Questions for the statisticians on here

[boilerpt]

Where does Painter rank among B1G coaches in the last 10 years (record)?

 

[lbodel]

Where does Painter rank among B1G coaches in the last 10 years (record)?

Don't have those specifics, but in terms of active Big Ten coaches at their respective Big Ten school...

1. Thad Matta - 76.1% (393 games)
2. Bo Ryan - 74% (488 games)
3. Tom Izzo - 71.4% (697 games)
4. Matt Painter - 64.6% (341 games)
5. Mark Turgeon - 64% (139 games)
6. Richard Pitino - 61.3% (75 games)
7. John Beilein - 60.4% (278 games)
8. John Groce - 59.4% (106 games)
9. Fran Mccafferty - 56.9% (174 games)
10. Tom Crean - 52.5% (238 games)
11. Tim Miles - 50.5% (101 games)
12. Chris Collins - 44.6% (65 games)
13. Pat Chambers - 43.3% (134 games)
14. Eddie Jordan - 35.7% (70 games)

Obviously there's wide ranges of how long each coach has been at a school. One real good season can throw off statistics for some of the newer coaches - like a Turgeon where one really good season accounted for just over 10% of his losses over 4 years. You also have a Richard Pitino who has had some consistently ok seasons - but yet to make the NCAA Tournament.

 

[CRBoiler]

I look at that list of coaches ranked by career B1G record and wonder what would be the best way to use stats to objectively rank the coaches on performance vs. expectations given the talent & experience they have had each year. Sum of final rank vs. preseason rank? Nah, because preseason rankings are subjective bull$hit. Not sure how you'd do it, but if you did I think Ryan would be way up there, as would Painter. Guys like Chambers might move to the middle of the pack, and Crean would almost certainly be dead last.

 

[tjreese]

I look at that list of coaches ranked by career B1G record and wonder what would be the best way to use stats to objectively rank the coaches on performance vs. expectations given the talent & experience they have had each year. Sum of final rank vs. preseason rank? Nah, because preseason rankings are subjective bull$hit. Not sure how you'd do it, but if you did I think Ryan would be way up there, as would Painter. Guys like Chambers might move to the middle of the pack, and Crean would almost certainly be dead last.

I think without any math you already have the answer and I agree with your results. However, if someone attempted to qualify an understanding by quantifying with some number I might start something like this...

I'm always leery of using vague data to derive precise numbers and this is no exception. However, without any understanding of the models at play and the mean square error relative to the total error term I offer a guess as to a starting point. I'm no statistician and only played one 30 years ago for a short while. My model would go something like this for starters as an initial thought for reflection. I would try to quantify the average of several recruiting services position of the top 8 players by playing time for each of the last 8 years per team. I would try to weight the actual player (top 8 for each year of the last 8) rankings so as to take into consideration a comprehensive playing time of the total minutes allowed to derive an weighted average player position for the 200 minutes per game for all games in each of the 8 years. I would then take that number for every year being considered (8 min.) and divide it into the final average of the RPI and Sagarin for each year. I would then total up all 8 years and divide by 8 to get my mean over the last 8 years. I would do this for all coaches in consideration in the conference. I would then take each final data point per year and plot all 8 years per coach on a line. Those lines would be compared to the average line generated for all 8 years of all coaches as a means of comparing each coach to the average, to each other and to see the variation of each coach over the 8 years as well as the general slope should it exist. Now that was off the top of my head and I'm sure there would be many better ways of doing this, but that was the basic idea that first popped into my head. Again, it has been slightly over 30 years since I played with anything of similar approach....

 

[boilerpt]

Don't have those specifics, but in terms of active Big Ten coaches at their respective Big Ten school...

1. Thad Matta - 76.1% (393 games)
2. Bo Ryan - 74% (488 games)
3. Tom Izzo - 71.4% (697 games)
4. Matt Painter - 64.6% (341 games)
5. Mark Turgeon - 64% (139 games)
6. Richard Pitino - 61.3% (75 games)
7. John Beilein - 60.4% (278 games)
8. John Groce - 59.4% (106 games)
9. Fran Mccafferty - 56.9% (174 games)
10. Tom Crean - 52.5% (238 games)
11. Tim Miles - 50.5% (101 games)
12. Chris Collins - 44.6% (65 games)
13. Pat Chambers - 43.3% (134 games)
14. Eddie Jordan - 35.7% (70 games)

Obviously there's wide ranges of how long each coach has been at a school. One real good season can throw off statistics for some of the newer coaches - like a Turgeon where one really good season accounted for just over 10% of his losses over 4 years. You also have a Richard Pitino who has had some consistently ok seasons - but yet to make the NCAA Tournament.

Thanks...I was talking with someone last evening during the IU game and he was going on about how Crean and Painter were two of the worst coaches in the country. I agreed on Crean as I don't know who else gets less from the kind of talent he has each year. Painter, I disagreed with as I feel that he tends to get a lot from his guys...the drawback being that he hasn't recruited better in those years between '07 class and the last couple.

 

[BoilerJS]

Thanks...I was talking with someone last evening during the IU game and he was going on about how Crean and Painter were two of the worst coaches in the country. I agreed on Crean as I don't know who else gets less from the kind of talent he has each year. Painter, I disagreed with as I feel that he tends to get a lot from his guys...the drawback being that he hasn't recruited better in those years between '07 class and the last couple.

I'd take Painter and Creans first year out of the equation.