Youth Soccer Rankings ?

Only playing highly ranked teams in league doesnt immediately inflate a teams ranking it takes time to occur. Also all teams in the league have to only be playing teams in that league. If one team goes off the reservation and losses it affects everyone else.

This is exactly what’s happening. Teams in these closed league play most of their games against themselves, even if they lose one game badly against an outsider team, their ranking aren’t affected because there are 9 other games that fits the soccer ranking prediction. It’s like you said a “self fulfilling” prophecy.

You both realize you're arguing contradictory points and think that you're agreeing, right? One of you is saying that once a team plays outside the league, the results can/will affect everyone else that is within the league. The other is saying that when a team plays outside the league, the results don't count for enough.

You both can't be correct. For what it's worth, Carlsbad7 is closer to the truth.

It might make sense to add additional weight to cross league games as long a both teams were equally ranked. This in theory would incentivize cross league play. This is assuming that US Soccer wants to encourage cross league play. Everyone seems pretty happy the way things are right now.

Additional weight should be placed on games that better predict actual performance. Less weight should be placed on games that aren't as good at predicting actual performance. To your point - the results of games between teams that are close in rating are already more heavily weighted, than games between teams that are further apart from each other. How much weight isn't based on feels - it's based on how much weight results in the highest actual predictivity that can be achieved.

I just doesn't seem the cross pollination between different groups is sufficient to get robust results. Case in point - our older teams (U16, U19) are consistently rated at 4-5 points higher than our U14 group. During intraclub weekly intraclub trainings and scrimmages, the U14 is obviously the stronger team - consistently going up by 1-2 goals over 15-20 minutes. Sure, they're not official matches, but we've seen this over the past 2 years week in week out. We find soccer rankings to be predictive within the group, but it hasn't done a great job predicting results between different groups of players.

This is interesting, and I wonder why you're seeing that. How are the individual teams compared to their peer teams in other clubs - are the U14's performing better comparatively than the olders? I wonder what's significantly different (if anything) from the trainings/scrimmages than the results of recorded games. For what it's worth, I haven't seen it with clubs we've been involved with. The stronger teams (by SR, by standings bracket, by everything) tend to perform well during any intraclub events as well, there aren't any real surprises where a team is unexpectedly strong (or weak).

Awhile back SR shared some of their predictivity stats, to gauge how well it was predicting results among games of various different groups:

Total cross-gender games with a win: 71.1% => Predictive power = 42.2%
Total cross-year games with a win: 84.0% => Predictive power = 68%

This was from a few seasons ago, so maybe things have shifted a bit. But for games between teams of different years, there was virtually no difference in predictivity compared to teams from the same year. It is still picking 5 of 6 games correctly.
 
I can see why MLS next HD teams are afraid to play in Surf tournaments because they are half a year younger. But I don’t understand why there aren’t more ECNL teams in Albion tournaments. They will make a killing in there.
I see quite a few ECNL clubs at Albion tournaments for youngers, but not so much for olders. I wonder if it's because of the college coach exposure. Surf Cup showed over 150 confirmed attending coaches whereas the Albion Showcase listed 7 coaches confirmed. With the events happening just a couple of weeks apart, there's really no incentive.
 
I see quite a few ECNL clubs at Albion tournaments for youngers, but not so much for olders. I wonder if it's because of the college coach exposure. Surf Cup showed over 150 confirmed attending coaches whereas the Albion Showcase listed 7 coaches confirmed. With the events happening just a couple of weeks apart, there's really no incentive.
Once ECNL teams get to U15 there's no need to go to tournaments. Between league play running Sep - Nov, high school soccer Nov - Feb, league resuming Mar - Jun, playoffs in Jun - July, scrimmages in Aug and two to three showcases/playoffs where you're traveling across the country there is no need for more games. ECNL teams can get their college exposure at their showcases. And no older ECNL team really wants to play Surf Cup right after coming off an 11-month season and playoffs.
 
You both realize you're arguing contradictory points and think that you're agreeing, right? One of you is saying that once a team plays outside the league, the results can/will affect everyone else that is within the league. The other is saying that when a team plays outside the league, the results don't count for enough.

You both can't be correct. For what it's worth, Carlsbad7 is closer to the truth.



Additional weight should be placed on games that better predict actual performance. Less weight should be placed on games that aren't as good at predicting actual performance. To your point - the results of games between teams that are close in rating are already more heavily weighted, than games between teams that are further apart from each other. How much weight isn't based on feels - it's based on how much weight results in the highest actual predictivity that can be achieved.



This is interesting, and I wonder why you're seeing that. How are the individual teams compared to their peer teams in other clubs - are the U14's performing better comparatively than the olders? I wonder what's significantly different (if anything) from the trainings/scrimmages than the results of recorded games. For what it's worth, I haven't seen it with clubs we've been involved with. The stronger teams (by SR, by standings bracket, by everything) tend to perform well during any intraclub events as well, there aren't any real surprises where a team is unexpectedly strong (or weak).

Awhile back SR shared some of their predictivity stats, to gauge how well it was predicting results among games of various different groups:



This was from a few seasons ago, so maybe things have shifted a bit. But for games between teams of different years, there was virtually no difference in predictivity compared to teams from the same year. It is still picking 5 of 6 games correctly.
I’m going to have to take my claim back: the older team usually borrows 3-4 star players from the younger team as full time starters
 
So I asked SR about interleague predictivity between MLSN, ECNL, GA, etc., and shared how there were those online who didn't believe there was enough interplay for the rating algorithm to work well. They've investigated the same topic as recently as this year. Here's what they found:

We studied this earlier this year and found that interleague predictions are just as good as intraleague predictions. The argument that leagues don't play each other enough doesn't match reality. Attached is a new analysis showing the level of inter-league play over the last 12 months. There are plenty of results to accurately calibrate the leagues' relative quality. Please feel free to share.

league-grid-boys.png
league-grid-girls.png
 
So I asked SR about interleague predictivity between MLSN, ECNL, GA, etc., and shared how there were those online who didn't believe there was enough interplay for the rating algorithm to work well. They've investigated the same topic as recently as this year. Here's what they found:
(10,622+627)/627 is roughly 18. So a boys mls next team would need to play 17 times other mls next teams before they get to play an ecnl team.
I would like to know why they think that’s enough inter league play for the algorithm to work.
 
(10,622+627)/627 is roughly 18. So a boys mls next team would need to play 17 times other mls next teams before they get to play an ecnl team.
I would like to know why they think that’s enough inter league play for the algorithm to work.
Some regional leagues are stacked with all good teams. Looking at a league in its entirety is like an average. There will be outliers. The outliers will be most noticeable on top clubs that only play other top clubs.

All this quickly will change when teams play against teams they dont normally play in Tournamants, Showcases, or Finals. Its also a good way to see that a feedback loop exists.
 
(10,622+627)/627 is roughly 18. So a boys mls next team would need to play 17 times other mls next teams before they get to play an ecnl team.
I would like to know why they think that’s enough inter league play for the algorithm to work.

If you really want to know things, you have to at least try and understand them when people explain them to you. Stubbornly continuing to believe falsehoods based on a lack of knowledge is a trait we all try to have our kids grow out of. If you have actual questions - ask them!

The required amount of interplay to calibrate effectively between leagues is much, much smaller than you believe is necessary. It's like Vitamin C. Have none for many months? Get scurvy and even die. But have as little as 10 mg every day or so, and you'll never have a problem. And a bit of it is supposed to be good for colds. So people take 250 mg. Or 500 mg. Some even take 1000 mg or 2000 mg thinking if a little is good, more must be better. But over a pretty low threshold, any more doesn't actually do anything (other than support supplement companies). People are just going to pee out any extra anyway.

Interplay is the same way. Enough interplay doesn't have to happen so it's as if it really is one pile of homogenous teams, all playing each other a roughly equal amount of times. A team gets it rating affected every time it plays another ranked team. It is affected by all of the opponents of its opponents. Even within a very small ("closed") group, they all are stratified by their results in a way that best represents the relative performance of the team. And once any of their opponents, or their opponents opponents, start to have game results from other populations - those results all have an effect on adjusting the ratings. In cases where the actual results are way off - that result moves ratings of all teams in the league much more quickly. In cases where the actual results are pretty close to expected - that result ends up not needing to adjust ratings much at all. It doesn't have to be any of the top teams playing outside. It doesn't have to be any of the bottom teams playing outside. Any/all of them will have the appropriate effect on the group and each other.

Some regional leagues are stacked with all good teams. Looking at a league in its entirety is like an average. There will be outliers. The outliers will be most noticeable on top clubs that only play other top clubs.

All this quickly will change when teams play against teams they dont normally play in Tournamants, Showcases, or Finals. Its also a good way to see that a feedback loop exists.

I just don't see how this is as impactful as you believe it to be, at least not for the reasons you're attributing. By the time it gets to playoffs/finals in these top leagues, there certainly is a dip in predictivity compared to regular season. It's now going from a full group of teams with skill A to skill Z, and cutting them down to a subgroup of teams with skill A to skill F. The relative differences between them are smaller - making the results that much harder to predict. It happens reliably, every season.

If one really wants to find a set of teams that all have a rating that is well off "reality", defined as the expected rating nationally for a team that is objectively performing at that level, they need to look at the very youngest teams when they are first established in brand new leagues. A town has a brand new set of teams in travel ball, say 8 of them, all U8. All of them have zero history, and all of them are starting to play nobody but each other. None of the teams have a rating at all. They all are given a hidden starting rating tied to their age. They start to play each other, and teams start to stratify themselves in the standings bracket. Once they've played 5 or 6 games, the ability to calculate expected performance becomes statistically significant, and they start to pop in to the Ranked teams rather than Unranked. If at this point, there still have been 48 games played, with zero extra tournaments or anything else in any of their histories, then the teams themselves are the only ones that can directly affect their rating.

But even so - if you take the average score for that entire league, and compare it to the average score for the entire league of the town next door and their U8 teams - it's likely to still be awfully close, as 8 year old kids here as a group are pretty similar to 8 year old kids over there as a group. Playing in the small closed league may be seen as a feedback loop by some definitions - but it's not a feedback loop that continues to emphasize incorrect or unwanted information (like a feedback loop in a mic/speaker that results in those high frequency squeals).

For this same thing to happen in a regional league at the older level, when more people might agree that ratings/rankings could be perceived as more valuable, it would have to be made up of all entirely new teams - with zero history among all of them. All of the teams would have to have been started with a generic rating, and none of them would have played any games outside of that brand new league. I'm sure that it happens from time to time, perhaps at the U13 age when new teams are established, but it's a fairly limited time span before the collective game history across all teams gets wide enough to bring things in line as needed. And once it does - it's not like that calibration goes away in a short time and needs to be "rebuilt". The continued results of the team continue to adjust the rating each game, and they survive season over season rather than having to start from scratch every 6 months.
 
If you really want to know things, you have to at least try and understand them when people explain them to you. Stubbornly continuing to believe falsehoods based on a lack of knowledge is a trait we all try to have our kids grow out of. If you have actual questions - ask them!

The required amount of interplay to calibrate effectively between leagues is much, much smaller than you believe is necessary. It's like Vitamin C. Have none for many months? Get scurvy and even die. But have as little as 10 mg every day or so, and you'll never have a problem. And a bit of it is supposed to be good for colds. So people take 250 mg. Or 500 mg. Some even take 1000 mg or 2000 mg thinking if a little is good, more must be better. But over a pretty low threshold, any more doesn't actually do anything (other than support supplement companies). People are just going to pee out any extra anyway.

Interplay is the same way. Enough interplay doesn't have to happen so it's as if it really is one pile of homogenous teams, all playing each other a roughly equal amount of times. A team gets it rating affected every time it plays another ranked team. It is affected by all of the opponents of its opponents. Even within a very small ("closed") group, they all are stratified by their results in a way that best represents the relative performance of the team. And once any of their opponents, or their opponents opponents, start to have game results from other populations - those results all have an effect on adjusting the ratings. In cases where the actual results are way off - that result moves ratings of all teams in the league much more quickly. In cases where the actual results are pretty close to expected - that result ends up not needing to adjust ratings much at all. It doesn't have to be any of the top teams playing outside. It doesn't have to be any of the bottom teams playing outside. Any/all of them will have the appropriate effect on the group and each other.



I just don't see how this is as impactful as you believe it to be, at least not for the reasons you're attributing. By the time it gets to playoffs/finals in these top leagues, there certainly is a dip in predictivity compared to regular season. It's now going from a full group of teams with skill A to skill Z, and cutting them down to a subgroup of teams with skill A to skill F. The relative differences between them are smaller - making the results that much harder to predict. It happens reliably, every season.

If one really wants to find a set of teams that all have a rating that is well off "reality", defined as the expected rating nationally for a team that is objectively performing at that level, they need to look at the very youngest teams when they are first established in brand new leagues. A town has a brand new set of teams in travel ball, say 8 of them, all U8. All of them have zero history, and all of them are starting to play nobody but each other. None of the teams have a rating at all. They all are given a hidden starting rating tied to their age. They start to play each other, and teams start to stratify themselves in the standings bracket. Once they've played 5 or 6 games, the ability to calculate expected performance becomes statistically significant, and they start to pop in to the Ranked teams rather than Unranked. If at this point, there still have been 48 games played, with zero extra tournaments or anything else in any of their histories, then the teams themselves are the only ones that can directly affect their rating.

But even so - if you take the average score for that entire league, and compare it to the average score for the entire league of the town next door and their U8 teams - it's likely to still be awfully close, as 8 year old kids here as a group are pretty similar to 8 year old kids over there as a group. Playing in the small closed league may be seen as a feedback loop by some definitions - but it's not a feedback loop that continues to emphasize incorrect or unwanted information (like a feedback loop in a mic/speaker that results in those high frequency squeals).

For this same thing to happen in a regional league at the older level, when more people might agree that ratings/rankings could be perceived as more valuable, it would have to be made up of all entirely new teams - with zero history among all of them. All of the teams would have to have been started with a generic rating, and none of them would have played any games outside of that brand new league. I'm sure that it happens from time to time, perhaps at the U13 age when new teams are established, but it's a fairly limited time span before the collective game history across all teams gets wide enough to bring things in line as needed. And once it does - it's not like that calibration goes away in a short time and needs to be "rebuilt". The continued results of the team continue to adjust the rating each game, and they survive season over season rather than having to start from scratch every 6 months.
I dont understand why you keep arguing that just because you think something is insignificant that it doesnt exist.

As top teams get older they retreat into whichever closed league they participate in more and more. Ive seen around 5 ranking swings when teams that usually play in a closed regional league suddenly play against teams outside of the
he loop. Maybe this is insignificant to you but I think its noticeable.

I also dont think its that big of a deal. With more cross league play the less feedback loops are seen. Big clubs live and and die on ranking when it comes to recruiting. Does 5 rankings reallly matter? Yes and no.
 
If you really want to know things, you have to at least try and understand them when people explain them to you. Stubbornly continuing to believe falsehoods based on a lack of knowledge is a trait we all try to have our kids grow out of. If you have actual questions - ask them!

The required amount of interplay to calibrate effectively between leagues is much, much smaller than you believe is necessary. It's like Vitamin C. Have none for many months? Get scurvy and even die. But have as little as 10 mg every day or so, and you'll never have a problem. And a bit of it is supposed to be good for colds. So people take 250 mg. Or 500 mg. Some even take 1000 mg or 2000 mg thinking if a little is good, more must be better. But over a pretty low threshold, any more doesn't actually do anything (other than support supplement companies). People are just going to pee out any extra anyway.
Why would I listen to a guy who doesn’t have the source code and isn’t named Mark? You have to come up with a better explanation than Vitamin C. Those of us who took statistic classes know about sample size and how it affects the confidence level. Relying on 1 out of 18 games to “adjust” inter group ranking doesn’t sound right.
 
I dont understand why you keep arguing that just because you think something is insignificant that it doesnt exist.

As top teams get older they retreat into whichever closed league they participate in more and more. Ive seen around 5 ranking swings when teams that usually play in a closed regional league suddenly play against teams outside of the
he loop. Maybe this is insignificant to you but I think its noticeable.

I also dont think its that big of a deal. With more cross league play the less feedback loops are seen. Big clubs live and and die on ranking when it comes to recruiting. Does 5 rankings reallly matter? Yes and no.

What does "5 ranking swings" mean? A team was off by 5 goals? 5 times you saw a team that played in a tournament had their rating adjusted? 5 times you saw that a regional league was all off by a lot until a team went to a tournament?

I'll agree with your statement that big clubs live and die on ranking due to recruiting - what I continue to disagree with is that the closed system is giving them a noticeable, repeatable, "artificial" rating compared to what you've determined to be a more "fair" rating. Which clubs/teams? Point to 1 of the 5 examples! Show how they used to have a rating of X, but their real rating turned out to be Y. There very well may be a conspiracy to make sure those with the $ and power keep as much of it as possible while locking out those on the other side of the fence - it's just that SR isn't a relevant reason or result that allows them to do it.
 
Why would I listen to a guy who doesn’t have the source code and isn’t named Mark? You have to come up with a better explanation than Vitamin C. Those of us who took statistic classes know about sample size and how it affects the confidence level. Relying on 1 out of 18 games to “adjust” inter group ranking doesn’t sound right.
Congrats. You don't want to compare statistics classes, rest assured I'm covered. On the other hand, you've posted an unending stream of poorly thought out conspiracy theories ever since you've joined the board. At least you've been consistent.

They can directly validate any and all of the ratings, across all unique/different populations, by looking at the end result for that group - predictivity. It's not a very large quantity of interplay that is necessary to keep that predictivity high enough to be statistically significant.

You're welcome, and encouraged, to message SR and talk over the details with them, assuming they're patient enough to deal with you.
 
What does "5 ranking swings" mean? A team was off by 5 goals? 5 times you saw a team that played in a tournament had their rating adjusted? 5 times you saw that a regional league was all off by a lot until a team went to a tournament?

I'll agree with your statement that big clubs live and die on ranking due to recruiting - what I continue to disagree with is that the closed system is giving them a noticeable, repeatable, "artificial" rating compared to what you've determined to be a more "fair" rating. Which clubs/teams? Point to 1 of the 5 examples! Show how they used to have a rating of X, but their real rating turned out to be Y. There very well may be a conspiracy to make sure those with the $ and power keep as much of it as possible while locking out those on the other side of the fence - it's just that SR isn't a relevant reason or result that allows them to do it.
Watch a regional league with mostly highly ranked teams before and after finals or a big showcase with teams they dont play as much.
 
Congrats. You don't want to compare statistics classes, rest assured I'm covered. On the other hand, you've posted an unending stream of poorly thought out conspiracy theories ever since you've joined the board. At least you've been consistent.

They can directly validate any and all of the ratings, across all unique/different populations, by looking at the end result for that group - predictivity. It's not a very large quantity of interplay that is necessary to keep that predictivity high enough to be statistically significant.

You're welcome, and encouraged, to message SR and talk over the details with them, assuming they're patient enough to deal with you.

What does "5 ranking swings" mean? A team was off by 5 goals? 5 times you saw a team that played in a tournament had their rating adjusted? 5 times you saw that a regional league was all off by a lot until a team went to a tournament?

I'll agree with your statement that big clubs live and die on ranking due to recruiting - what I continue to disagree with is that the closed system is giving them a noticeable, repeatable, "artificial" rating compared to what you've determined to be a more "fair" rating. Which clubs/teams? Point to 1 of the 5 examples! Show how they used to have a rating of X, but their real rating turned out to be Y. There very well may be a conspiracy to make sure those with the $ and power keep as much of it as possible while locking out those on the other side of the fence - it's just that SR isn't a relevant reason or result that allows them to do it.
What makes a more convincing NBA champion? A team that won a one game NBA final or a team that won a 7 game NBA final?

I don’t know why you get so offended. Nobody is attacking SR. It’s not their fault their samples don’t play each other.
 
Watch a regional league with mostly highly ranked teams before and after finals or a big showcase with teams they dont play as much.
Are you talking about like one of the ECNL-RL leagues, as a "regional" league, or do you mean regional as in Southwest ECNL is a region compared to Midwest ECNL? At any of the top levels, where the rating/ranking would matter for recruiting - I just don't see as much ratings movement as you're describing. At the lower levels? Maybe, I saw it this year when looking at teams in a league in WI that appeared to have wonky ratings, which all changed significantly once the proper new data sources were added.

What makes a more convincing NBA champion? A team that won a one game NBA final or a team that won a 7 game NBA final?
That's a completely different question, that has very little to do with the topic. Is the Superbowl champion the "best" football team, or is it instead the team that won the most games that season? Is the "best" batter the one with the highest batting average, or the one with the most home runs? Anyone can come up with any number of equally valid opinions about what makes a more convincing champion.

SR rates teams on exactly one and only one factor - is this team predicted to beat that team right now, based on their game history. The more games it gets right, the more accurate the predictions can be assumed to be. At this point, by all measures it's very accurate. That's what the entire system was developed for, so tournament directors could more fairly flight teams to promote closer competition and avoid blowouts. Yes - those same ratings can be put in a list and ranked locally/regionally/nationally. But that's never been the main focus. Nobody has to accept that definition as the list of the "best" teams in order, any more than they need to accept the rankings put up by ECNL power rankings, TopSoccer, GotSport, or any other system that has put together their own belief on what constitutes the "best" teams/clubs. Proposing that SR needs to change their rating/ranking algorithm to make it "more accurate" is, as stated several times already, a bad idea that doesn't understand what's already going on.

I don’t know why you get so offended. Nobody is attacking SR. It’s not their fault their samples don’t play each other.
You forget the drivel that you've posted on this board, much of it attacking me unnecessarily. As long as you continue to post misleading, useless, or otherwise incorrect "thoughts" up here publicly, expect everyone to read them, and some to be called out appropriately.
 
Are you talking about like one of the ECNL-RL leagues, as a "regional" league, or do you mean regional as in Southwest ECNL is a region compared to Midwest ECNL? At any of the top levels, where the rating/ranking would matter for recruiting - I just don't see as much ratings movement as you're describing. At the lower levels? Maybe, I saw it this year when looking at teams in a league in WI that appeared to have wonky ratings, which all changed significantly once the proper new data sources were added.


That's a completely different question, that has very little to do with the topic. Is the Superbowl champion the "best" football team, or is it instead the team that won the most games that season? Is the "best" batter the one with the highest batting average, or the one with the most home runs? Anyone can come up with any number of equally valid opinions about what makes a more convincing champion.

SR rates teams on exactly one and only one factor - is this team predicted to beat that team right now, based on their game history. The more games it gets right, the more accurate the predictions can be assumed to be. At this point, by all measures it's very accurate. That's what the entire system was developed for, so tournament directors could more fairly flight teams to promote closer competition and avoid blowouts. Yes - those same ratings can be put in a list and ranked locally/regionally/nationally. But that's never been the main focus. Nobody has to accept that definition as the list of the "best" teams in order, any more than they need to accept the rankings put up by ECNL power rankings, TopSoccer, GotSport, or any other system that has put together their own belief on what constitutes the "best" teams/clubs. Proposing that SR needs to change their rating/ranking algorithm to make it "more accurate" is, as stated several times already, a bad idea that doesn't understand what's already going on.


You forget the drivel that you've posted on this board, much of it attacking me unnecessarily. As long as you continue to post misleading, useless, or otherwise incorrect "thoughts" up here publicly, expect everyone to read them, and some to be called out appropriately.
I dont talk about specific leagues anymore. Its all the same pay to play. Theres just different levels and groups within. At the highest levels its easiest to identify anomalies because everything is on the line and the have and have nots becomes more clear.

But, the last time I was watching closely I noticed it in specific regional leagues that were part of a larger league when everyone played each other in finals. I also noticed it when you compare a state like California vs Nebraska. The big takeaway is that to artificially inflate rankings a little, a single group of teams have to be high level and nobody can play outside the group.
 
I dont talk about specific leagues anymore. Its all the same pay to play. Theres just different levels and groups within. At the highest levels its easiest to identify anomalies because everything is on the line and the have and have nots becomes more clear.

But, the last time I was watching closely I noticed it in specific regional leagues that were part of a larger league when everyone played each other in finals. I also noticed it when you compare a state like California vs Nebraska. The big takeaway is that to artificially inflate rankings a little, a single group of teams have to be high level and nobody can play outside the group.
What impresses me more than anything else is how leagues and clubs exploit every possible advantage no matter how small they are. People sometimes have the perception that sports people are dumb. I dont think this is the case. Maybe everyone just has a lot of time to think about how to tilt everything in clubs/leagues favor when players are kicking a ball around on a field 2 hours a day.
 
What’s better, SR curve fit/adjust against outsiders 1 time out of 18 chances or 5 times out of 18? Junk in junk out. You can be good at curve fitting working with junk data. Again not SR’s fault they don’t have nice large randomized data points to work with.
 
What’s better, SR curve fit/adjust against outsiders 1 time out of 18 chances or 5 times out of 18? Junk in junk out. You can be good at curve fitting working with junk data. Again not SR’s fault they don’t have nice large randomized data points to work with.
You're misunderstanding and misrepresenting the problem, and coming up with an inaccurate conclusion. Couple things that you should think through:
  • All teams - in all sets - that have enough game data to be classed as ranked are already statistically significant enough to predict future game performance within the chosen confidence interval
  • All teams - in all sets - that have enough game data to be classed as ranked are already gapped appropriately
  • None of these results are groups of random data, they are all specific results to games that have already happened
  • None of these results are junk data, they are all specific results to games that have already happened
  • If two sets are in any way out of balance, any movement between them will serve to bring them closer. The further apart they are/were, the faster it will happen
  • Curve fitting is exactly what they are doing, and the better it's done the better the predictions can be
  • The quality of the predictions can be directly and objectively measured by the resulting predictivity
Look, here's the conclusion that you just aren't coming to. They've been working on this for years to identify any signals they can get from the data to provide a better answer. Pretty much anything that you could conceive of, it's been tried a million different ways over many years. But even if that weren't true - and in fact you've come up with a method using the existing and available data that would allow them to better predict a result (and come up with a better rating) - they'd be ecstatic about it and would be happy to try and implement it. I've had them run cases before on ideas I've had, and some of the results have been both unintuitive and surprising.
 
You're misunderstanding and misrepresenting the problem, and coming up with an inaccurate conclusion. Couple things that you should think through:
  • All teams - in all sets - that have enough game data to be classed as ranked are already statistically significant enough to predict future game performance within the chosen confidence interval
  • All teams - in all sets - that have enough game data to be classed as ranked are already gapped appropriately
  • None of these results are groups of random data, they are all specific results to games that have already happened
  • None of these results are junk data, they are all specific results to games that have already happened
  • If two sets are in any way out of balance, any movement between them will serve to bring them closer. The further apart they are/were, the faster it will happen
  • Curve fitting is exactly what they are doing, and the better it's done the better the predictions can be
  • The quality of the predictions can be directly and objectively measured by the resulting predictivity
Look, here's the conclusion that you just aren't coming to. They've been working on this for years to identify any signals they can get from the data to provide a better answer. Pretty much anything that you could conceive of, it's been tried a million different ways over many years. But even if that weren't true - and in fact you've come up with a method using the existing and available data that would allow them to better predict a result (and come up with a better rating) - they'd be ecstatic about it and would be happy to try and implement it. I've had them run cases before on ideas I've had, and some of the results have been both unintuitive and surprising.
I would like to see the before the game prediction of the 627 mls next vs ecnl games. Then the game prediction of mls next vs mls next games. If there is indeed enough cross pollination, the predictiveness for these two sets should be the same.
 
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