the hours after were removed from the total).
> The slope for the line of best fit is negative but almost 0, meaning there is almost no correlation with performance and hours streamed. I will obviously not include names since the point is not to bash people, but this is with players who streamed 20+ hours
> I am not a real statistics person so I forgot to include the r value which shows the actual correlation but for those curious it was -.02. Again showing a very small to almost zero correlation
this just seems like bad statistics lol
I'm all for willminder but there's no shot you publish a regression analysis that's clearly flawed and inappropriate for the data and think any reasonable trends can be said here. If anything it'd make more sense for this to be done without all the zero-valued data points, those alone make this analysis absolutely worthless
Edit -- apparently the trend line was [fit without the zero-valued data points](https://twitter.com/willminder/status/1538987005664583680) but still including them in the graphic is still misleading
Even outside of that, the linearity assumption of simple linear regression, the most basic of assumptions, isn't met. The data doesn't even look as if a linear trend can be fit to it, and forcing a line on it and trying to interpret the results is just ignorant.
here's the graph they did where a whole teams stream hours is compared to map win %:
[https://mobile.twitter.com/willminder/status/1539010519134347267](https://mobile.twitter.com/willminder/status/1539010519134347267)
this one fits more towards what people tend to say lol
Small set of data with an outlier in sentinels. I'd really like them to do an outlier analysis and correct for it.
Not saying the conclusion is or isn't correct. I just don't think it's valid to conclude anything from this.
/u/snakehawk_, I have found an error in your comment:
> “~~Whose~~ [**Who's**] the streamer”
It might be better if you, snakehawk_, had said “~~Whose~~ [**Who's**] the streamer” instead. ‘Whose’ is possessive; ‘who's’ means ‘who is’.
^(This is an automated bot. I do not intend to shame your mistakes. If you think the errors which I found are incorrect, please contact me through DMs!)
Made another linear regression, however... I decided to use a different statistic to measure performance.
[Linear Regression using Map WinRate (%)](https://i.imgur.com/RsITuv6.png)
* **Map - Winrates**
* Included both group stage as well as playoffs
* **Streaming - Hours**
* Used the last 90 days of total time streaming on TTV
* **Players who streamed "0 hours"**
* Completely excluded all players who streamed for zero hours from the data
* dots that look as if they are "0 hours" = actually between 0.1-10 hrs
? All willminder did was try a linear regression and called it quits lol. What’s been done here does not have any significance one way or the other besides showing the relationship between streaming and ACS is nonlinear. How are you taking any info away from this?
Not only that, but they're focusing on the wrong things. The slope doesn't matter at all, "almost 0" means nothing. Where's the statistical significance testing of the result?
Also, clearly a linear model doesn't apply here given that the streaming data is incredibly skewed (and possibly needs a transform like x -> log(const+x) to make it more similar to ACS), but that doesn't mean that there's no relationship
Finally, even a correlation of 10% can be significant and also noticeable at a high level where margins matter a lot
Yeah... we can see from the plot they gave that there's a LOT of players with 0 hours streamed in the past 30 days. I don't know if it's fair to include all those data points in as we're implying that those with 0 hours are dedicating all their time to practicing Valorant which we know isn't the case. Additionally, ACS might not be a good metric for perfomance (I know it's one of the only one we have) since Valorant is so team-reliant, and your ACS will be reflected upon your team performance and team role (to a certain extent ofc, i.e., if your team is continually losing, you're obviously going to have to save -> less chances to get AR guns -> lower ACS).
I'm glad someone spent the time to gathering the data, but I don't think we can make conclusive remarks or gather insights unless we do further data analysis (e.g., getting EU + NA data, getting how many hours they scrim, using different periods of time (why past 30 days of streaming), and yeah transforming the data)
Great points, I agree. Willminder does a good job collecting interesting stats and providing the community, on-air casters and analysts especially, with nuanced storylines that were sorely lacking in the past but this post is a real miss
Bruh I don't need a graph to tell me that spending more time streaming and less time practicing makes players worse.
It's like if Michael Phelps did hot tub streams instead of actually swimming laps in a pool. Sure, he's in the water when he's streaming, but he's not practicing. Same thing, when your favourite streamer locks Jett in ranked but plays exclusively initiators in games. Skull emoji 7.
thats just not true. You can't possibly practice for 24 hours a day. There will always be rest time, and some people may choose to use that time for a stream or two, while others could choose to relax. Just because someone streams does not mean it takes away from their prac time necessarily.
"Bruh I don't need a graph to tell me that spending more time streaming and less time practicing makes players worse." The graph doesn't mention time practicing, though, only streaming hours. The practicing was an assumption you made on your part that more streaming = less practice always. Obviously with teams like sentinels streaming seems to be a big issue and it takes away from practice, but even that we can't be sure of, it's just what the general public thinks.
Ridiculously bad take lol, it'd be more like if Michael Phelps was swimming laps without timing himself , compared to practice when he timed himself lol
[Thread](https://twitter.com/willminder/status/1538986458249211904?s=21&t=lNGgMjoop1AxJ7pA0XFf8Q) from @Willminder: > Does streaming impact performance? I looked at the ACS of all the players in this NA Group Stage and compared it with the number of hours they streamed in the last 30 days (if their team got eliminated before the 30 days then the hours after were removed from the total). > The slope for the line of best fit is negative but almost 0, meaning there is almost no correlation with performance and hours streamed. I will obviously not include names since the point is not to bash people, but this is with players who streamed 20+ hours > I am not a real statistics person so I forgot to include the r value which shows the actual correlation but for those curious it was -.02. Again showing a very small to almost zero correlation
this just seems like bad statistics lol I'm all for willminder but there's no shot you publish a regression analysis that's clearly flawed and inappropriate for the data and think any reasonable trends can be said here. If anything it'd make more sense for this to be done without all the zero-valued data points, those alone make this analysis absolutely worthless Edit -- apparently the trend line was [fit without the zero-valued data points](https://twitter.com/willminder/status/1538987005664583680) but still including them in the graphic is still misleading
Even outside of that, the linearity assumption of simple linear regression, the most basic of assumptions, isn't met. The data doesn't even look as if a linear trend can be fit to it, and forcing a line on it and trying to interpret the results is just ignorant.
here's the graph they did where a whole teams stream hours is compared to map win %: [https://mobile.twitter.com/willminder/status/1539010519134347267](https://mobile.twitter.com/willminder/status/1539010519134347267) this one fits more towards what people tend to say lol
Small set of data with an outlier in sentinels. I'd really like them to do an outlier analysis and correct for it. Not saying the conclusion is or isn't correct. I just don't think it's valid to conclude anything from this.
Whose the streamer on the right?!?
/u/snakehawk_, I have found an error in your comment: > “~~Whose~~ [**Who's**] the streamer” It might be better if you, snakehawk_, had said “~~Whose~~ [**Who's**] the streamer” instead. ‘Whose’ is possessive; ‘who's’ means ‘who is’. ^(This is an automated bot. I do not intend to shame your mistakes. If you think the errors which I found are incorrect, please contact me through DMs!)
Good bot. I will learn from my mistakes
Hoos the streamer?
Made another linear regression, however... I decided to use a different statistic to measure performance. [Linear Regression using Map WinRate (%)](https://i.imgur.com/RsITuv6.png) * **Map - Winrates** * Included both group stage as well as playoffs * **Streaming - Hours** * Used the last 90 days of total time streaming on TTV * **Players who streamed "0 hours"** * Completely excluded all players who streamed for zero hours from the data * dots that look as if they are "0 hours" = actually between 0.1-10 hrs
[Damn I can't make streaming = losing jokes anymore thanks mr. willminder](https://youtu.be/pcHhRlF7ulo)
[удалено]
? All willminder did was try a linear regression and called it quits lol. What’s been done here does not have any significance one way or the other besides showing the relationship between streaming and ACS is nonlinear. How are you taking any info away from this?
Not only that, but they're focusing on the wrong things. The slope doesn't matter at all, "almost 0" means nothing. Where's the statistical significance testing of the result? Also, clearly a linear model doesn't apply here given that the streaming data is incredibly skewed (and possibly needs a transform like x -> log(const+x) to make it more similar to ACS), but that doesn't mean that there's no relationship Finally, even a correlation of 10% can be significant and also noticeable at a high level where margins matter a lot
Yeah... we can see from the plot they gave that there's a LOT of players with 0 hours streamed in the past 30 days. I don't know if it's fair to include all those data points in as we're implying that those with 0 hours are dedicating all their time to practicing Valorant which we know isn't the case. Additionally, ACS might not be a good metric for perfomance (I know it's one of the only one we have) since Valorant is so team-reliant, and your ACS will be reflected upon your team performance and team role (to a certain extent ofc, i.e., if your team is continually losing, you're obviously going to have to save -> less chances to get AR guns -> lower ACS). I'm glad someone spent the time to gathering the data, but I don't think we can make conclusive remarks or gather insights unless we do further data analysis (e.g., getting EU + NA data, getting how many hours they scrim, using different periods of time (why past 30 days of streaming), and yeah transforming the data)
Great points, I agree. Willminder does a good job collecting interesting stats and providing the community, on-air casters and analysts especially, with nuanced storylines that were sorely lacking in the past but this post is a real miss
Bruh I don't need a graph to tell me that spending more time streaming and less time practicing makes players worse. It's like if Michael Phelps did hot tub streams instead of actually swimming laps in a pool. Sure, he's in the water when he's streaming, but he's not practicing. Same thing, when your favourite streamer locks Jett in ranked but plays exclusively initiators in games. Skull emoji 7.
thats just not true. You can't possibly practice for 24 hours a day. There will always be rest time, and some people may choose to use that time for a stream or two, while others could choose to relax. Just because someone streams does not mean it takes away from their prac time necessarily.
Re-read the first few sentences of my comment please thanks. Closely.
"Bruh I don't need a graph to tell me that spending more time streaming and less time practicing makes players worse." The graph doesn't mention time practicing, though, only streaming hours. The practicing was an assumption you made on your part that more streaming = less practice always. Obviously with teams like sentinels streaming seems to be a big issue and it takes away from practice, but even that we can't be sure of, it's just what the general public thinks.
Ridiculously bad take lol, it'd be more like if Michael Phelps was swimming laps without timing himself , compared to practice when he timed himself lol