Flames & Team Metrics (Analytics)

[squiggs96]

Originally Posted by DeluxeMoustache

This leads to a question about what the whole value of the statistical analysis is, though

Originally Posted by Bingo

It's counting. Counting isn't a model. Summarizing a bunch of counting stats isn't a model, its a summary.


I'm just summarizing that ... it's not a model.

When what's the point of all the counting? In the first post you state that you want to be above the red line in each case. FanIn80 points out that Calgary was above the red line in games the Flames lost (one of them a 9-1 defeat) and below the line in games they won handily. There were explanations on why the data didn't match the final score.

So, I will go back to my original question. What's the point of all the counting? I don't mean the question in a snarky way. I actually want to know the point. If all of the counting leads to all of the graphs, and the counting and graphs don't match up with winning or losing in the NHL, then what's the point? It seems the point of counting is just to do some counting. If you could do the counting for the metrics, and then it would be able to reasonably predict something, then there is value in the counting. There should be a cause and effect or correlation from the counting to results.

In your chart there are 17 games The green line is above the red line 14 times. During those 14 games the Flames record was 8-5-1. Of the 3 times the green line was below the red line the Flames won all 3 games. So here's my problem with this stat/metric/count: It doesn't correlate to anything. When the green line is below the red line the Flames have won 100% of the games. The point of hockey is to win games. If I'm coaching a hockey team I want my team to do things that will help us win games. If I see that we win 100% of the games when the green line is below the red line, I want our team doing this more often, because it will lead to more wins. If this is true, then the metric has value. In this case we have been told that the green line being below the red line is bad. We aren't supposed to be down there. We are told we want to be above the red line. However, when the green line is above the red line, Calgary only wins 57% of the games. If you tell me that I can play one way that has shown I have a 57% chance of winning or another way that has a 100% chance of winning, I'm going to go with the way that has a 100% chance of winning. However, what the metrics crowd has stated is that we want to follow the other path. We want to be on the other side of the red line, even though that doesn't lead to more wins. If this is the case, why are we counting? There is no value in counting something if it doesn't help predict something or tell you the story of what happened. It's simply an exercise in counting.

If you require an explanation on why everything is backwards from the output, then methodology of collecting the data in this specific way is flawed. The method of counting individual markers can be correct, but the output of displaying them can still be flawed. Let's suppose you were buying stocks and you believe the best stocks to buy are ones where the company has a P/E ratio of greater than 50% of the highest P/E ratio over the last 5 years. You go through all the companies and you find the companies that fit this metric. You buy these stocks and then notice the companies you've invested in have share prices that continue to decline. You've lost a lot of money and time. Would you still continue using this metric? Of course not. It does not predicatively lead to you picking good stocks to buy even though the raw data and counting is done perfectly. In this case you'd say the output has no bearing on future events, it doesn't explain what happened in the past, and it was simply an exercise in counting.

Why summarize these data points if it doesn't point to anything? Why not find data points that lead to more victories in the NHL? This is why advanced metrics work better in baseball than they do in hockey. In baseball you can find data on how many times a left handed hitter has hit the ball to the left side of the infield against any pitcher. You can use that data to shift, or not shift, the infield's defence to the right side. Of course the batter may still put the ball where you don't want it to go on occasion, but more often than not, the stats can be used as a predictive tool. If they weren't useful in predicting something, they wouldn't be used. Looking at the green line, it's not predicting anything, nor is it explaining anything. It's just a line that doesn't correlate or correspond to anything.

[Resolute 14]

Originally Posted by squiggs96

So, I will go back to my original question. What's the point of all the counting? I don't mean the question in a snarky way. I actually want to know the point. If all of the counting leads to all of the graphs, and the counting and graphs don't match up with winning or losing in the NHL, then what's the point? It seems the point of counting is just to do some counting. If you could do the counting for the metrics, and then it would be able to reasonably predict something, then there is value in the counting. There should be a cause and effect or correlation from the counting to results.

IMO, one problem is that one of the key aspects of how Corsi was used early on by analytics types has been lost: The relative relationship between possession/Corsi and winning is stronger with a large sample size. When there's 80-100 Corsi events in a game, and 3000+ in a season per team, you have enough data points to at least have a decent picture. Even if things we cannot or do not factor still create a larger margin of error.

But so much focus has been put on single games in the last couple years that we've eliminated one of the strengths of the stat. Especially since the effects of ignoring special teams becomes dramatic at the single game level.

Consequently, there is no correlation between winning and Corsi at the level of a single game. To wit, our record when....

CF% <= 40%: 2-0
CF% < 50%: 2-0-1
CF% >= 50%: 8-7-0
CF% >= 60%: 3-2-0

On the other hand, when we look only at the one thing analytics types typically ignore, special teams, we see a much stronger correlation:

When Flames win special teams: 5-2-0
When Flames lose special teams: 4*-4-1
When Flames tie special teams: 1-1-0

*Includes the Rangers win where we scored three goals on delayed penalties. Did not count as power play goals in the stats.

[Bingo]

Does this just happen after Flames losses? Sure seems that way.

I don't need direct causation in statistics to find them interesting. When a hockey team is doing well I love digging into the stats to see if what I'm seeing is being supported by data. If not I look again.

In my real job I trade energy futures. I look at things like old weather vs the forecast along with historical burn rates to try and justify or create a trade plan vs the current value in the future market.

None of these things are a direct causal relationship but they are indicative, and a good way to come up with a trade plan.

These charts show how the Flames generate simply shot attempts, scoring chances and high danger chances against the bubble team.

I like to think generating more is good. If you don't suite yourself.

The charts also show how the Flames defend against shot attempts, scoring chances and high danger chances vs the bubble team.

I like to think giving up less is good. If you don't suite yourself.

Not sure how much more I can say.

[Bingo]

Originally Posted by Resolute 14

IMO, one problem is that one of the key aspects of how Corsi was used early on by analytics types has been lost: The relative relationship between possession/Corsi and winning is stronger with a large sample size. When there's 80-100 Corsi events in a game, and 3000+ in a season per team, you have enough data points to at least have a decent picture. Even if things we cannot or do not factor still create a larger margin of error.

But so much focus has been put on single games in the last couple years that we've eliminated one of the strengths of the stat. Especially since the effects of ignoring special teams becomes dramatic at the single game level.

Consequently, there is no correlation between winning and Corsi at the level of a single game. To wit, our record when....

CF% <= 40%: 2-0
CF% < 50%: 2-0-1
CF% >= 50%: 8-7-0
CF% >= 60%: 3-2-0

On the other hand, when we look only at the one thing analytics types typically ignore, special teams, we see a much stronger correlation:

When Flames win special teams: 5-2-0
When Flames lose special teams: 4*-4-1
When Flames tie special teams: 1-1-0

*Includes the Rangers win where we scored three goals on delayed penalties. Did not count as power play goals in the stats.

Analytics types? That's kind of loaded isn't it?

And of course sample sizes get in the way, but they do with almost any stats. If you looked at out shooting opponents in a ten game stretch it may suggest you're better to take less shots, but that wouldn't be a good game plan.

The problem with your special teams argument is it's too simple. You're pointing to goal differential by saying "win the special teams", so yeah of course it's going to matter. Its like saying if you spot a team a lead you're going to lose more often than not ...

So it doesn't take an analytics type to see special teams is a separate discussion, and doesn't belong in a comparison any more than "on nights where your goalie out plays their goalie you win more often" ... once again ... no kidding!

[Resolute 14]

Ehh, somewhat loaded, but at the same time, accurate. Stat sites will include all the stats in special teams situations, but the analytics community as a whole routinely ignores everything that is not 5 on 5. I get some of the reasoning, notably that it equalizes for all teams, and that over the course of a season, it forms a far larger data set than 5v4, 4v4, etc. will.

Also, how does "too simple" represent a flaw? I don't see how more complicated, but with no correlation to wins and losses is better than less complicated but significant correlation. That being said, I do have to concede your point as you haven't, at any point, tied any of your data to wins and losses. So you are correct that determining what relates to success is a separate discussion.

[Bingo]

Originally Posted by Resolute 14

Ehh, somewhat loaded, but at the same time, accurate. Stat sites will include all the stats in special teams situations, but the analytics community as a whole routinely ignores everything that is not 5 on 5. I get some of the reasoning, notably that it equalizes for all teams, and that over the course of a season, it forms a far larger data set than 5v4, 4v4, etc. will.

Also, how does "too simple" represent a flaw? I don't see how more complicated, but with no correlation to wins and losses is better than less complicated but significant correlation. That being said, I do have to concede your point as you haven't, at any point, tied any of your data to wins and losses. So you are correct that determining what relates to success is a separate discussion.

You have to look at special teams, I do all the time.

But your example of winning special teams is giving one team a +1 or greater on the scoreboard to start and is too much of an advantage to be statistically significant.

It's not flawed ... it's too clearly connected to wins.

And thanks ... that's why I don't get the constant witch hunt I'm defending. I like my hockey team to give up less and generate more. It's not an equation that guarantees victories, but it's a great place to target the areas of the game that the team needs to focus on.

That's it.

[Resolute 14]

It's not a witch hunt, Bingo. You're just - by far - the most vocal advocate for these kinds of stats 'round here. It's only natural that when they, or how they are presented, are challenged, that you'll want to get further involved defending them.

[squiggs96]

Originally Posted by Bingo

Does this just happen after Flames losses? Sure seems that way.

I bet there are some stats and graphs for it.

Originally Posted by Bingo

I don't need direct causation in statistics to find them interesting. When a hockey team is doing well I love digging into the stats to see if what I'm seeing is being supported by data. If not I look again.

In my real job I trade energy futures. I look at things like old weather vs the forecast along with historical burn rates to try and justify or create a trade plan vs the current value in the future market.

None of these things are a direct causal relationship but they are indicative, and a good way to come up with a trade plan.

These charts show how the Flames generate simply shot attempts, scoring chances and high danger chances against the bubble team.

I like to think generating more is good. If you don't suite yourself.

The charts also show how the Flames defend against shot attempts, scoring chances and high danger chances vs the bubble team.

I like to think giving up less is good. If you don't suite yourself.

Not sure how much more I can say.

*suit, not suite

You can do whatever you want with your free time. You obviously don't need my permission for it. If you want to look at data, that don't correlate to wins or losses, then go ahead and do that if it floats your boat. What I'm getting at is that sometimes the CA60Vs16 will be above/below the red line when the Flames win/lose. There is no correlation between winning/losing and the position of the CA60Vs16 relative to the red line, and there are not indicative. You want them to be, but they aren't. When they don't go the way you expect them to, they are always explanations. That's not how statistics work. You aren't just counting and presenting. You are counting, presenting, and creating a narrative based on what you want them to show.

Here's how I'd work backwards to find stats that are useful. My end goal is to win the Stanley Cup. To give me the best possible road to achieve this objective I'd like to have the most points in the regular season. This will give me home ice advantage throughout the playoffs. In order to get the highest see I'll need the most points. In order to get the most points I'll (usually) need the most wins. In order to get the most wins I'll need X. It's debatable what X is. If I believe X is special team goal differential, I'll look at stats that will help me draft and trade for players that will help me achieve this metric. X isn't one thing, so X is likely X, Y, Z, etc. I rank these in order of importance to me, and start trying to build a roster.

The stats I'd find useful are ones that correlate to my end objective. If my stats nerds on my team kept bringing me stats that said I need to find players that did Y because it helped with a metric, but that metric didn't correlate to wins or losses over the course of a season, I'd tell them to stop wasting their, and my, time. Why tell me we need to be better in some area if it doesn't lead to wins, which is the point of hockey.

Let's suppose you think having high danger chances is a key component to winning. It might be. It sure sounds like it should. However, if you have a bunch of plugs, relative to other NHL players, getting high danger chances, what good is it doing? Sure you are getting some fancy stats, but it isn't achieving anything. To simply say the output is unlucky is not how stats work.

Now back to the charts. You think it is better to be above the red line, but the chart shows it's the opposite. That's not me creating advanced metrics, that's just me reading the outputs from the data that is counted. In the 17 games that have bar charts, I've been told it's better to be above the line. In post #31 of the thread in the first bar chart there are nine games where at least one of the bars is below the red line. The Flames are 6-2-1 in those games. If there truly was an indication or there was a correlation between this stat and winning and losing, then you'd have to think that you'd need to be above the line in order to win the majority of your games. In fact, the Flames captured 72% of the points with this happening. To me, that says there isn't a point in needing to be above the red line. In the same graph the two biggest grey bars are on games they got soundly beaten.

If the metric was truly a great metric is would be more closely aligned with wins and losses. You are free to think that you need to have more chances, possessions, shots, shots from certain angles, etc., is better, but when the data keeps being presented over and over, and it doesn't tie to results, I'm not sure what the point of it is. I'm also not sure how much more you can say. If you keep telling us that a team needs to rank favorably in a certain metric to be successful, but the data shows that's simply not true, it's time to see if the output is relevant.

[LWcrowfoot]

Originally Posted by Resolute 14

It's not a witch hunt, Bingo. You're just - by far - the most vocal advocate for these kinds of stats 'round here. It's only natural that when they, or how they are presented, are challenged, that you'll want to get further involved defending them.

In his thread with graphs that he made. Of course the majority of replies will be directed towards him. Puzzling response. Others are going to challenge these graphs, especially with how awkward they were initially. Have to accept that and can't brush them off as a witch hunt.

[squiggs96]

Originally Posted by Bingo

that's why I don't get the constant witch hunt I'm defending.

It's not a witch hunt. In this specific case this is a thread you started to discuss metrics, and the first sentence in this thread was you knew not everyone likes the graph. You have stated, multiple times, that you love being challenged, but when people, like myself, have disagreed with you, you tell us to go suit ourselves or float our boat. Me coming into a metrics thread and discussing metrics with you isn't a witch hunt. If we can't discuss metrics in a metrics thread, where else would we talk about them? And they aren't just in this thread. You are very vocal about your love for these metrics and they are in many of your posts in many threads. You can't create a thread about something, have us discuss it, and then call it a witch hunt. It didn't take much hunting to find it.



I think there is value in statistics and analytics. I have taken multiple advanced statistics courses in multiple fields of study in university. I understand the theory behind collecting, sorting, displaying, and interpreting statistics. I just don't think there is value in the outputs that come from the data collection you are defending. It's a difference of opinion that you said you welcome. However when you disagree with us, often we are told to fill our boots and suit ourselves. It's dismissive.

[Bingo]

Originally Posted by LWcrowfoot

In his thread with graphs that he made. Of course the majority of replies will be directed towards him. Puzzling response. Others are going to challenge these graphs, especially with how awkward they were initially. Have to accept that and can't brush them off as a witch hunt.

Wasn't talking about the graphs ... the general attack on advanced stats in general, especially as Resolute pointed out I'm not suggesting any true linkage at all.

I found the graphs interesting, if others don't that's fine and good.

Just trying to provide some summaries to generate discussion.

[Bingo]

Originally Posted by squiggs96

I bet there are some stats and graphs for it.




*suit, not suite

You can do whatever you want with your free time. You obviously don't need my permission for it. If you want to look at data, that don't correlate to wins or losses, then go ahead and do that if it floats your boat. What I'm getting at is that sometimes the CA60Vs16 will be above/below the red line when the Flames win/lose. There is no correlation between winning/losing and the position of the CA60Vs16 relative to the red line, and there are not indicative. You want them to be, but they aren't. When they don't go the way you expect them to, they are always explanations. That's not how statistics work. You aren't just counting and presenting. You are counting, presenting, and creating a narrative based on what you want them to show.

Here's how I'd work backwards to find stats that are useful. My end goal is to win the Stanley Cup. To give me the best possible road to achieve this objective I'd like to have the most points in the regular season. This will give me home ice advantage throughout the playoffs. In order to get the highest see I'll need the most points. In order to get the most points I'll (usually) need the most wins. In order to get the most wins I'll need X. It's debatable what X is. If I believe X is special team goal differential, I'll look at stats that will help me draft and trade for players that will help me achieve this metric. X isn't one thing, so X is likely X, Y, Z, etc. I rank these in order of importance to me, and start trying to build a roster.

The stats I'd find useful are ones that correlate to my end objective. If my stats nerds on my team kept bringing me stats that said I need to find players that did Y because it helped with a metric, but that metric didn't correlate to wins or losses over the course of a season, I'd tell them to stop wasting their, and my, time. Why tell me we need to be better in some area if it doesn't lead to wins, which is the point of hockey.

Let's suppose you think having high danger chances is a key component to winning. It might be. It sure sounds like it should. However, if you have a bunch of plugs, relative to other NHL players, getting high danger chances, what good is it doing? Sure you are getting some fancy stats, but it isn't achieving anything. To simply say the output is unlucky is not how stats work.

Now back to the charts. You think it is better to be above the red line, but the chart shows it's the opposite. That's not me creating advanced metrics, that's just me reading the outputs from the data that is counted. In the 17 games that have bar charts, I've been told it's better to be above the line. In post #31 of the thread in the first bar chart there are nine games where at least one of the bars is below the red line. The Flames are 6-2-1 in those games. If there truly was an indication or there was a correlation between this stat and winning and losing, then you'd have to think that you'd need to be above the line in order to win the majority of your games. In fact, the Flames captured 72% of the points with this happening. To me, that says there isn't a point in needing to be above the red line. In the same graph the two biggest grey bars are on games they got soundly beaten.

If the metric was truly a great metric is would be more closely aligned with wins and losses. You are free to think that you need to have more chances, possessions, shots, shots from certain angles, etc., is better, but when the data keeps being presented over and over, and it doesn't tie to results, I'm not sure what the point of it is. I'm also not sure how much more you can say. If you keep telling us that a team needs to rank favorably in a certain metric to be successful, but the data shows that's simply not true, it's time to see if the output is relevant.

When have I ever stated any thing is a great metric?

And what output? I've never stated anything is an output or is relevant? It's a summary of what they've done with no manipulation, hypothesis or projection at all.

It's pretty simple ... do more good things and do less bad things and you probably win more of those games than you lose.

Are you debating that?

[jayswin]

Originally Posted by Bingo

When have I ever stated any thing is a great metric?

And what output? I've never stated anything is an output or is relevant? It's a summary of what they've done with no manipulation, hypothesis or projection at all.

It's pretty simple ... do more good things and do less bad things and you probably win more of those games than you lose.

Are you debating that?

It's a little confusing though, Bingo. Your first sentence says you never state anything is an output, and that they're done with no manipulation, hypothesis or projection at all.

But then your next sentence says it's really simple, do more good things and less bad and you probably win more games than you lose. Assuming the "more good" and "less bad" is referring to your data than that is a hypothesis and/or projection, no?

And if so, I think that's what Squiggs and Res are taking issue with. It feels a little like you want them to mean more than they currently do, hence the frequent posts, but claim they aren't meant to say anything when you are challenged on them.

[Bingo]

Originally Posted by jayswin

It's a little confusing though, Bingo. Your first sentence says you never state anything is an output, and that they're done with no manipulation, hypothesis or projection at all.

But then your next sentence says it's really simple, do more good things and less bad and you probably win more games than you lose. Assuming the "more good" and "less bad" is referring to your data than that is a hypothesis and/or projection, no?

And if so, I think that's what Squiggs and Res are taking issue with. It feels a little like you want them to mean more than they currently do, hence the frequent posts, but claim they aren't meant to say anything when you are challenged on them.

Well that was meant as a statement to see if he agreed.

I assumed most would ... guess I was wrong.

Did I present a causal relationship between underlying stats and winning?

If this is the run around posting this stats is going to create I may just take a pass. Not worth it. Honestly thought I was providing good information for the site that beats the hell out of reams of data in a table.

[wingmaker]

LOL at Squiggs. I will make fun of you for spending your time looking at stats while I spend my time writing longwinded posts about why you are wrong.

Stats give you information about events that happen in games. Over time, you can look at patterns at what the data is showing and compare it to wins and losses, special teams events, how the play of certain players lines up with team performance, etc. It is a way of understanding what is happening in games on a granular level that balances out the "eye test".

You don't want to do that, don't do it. No need to dump on people who do.

[nik-]

Originally Posted by wingmaker

LOL at Squiggs. I will make fun of you for spending your time looking at stats while I spend my time writing longwinded posts about why you are wrong.

Stats give you information about events that happen in games. Over time, you can look at patterns at what the data is showing and compare it to wins and losses, special teams events, how the play of certain players lines up with team performance, etc. It is a way of understanding what is happening in games on a granular level that balances out the "eye test".

You don't want to do that, don't do it. No need to dump on people who do.

Except there's no pattern, which is the crux of his argument.

[wingmaker]

Originally Posted by nik-

Except there's no pattern, which is the crux of his argument.

Sure there is. It doesn't correlate to a game by game comparison, but in a larger subset there is, which Bingo explained. Which is just common sense. Everyone knows teams lose when they play well, win when they play poorly. Or get down and then pour it on but not in a meaningful way. This is why these types of stats are about larger sections of games, not individual games. This is exactly why a graph like Bingo's is interesting, because you can quickly look at it over a longer period rather than bogged down on a game by game basis.

Again, you don't think it is interesting, don't bother.

[squiggs96]

Originally Posted by Bingo

When have I ever stated any thing is a great metric?

Honest question: If it's not a great metric, then why discuss it and bring it up as frequently as you do? You have two threads you started that are on the front page discussing these metrics/analytics. It's in your game takes and a large number of your posts over the last year or so. Why would you spend so much time producing and defending something if you didn't think it was great?

Originally Posted by Bingo

And what output? I've never stated anything is an output or is relevant? It's a summary of what they've done with no manipulation, hypothesis or projection at all.

What output? The graphs are an output. The data comes from the games and you produce graphs, charts, and figures. Those are all outputs. Back to my question above: If it's not relevant, then why spend so much time producing and defending them? You clearly like advanced stats/metrics. That's your thing. I didn't say you manipulated them. You do have a hypothesis. Your hypothesis is somewhere along the lines of if you do more good things than bad things, you'll win more games. We disagree on what is a good thing, because I don't see much value in corsi. I don't think it's a good predictor of what will happen and I don't think you can look back and say that teams won or lost based on their corsi. What we have seen from the charts in this thread is that if you are above the red line with those metrics, you have a little better than 50% chance of winning the game. If that's the case, why not just flip a coin? If the stats can predict the future, and they can't shed light on why a team won or not, then what value is the statistic? I'm not saying the data is flawed, or the collection method is flawed/manipulated. I am saying the stats, in this case CA60Vs16, SCA60Vs16, and HDCA60Vs16 don't have a lot of value because they can't predict anything and don't substantially indicate whether the team won or lost. They have little more value than the GRIT index.

In your game takes you bring in a bunch of these stats. I don't know if they are the identical stats, but you have a fancy stats section in your game takes. Once again, the statistics are the output. In the last two game takes you reference, compare, contrast, and equate fancy stats to what happened on the ice. As a writer, why would you discuss these if they aren't relevant. You may not come out and say, word for word, that they are relevant, but by continuing to post threads, posts, and stories involving them, your actions are saying that they are relevant. By saying that you want the stats to be above the red line, or a certain figure, you are forming a hypothesis.

Originally Posted by Bingo

It's pretty simple ... do more good things and do less bad things and you probably win more of those games than you lose.

Are you debating that?

I'm not debating that. I'm debating what is a good thing and what is a bad thing. I don't believe the statistic of corsi, or any of the related statistics, are a good measure of things done well. You do. I can't change your mind on that. By you continuing to present these figures, you must believe that they are good statistics, and that you find them relevant, or you wouldn't keep presenting them. I don't bring up my elementary school science fair projects when discussing the Flames because they aren't relevant, even if they might be interesting. They have no bearing on whether the Flames will win or lose.

I would say that the greater your goal differential, the greater chances you'll be higher in the standings. You earn a greater goal differential by scoring more goals than the other team in a majority of games. A major part of the goal differential is from scoring on your powerplay and preventing them from scoring on your penalty kill. If you have a good PP and PK, I'd argue you win more games than you lose.

[nik-]

Originally Posted by wingmaker

Sure there is. It doesn't correlate to a game by game comparison, but in a larger subset there is, which Bingo explained. Which is just common sense. Everyone knows teams lose when they play well, win when they play poorly. Or get down and then pour it on but not in a meaningful way. This is why these types of stats are about larger sections of games, not individual games. This is exactly why a graph like Bingo's is interesting, because you can quickly look at it over a longer period rather than bogged down on a game by game basis.

Again, you don't think it is interesting, don't bother.

Ok, please point it out.

[squiggs96]

Originally Posted by wingmaker

LOL at Squiggs. I will make fun of you for spending your time looking at stats while I spend my time writing longwinded posts about why you are wrong.

Stats give you information about events that happen in games. Over time, you can look at patterns at what the data is showing and compare it to wins and losses, special teams events, how the play of certain players lines up with team performance, etc. It is a way of understanding what is happening in games on a granular level that balances out the "eye test".

You don't want to do that, don't do it. No need to dump on people who do.

I never once made fun of someone for spending time on stats. I even said he obviously doesn't need my permission to spend his time however he wants. I also said I've taken multiple advanced statistics classes, so I'm well versed in how they work. I didn't know spending five minutes typing a reply was long winded. I learned something new today.


My argument on this topic is there isn't a pattern of predictability from these measures. If you are saying you need more data to make up a bigger pattern, I can buy that. However, when you present one game, four game, and/or 17 game outputs that show the exact opposite of what you set out to prove, then the output is flawed. Why show it for one, four, or seventeen games if you need more data? Why not present it for 50, 60, 82 games? You might get more people on your side if you can show it's a greater predictor or indicator. Instead it gets presented showing opposite of the intention, and that's explained by it's luck/you need more data/you don't understand.