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Thread: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

  1. #421
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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    I'm not sure how to do the analysis of this data, but in regard to regionals, starting in 2006 and not including 2019,
    #1s are 31-21 in round one
    #2s are 27-25, with slightly better records in the last 7 years than before then.

    This set of numbers seems to make sense in a sort of a way.....There should be little difference between 2s and 3s, given that it's often true in the final PWR that one game result different (which isn't much - just one fluky goal) can make the difference in seeding a 2 or a 3.
    More parity, since !s are not dominant, for sure.

  2. #422
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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    One game can move a team from a 3 to a 1. Itís not unheard of. Even recently.

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by dxmnkd316 View Post
    One game can move a team from a 3 to a 1. It’s not unheard of. Even recently.
    I agree completely. The real truth is that hockey is a game of very small margins, usually. The real truth is that there is NO WAY to really judge the most deserving 16 teams. All kinds of things enter in....player injuries, single goal games, penalty calls which were not correct, etc.....

    Considering that, it seems correct in my view to say this:
    There is no perfect system.
    The conferences make money from their tournaments. Without the tournament AQ, that disappears.
    The current system considers SOS in a way which, although not the abject best, comes close and is in some way understandable. (KRACH or KASA do better, but are too math-y for the common fan).
    Thus, for choosing the 16 teams, I don't think there is a good argument that what is in place is a broken system.

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    I'm arguing it because hockey might be the most random of any sports in terms of the outcome of a single game. Its low scoring nature means you get a decent number of upsets on any given night and even NHL teams that traded away all their talent like the Sens have a decent shot at winning a game vs a 100+ point team like the Leafs on any given night. So I just think there's a better way to do it.

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by trixR4kids View Post
    I'm arguing it because hockey might be the most random of any sports in terms of the outcome of a single game. Its low scoring nature means you get a decent number of upsets on any given night and even NHL teams that traded away all their talent like the Sens have a decent shot at winning a game vs a 100+ point team like the Leafs on any given night. So I just think there's a better way to do it.
    Would you mind fleshing out your system? And, describing why it is better?

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by Numbers View Post
    Would you mind fleshing out your system? And, describing why it is better?
    Just generally speaking I would think a better way of examining parity would be to figure out how many different teams are making the tournament (without an autobid) as a percentage of all NCAA teams and comparing that to the pre-2005 percentage. Like if the same schools (Like say the Boston schools, UMN, WI, Michigan) were constantly making it before 2005 and now you have more teams like UMass, Providence, and UNO making it, there's probably a way to measure this and find out how much parity has changed since then. In order to truly measure parity you need to look at how successful teams are over the course of a 40 (or so) game season and see if there's a greater variety of teams having success (measured via PWR or KRACH perhaps) than pre-2005.

  7. #427
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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    I have KRACH calculated back to 1900.

    Itís a MASSSIVE spreadsheet. Took me forever to figure out how to do it efficiently.
    Last edited by dxmnkd316; 04-06-2019 at 01:55 PM.

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by dxmnkd316 View Post
    I have KRACH calculated back to 1900.

    It’s a MASSSIVE spreadsheet. Took me forever to figure out how to do it efficiently.
    Considering that I have one for the NHL, which I can update season by season, and I know how detailed it is, I can hardly imagine yours. Must have 70 teams or better. Do you have all the games for 100+years included so there is a 'full history' KRACH metric you can derive?

    Not sure what you mean by "since 1900".

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by Numbers View Post
    Considering that I have one for the NHL, which I can update season by season, and I know how detailed it is, I can hardly imagine yours. Must have 70 teams or better. Do you have all the games for 100+years included so there is a 'full history' KRACH metric you can derive?

    Not sure what you mean by "since 1900".
    If it can be put in a spreadsheet, dx will have it. Guaranteed.
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  10. #430
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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by Numbers View Post
    Considering that I have one for the NHL, which I can update season by season, and I know how detailed it is, I can hardly imagine yours. Must have 70 teams or better. Do you have all the games for 100+years included so there is a 'full history' KRACH metric you can derive?

    Not sure what you mean by "since 1900".
    I have it setup with a toggle switch to punch out seasons or do a running total as well.

    Because games pre-1900 are spotty records at best. And Iíve done the best I can to find all games. The problem is I know Iím missing some. Itís very difficult to understand when teams were playing exhibitions or what happens when teams changed names and I didnít know.

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by The Rube View Post
    If it can be put in a spreadsheet, dx will have it. Guaranteed.


    Even if it canít....

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    A couple of questions for you, dx:

    1. What is the purpose of going all the way back to 1900? The game has changed so much, and many schools didn't even field teams, so I'm just wondering what's the point of including those very early results.

    2. Would it be easy to run the numbers taking into account just a portion of the current season, i.e. say the games played after the December break? Heading into the post season this would give you a good idea as to which teams are "hot", or "not" (vs. the PairWise which places as much weight on the very early season results as the latest).
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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by Koho View Post
    Another contributor is mentioned in the article that I don't think many people talk about is the apparent increase in talent pool. There seems to be more talented kids to go around. Not just due to the rise in other states. I was talking to a friend about some HS players who are destined for D1 teams didn't seem to stand out that much. And we both seemed to recollect that kids who went on to play D1 20 and 30 years ago seemed to stand out from the rest of the players on the ice pretty quickly, whereas now it seems like it is more like a shift here or there you notice them. Maybe it is poor memory, but it seems kids today are better trained and there is more depth, at that level, which would translate into colleges who get the first choice of kids would have less of a talent gap than the rest. And I would argue that the fact that about a third of NHL players come from NCAA now would support that. (Although this could also be due to more talented kids just choosing the NCAA route too, but there seems to be more Minnesotans in the NHL as well.) Add in the fact that the kids who ARE clearly more talented than the average will leave early, and one can see why this would contribute to parity.


    As for the one and done influencing stats, if all you are doing is looking at win percentages in all games, how does that influence the stats? And even if you want to look at number of championships by seeding, or mean seed of Champion from a period pre CBA to post, while the sample would be small, even with the confounding effect I would expect one would see a trend towards an increase in low seeds winning. (Keep in mind, it was one and done pre and post CBA.)

    I have moved into a different position, but in my previous position did some stats on biological data. While you can talk about ideal sample sizes and having perfect design, you can never create a perfect statistical sampling method, as you are sampling highly variable ever changing systems. If you held to rigid rules of statistical agreement, you would never conclude anything. The bar for statistical significance was lower than in other fields. What you typically were looking at were trends, not conclusive answers. And even though some people might argue the statistical significance of a conclusion, it was the best you could do in many situations. That did not mean the conclusions were wrong and the decisions we made were incorrect. SO if there are trends in number of 4 seeds winning games against #1 and trends in increasing low seeds winning it all, I will believe there is a good chance they represent reality. So go ahead and do stats on a better data set if you like. I don't need to. I think most people sense the shift that has occurred. Some of that is based on the observations I have mentioned. So why do some people feel the need to criticize such an approach without offering a better analysis? (And most people don't care about the details of stats and just want to discuss what they are seeing.) Argue if you think that there is not more parity in the league and offer your supporting observation. Buy why agree with my point but argue about the way I chose to show it? Does anyone think there isn't more parity now?
    Scouts and D1 coaches on and off the ice look for the small things. For example, if your kid doesn't have a dad in his life many of the teams will pass on him as he might be problem in the locker room and likely not a leader. Kids like this don't win championships but character kids do. Are the players playing other sports like tennis or golf? The multi star athlete likely will be great or very good at other sports. For example, look at Joe Mauer. Also, hockey sense might be the most important skill a hockey player can have. Is he out of position, is his stick in the right position at all times and does he take away space effectively. Finally, the best players have the acceleration from stop to go and back to stop again in seconds, it's basically an all around consistent skater.
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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by D2D View Post
    A couple of questions for you, dx:

    1. What is the purpose of going all the way back to 1900? The game has changed so much, and many schools didn't even field teams, so I'm just wondering what's the point of including those very early results.

    2. Would it be easy to run the numbers taking into account just a portion of the current season, i.e. say the games played after the December break? Heading into the post season this would give you a good idea as to which teams are "hot", or "not" (vs. the PairWise which places as much weight on the very early season results as the latest).
    1. I had the data, so why not?

    2. Yes

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by dxmnkd316 View Post
    1. I had the data, so why not?

    2. Yes
    What exactly are you trying to figure out? One of the discussions centered on if there has been a change in parity since the new CBA, combined with the shift (around early to mid-200's) towards recruiting at an earlier and earlier age. I have no idea how recruiting went in the early years of hockey (and we know there was a stretch where Denver just brought in older Canadians) so why not start at around 1970? If you are not going to look at that question, what are you trying to analyze?

  16. #436
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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    I was just curious. There wasnít a reason.

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by trixR4kids View Post
    Just generally speaking I would think a better way of examining parity would be to figure out how many different teams are making the tournament (without an autobid) as a percentage of all NCAA teams and comparing that to the pre-2005 percentage. Like if the same schools (Like say the Boston schools, UMN, WI, Michigan) were constantly making it before 2005 and now you have more teams like UMass, Providence, and UNO making it, there's probably a way to measure this and find out how much parity has changed since then. In order to truly measure parity you need to look at how successful teams are over the course of a 40 (or so) game season and see if there's a greater variety of teams having success (measured via PWR or KRACH perhaps) than pre-2005.
    If you're interested in mathematical modeling for predictive purposes, the best approach is multivariate multiple regression model with at least two criterion and several predictor variables. Depending on how much accuracy you'd like the results to represent, you may want to control for various covariates (eg. playoff experience, SOS, offensive and defensive ratings, etc.).

    If you want to research the comparison of teams between pre-2006 and post-2006 then a methodology using a t-test (including for example a Bonferroni adjustment) and two-way ANOVA is sufficient to compare the pre and post-2006 results against your hypothesis.

  18. #438
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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by SteveO View Post
    If you're interested in mathematical modeling for predictive purposes, the best approach is multivariate multiple regression model with at least two criterion and several predictor variables. Depending on how much accuracy you'd like the results to represent, you may want to control for various covariates (eg. playoff experience, SOS, offensive and defensive ratings, etc.).

    If you want to research the comparison of teams between pre-2006 and post-2006 then a methodology using a t-test (including for example a Bonferroni adjustment) and two-way ANOVA is sufficient to compare the pre and post-2006 results against your hypothesis.
    Makes sense, I didn't have as much exposure to multivariate regression in school but I can see how that'd be useful. And you're right I was gonna say something about controlling for SOS because of teams like ASU this season.

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by trixR4kids View Post
    Makes sense, I didn't have as much exposure to multivariate regression in school but I can see how that'd be useful. And you're right I was gonna say something about controlling for SOS because of teams like ASU this season.
    It's multivariate because you need two criterion or dependent variables to test the hypothesis. To do this right with a high internal validity and reliability, this project would involve quite a bit of data collection. As you stated, the single elimination format lends itself to a degree of randomness. One bad night for a favorite or one stellar night from an underdog can lead to the inevitable upset. So this research would need to focus heavily on the perceived differences between the NCAA tournament and the NCAA regular season.

    I think it's good research project though. If you're interested in pursuing it, I'd be keen to help you crunch the data analysis using regression analysis (maybe logistic).

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    Re: Minnesota Golden Gopher Season 2018-2019: Fire Motzko

    Quote Originally Posted by SteveO View Post
    It's multivariate because you need two criterion or dependent variables to test the hypothesis. To do this right with a high internal validity and reliability, this project would involve quite a bit of data collection. As you stated, the single elimination format lends itself to a degree of randomness. One bad night for a favorite or one stellar night from an underdog can lead to the inevitable upset. So this research would need to focus heavily on the perceived differences between the NCAA tournament and the NCAA regular season.

    I think it's good research project though. If you're interested in pursuing it, I'd be keen to help you crunch the data analysis using regression analysis (maybe logistic).
    You need to stop talking approaches and just team up with MR. Spreadsheet (dxmn) to have him hand you the data you need and just do it.

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