I have significant history of being a gold player so that nmakes me think I wouldn’t be eligble for this thing. A-B testing between “natural learning” and “proper learning” could still be relevant.
If the ability of the good players would consist of factors that could be communicated or transferred and people have the motivation to do so the good players would lose their edge. Different routes migth have different conveoyance limits. For example it is very hard to give verbal instructions to how to effectively use a bike but bike-skills are still frequent as a little experimental practise quickly aquires it. It is not a competetive market in the sense that everybody does the game thing,as there are actual barriers to entry. Some of the barriers might play larger or smaller roles but everybody doesn’t collapse to a single rating.
Picking only smart people is like a school accepting only good students and then miraclously having good grades for their students. If the point is to measure the impact of couching itm ight make sense to avoid be overly selective. However if the focus is on the minimum time and effort to hit a highish bar that might make sense.
With regard to “advice sink time” I could also describe that as “low cognitive autonomy”, “high suggestibility” or “meta-monkeying”. There is also the issues on whether a communcation succeds or not whether that is due to the success or failure of the transmitter or the receiver. Concepts made by 4000 to be consumed by 4000 people might be hard for others to adopt not because of cognitiive domination but it being relevant to that style and culture. What I have seen opinion leaders do is that some advice for pros should not be folowed by lo SR people and that some people actively hurt themjselfs for trying. “Under gold just get your aim correct and don’t even think about anything else”.
There are probaly bad memes about being “super good at reaction speed”. But there are also differnces within anticipation. There is atleast the distinction between remembering and calculating what is going to happen, that of being habituated what happens in situations like these ie memory and extrapolating current situation into the future. I think for example in high level chess players lose ability to articulate particular reasons why moves are good or bad. So for games there migth be situation where extrapolation couterintuitive gives a bad result and a pure associative link can get past this.
There is also a difference of being able to execute a strategy or tactic that is good in the current scene versus being able to adapt and come up with such things.
A lot of people play games to be entertained to be fun. Some pros can gain pleasure form being good but it seems it tends to have a “harsh practise big winout” structure. The problem for the casual player is that learning “properly lethal” techniques is fun negative in the first half. This prevents people from randomly fluctuating into them.n The proble is even worse if “playing crappy” produces actively more entertaining games. In a game if you are fairly matchmade it is always a challenge but the entertainment gained from different styles of play might not be similar. That is pro-like games can be more fragile in their entertainment payout rather than unskilled versus unskilled. This can form a phenomenon where a player learns that if they improve they just get put into games where they have more chance to make unfun mistakes which can effectively make learning punishing.
I am also interested about the hypotheses that if we take randoms and artifiically make them scrim and be deliberate for example 2 weeks, but don’t provide couching how much this would help things.
“You should not expect to get anything out of this other than ~80-100 hours of fun video game coaching.” vs “I cannot guarantee you will have fun.” these 2 are contradictory. In agreeing to a group setting and a schedule you can have experiences which would not be possible playing as a solo to the random wrath of matchmaking. It would make sense for me that if the participants are expected to commit to put in the time there could/would be a symmetric part for the couches. Currently it seems you would bail out the second you think you are wrong. If you don’t actively sabotage the fun it is probably be expected to be net-fun but the challenges of coaching are going to be how to do stuff that is indifferent or contrary to the fun-gradient.
I would prefer not to take on people with history of being gold players because it seems like bad science. However, I don’t have a ton of interest at the moment, so I might consider whether it’s a good idea?
“Picking only smart people is like a school accepting only good students and then miraclously having good grades for their students.”—I don’t think this is true. Yes, if I picked a bunch of smart students and then my students all turned out to be good at mathematics or programming or Greek, it wouldn’t be surprising. However, if I picked people purely on IQ and then it turned out they were all very good marathon runners, it actually would be very surprising! My point is that many people think that esports is a similar domain to marathon running (you primarily need genetics/reflexes and lots of time) whereas I think esports is in a similar domain to mathematics (smart people can become good at it quickly). This is precisely the point I am trying to prove; I am not trying to prove that I am a good coach or measure the impact of coaching or anything along those lines. That would be sort of egotistical.
“Concepts made by 4000 to be consumed by 4000 people might be hard for others to adopt not because of cognitiive domination but it being relevant to that style and culture.”—This is occasionally true, but primarily because of the way other people play in lower SR games. For instance, I might tell a 4400 player to do something which relies on the assumption that they will be backed up and supported by others, whereas in gold your teammates will leave you to die and you cannot demand so many resources. I think if you train an entire team simultaneously, this effect is wholly nullified. 4400 players are just better than gold players, and they play the strategies they play because they win, not because of a stylistic difference.
“There is also a difference of being able to execute”—yes, but this is not relevant for the goal of reaching ~3500. It is not even relevant if your goal was 4200. This is relevant if you wanted to become a 4500+ coach, and basically never relevant as a player.
On learning being less fun—I suspect this is significantly less true for LW-y nerdy types, who will enjoy a game more (not less) if it’s a tricky intellectual strategy game rather than a mindless spray-and-pray aiming adventure (which is the primary way I see the ‘but doing it properly wouldn’t be fun’ thing ever come up).
I can expect that you will have fun without guaranteeing that you will have fun. I think there is a high probability that you will have fun.
I am not planning on bailing out the second I think I am wrong. However, I will cancel the “mandatory activities that all six of you have to do as a team” part if I think the amount of fun/success you will have is not worth the mandatory-attendance-activity-time. In such a scenario I’m still more than happy to do optional one-on-one work if someone just wants to be better at video games for their own sake.
I am not surprised that gold background is a undesirable trait. however this is how we get high side-effects for women in drugs sold at stores, because testers prefer male over female. If humans in the wild have a 20% trait rate and your sample has 1% or 0% that is going to lead in a bad result in its own way. Having a WEIRD sample is not particularly representative.
If you have a discipline that supports multiple frameworks and recruit on resonance with a particular framework then the result tells less about the frameworks properties. For example one could try to provde that chess is an endurance game of bothering to check enough positions and reqruit based on stamina in order to “prove” it is not a game of intellect.
I remember when balancing away dive was a talking point. Then a lot of the teams were squamish in scrimming other strategies. If you need to redo the whole strategy stack instead of just adjusting the top layers then teams will eventually do it but it can take long while.
If you tell a high rank player to push they will know to still reftrain from being mindlessly suicidal, to not push all the way throught spawn etc. If you desribe somethings color in grue and bleen if helps if the communication reciever has existing support for those concepts. Even if there is no explicit culture sharing the learning curve could provide a way for “on the onset” some fundamentals to be evident and then when those are taken into account then more fine-graded concepts can make sense. But part of the point is that the incentive gradient to make the distinction doesn’t exist at all stages. This can be seen as an aspect to the “smiley face maximiser” error state of aligment problem, the defintions and concepts that humans actually use don’t exist in a neat context-free way. Telling a human to go “make people smile” result in sensible action while a literal minded Ai will tile things destructively with inapproriate patterns.
I have significant history of being a gold player so that nmakes me think I wouldn’t be eligble for this thing. A-B testing between “natural learning” and “proper learning” could still be relevant.
If the ability of the good players would consist of factors that could be communicated or transferred and people have the motivation to do so the good players would lose their edge. Different routes migth have different conveoyance limits. For example it is very hard to give verbal instructions to how to effectively use a bike but bike-skills are still frequent as a little experimental practise quickly aquires it. It is not a competetive market in the sense that everybody does the game thing,as there are actual barriers to entry. Some of the barriers might play larger or smaller roles but everybody doesn’t collapse to a single rating.
Picking only smart people is like a school accepting only good students and then miraclously having good grades for their students. If the point is to measure the impact of couching itm ight make sense to avoid be overly selective. However if the focus is on the minimum time and effort to hit a highish bar that might make sense.
With regard to “advice sink time” I could also describe that as “low cognitive autonomy”, “high suggestibility” or “meta-monkeying”. There is also the issues on whether a communcation succeds or not whether that is due to the success or failure of the transmitter or the receiver. Concepts made by 4000 to be consumed by 4000 people might be hard for others to adopt not because of cognitiive domination but it being relevant to that style and culture. What I have seen opinion leaders do is that some advice for pros should not be folowed by lo SR people and that some people actively hurt themjselfs for trying. “Under gold just get your aim correct and don’t even think about anything else”.
There are probaly bad memes about being “super good at reaction speed”. But there are also differnces within anticipation. There is atleast the distinction between remembering and calculating what is going to happen, that of being habituated what happens in situations like these ie memory and extrapolating current situation into the future. I think for example in high level chess players lose ability to articulate particular reasons why moves are good or bad. So for games there migth be situation where extrapolation couterintuitive gives a bad result and a pure associative link can get past this.
There is also a difference of being able to execute a strategy or tactic that is good in the current scene versus being able to adapt and come up with such things.
A lot of people play games to be entertained to be fun. Some pros can gain pleasure form being good but it seems it tends to have a “harsh practise big winout” structure. The problem for the casual player is that learning “properly lethal” techniques is fun negative in the first half. This prevents people from randomly fluctuating into them.n The proble is even worse if “playing crappy” produces actively more entertaining games. In a game if you are fairly matchmade it is always a challenge but the entertainment gained from different styles of play might not be similar. That is pro-like games can be more fragile in their entertainment payout rather than unskilled versus unskilled. This can form a phenomenon where a player learns that if they improve they just get put into games where they have more chance to make unfun mistakes which can effectively make learning punishing.
I am also interested about the hypotheses that if we take randoms and artifiically make them scrim and be deliberate for example 2 weeks, but don’t provide couching how much this would help things.
“You should not expect to get anything out of this other than ~80-100 hours of fun video game coaching.” vs “I cannot guarantee you will have fun.” these 2 are contradictory. In agreeing to a group setting and a schedule you can have experiences which would not be possible playing as a solo to the random wrath of matchmaking. It would make sense for me that if the participants are expected to commit to put in the time there could/would be a symmetric part for the couches. Currently it seems you would bail out the second you think you are wrong. If you don’t actively sabotage the fun it is probably be expected to be net-fun but the challenges of coaching are going to be how to do stuff that is indifferent or contrary to the fun-gradient.
I would prefer not to take on people with history of being gold players because it seems like bad science. However, I don’t have a ton of interest at the moment, so I might consider whether it’s a good idea?
“Picking only smart people is like a school accepting only good students and then miraclously having good grades for their students.”—I don’t think this is true. Yes, if I picked a bunch of smart students and then my students all turned out to be good at mathematics or programming or Greek, it wouldn’t be surprising. However, if I picked people purely on IQ and then it turned out they were all very good marathon runners, it actually would be very surprising! My point is that many people think that esports is a similar domain to marathon running (you primarily need genetics/reflexes and lots of time) whereas I think esports is in a similar domain to mathematics (smart people can become good at it quickly). This is precisely the point I am trying to prove; I am not trying to prove that I am a good coach or measure the impact of coaching or anything along those lines. That would be sort of egotistical.
“Concepts made by 4000 to be consumed by 4000 people might be hard for others to adopt not because of cognitiive domination but it being relevant to that style and culture.”—This is occasionally true, but primarily because of the way other people play in lower SR games. For instance, I might tell a 4400 player to do something which relies on the assumption that they will be backed up and supported by others, whereas in gold your teammates will leave you to die and you cannot demand so many resources. I think if you train an entire team simultaneously, this effect is wholly nullified. 4400 players are just better than gold players, and they play the strategies they play because they win, not because of a stylistic difference.
“There is also a difference of being able to execute”—yes, but this is not relevant for the goal of reaching ~3500. It is not even relevant if your goal was 4200. This is relevant if you wanted to become a 4500+ coach, and basically never relevant as a player.
On learning being less fun—I suspect this is significantly less true for LW-y nerdy types, who will enjoy a game more (not less) if it’s a tricky intellectual strategy game rather than a mindless spray-and-pray aiming adventure (which is the primary way I see the ‘but doing it properly wouldn’t be fun’ thing ever come up).
I can expect that you will have fun without guaranteeing that you will have fun. I think there is a high probability that you will have fun.
I am not planning on bailing out the second I think I am wrong. However, I will cancel the “mandatory activities that all six of you have to do as a team” part if I think the amount of fun/success you will have is not worth the mandatory-attendance-activity-time. In such a scenario I’m still more than happy to do optional one-on-one work if someone just wants to be better at video games for their own sake.
I am not surprised that gold background is a undesirable trait. however this is how we get high side-effects for women in drugs sold at stores, because testers prefer male over female. If humans in the wild have a 20% trait rate and your sample has 1% or 0% that is going to lead in a bad result in its own way. Having a WEIRD sample is not particularly representative.
If you have a discipline that supports multiple frameworks and recruit on resonance with a particular framework then the result tells less about the frameworks properties. For example one could try to provde that chess is an endurance game of bothering to check enough positions and reqruit based on stamina in order to “prove” it is not a game of intellect.
I remember when balancing away dive was a talking point. Then a lot of the teams were squamish in scrimming other strategies. If you need to redo the whole strategy stack instead of just adjusting the top layers then teams will eventually do it but it can take long while.
If you tell a high rank player to push they will know to still reftrain from being mindlessly suicidal, to not push all the way throught spawn etc. If you desribe somethings color in grue and bleen if helps if the communication reciever has existing support for those concepts. Even if there is no explicit culture sharing the learning curve could provide a way for “on the onset” some fundamentals to be evident and then when those are taken into account then more fine-graded concepts can make sense. But part of the point is that the incentive gradient to make the distinction doesn’t exist at all stages. This can be seen as an aspect to the “smiley face maximiser” error state of aligment problem, the defintions and concepts that humans actually use don’t exist in a neat context-free way. Telling a human to go “make people smile” result in sensible action while a literal minded Ai will tile things destructively with inapproriate patterns.