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I Put ESPN's Position Rankings in a Spreadsheet

Discussion in 'OSU Sports Forum' started by markortwein, May 18, 2017.

  1. hcebb

    hcebb Wrangler
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    Did the analysis real quick. Interesting results. Because of the emphasis on DL, OL, LB, and CB/S, it does change the rankings. Don't know if it helped or not. I also had to make some assumptions based on the number of players at some of the positions. Should note that only 8 points separate the top 4 teams which is impressive when the total is 348 points.

    upload_2017-5-19_10-47-50.png

    upload_2017-5-19_10-48-33.png

    upload_2017-5-19_10-48-54.png
     
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  2. jobob85

    jobob85 Alcoholistic Sage
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    Texas is back baby!!!!! At least until 9/2/2017
     
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  3. ksupoke

    ksupoke We don't need no edgeukashun
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    Something seems amiss, uo has the top rated qb and the top rated ol and their backs are rated 6th, I get that they don't return much but this is a great example of lies, damn lies and statistics, assuming that their qb is 1 or 2 and their ol is 1 it is highly unlikely their backs will perform to the bottom half of the conference. Great back can make an avg ol look good, great ol can make an avg rb look great.
     
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  4. hcebb

    hcebb Wrangler
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    Ha ha! I agree. Would be interesting to see how this method would have fared at predicting the outcome the past couple of seasons.
     
  5. PJ-OSU

    PJ-OSU Cowboy

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    Ooooo-snap! We have ourselves a good old fashion "statistics off" between an OP legend @Lab Rat and the "new" kid in town @hcebb
    [​IMG]
    [​IMG]

    Bring it on! As an engineer, I love me some graphs and as on OSU fan, I love me some graphs about our Pokes even more.
     
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  6. Duke Silver

    Duke Silver Find safe haven in a warm bathtub full of my jazz.
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    Thank you.
     
  7. Duke Silver

    Duke Silver Find safe haven in a warm bathtub full of my jazz.
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    I'm sure the ladies will love this thread.:rolleyes:
     
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  8. BeatOU

    BeatOU --- ... ..-
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    American English recognizes a collective singular, though, so "data is beautiful" is perfectly acceptable in this country.

    For example, it is acceptable to say "OSU has the ball" even though there are 11 people on the field. Whereas in England, they would say "OSU have the ball".
     
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  9. Duke Silver

    Duke Silver Find safe haven in a warm bathtub full of my jazz.
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    What is happening?
     
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  10. NYC Poke

    NYC Poke The Veil of Ignorance
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    Start a shoes thread.
     
  11. Duke Silver

    Duke Silver Find safe haven in a warm bathtub full of my jazz.
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  12. Poke4Christ

    Poke4Christ Federal Marshal

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    8 straight over TT right now and I don't see any way that does not continue. Current record is 21–20–3. Likely we will take it back in 2018.
     
  13. Lab Rat

    Lab Rat Hold on while I make a chart
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    This is quite interesting and I understand the logic for weighing each position group by the number of players within that group. Like you said though, without doing a proper regression, imperfect assumptions are inevitable. My assumptions were admittedly imperfect.

    Nevertheless, I'm suspicious that your system undervalues the QB position. The system I used assumes that the QB position as a group is more important than any other position group, regardless of the number of starting players within that group. One justification for this assumption is that the QB touches the ball on every offensive play, and thus has more control of the outcome of that play than any other position group. It also seems most practical to me, based on empirical evidence.

    For instance, I think it's fair to say that the value of Texas' OL and RBs over the past few seasons has been wasted on poor QB play. Last year, Texas had a 1st team All Big 12 RB (Foreman), a 1st team All Big 12 OL (Williams), and a 2nd team All Big 12 OL (Perkins). But, they ranked 6th in points per game, 7th in the Big 12 in total offensive yards, and 8th in offensive yards per play. Those mediocre numbers can be largely attributed to their poor QBs.

    There really isn't a right answer here, but I would be very suspicious of any ranking system that puts Texas as #1 in the Big 12.
     
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  14. CPTNQUIRK

    CPTNQUIRK I'm Your Captain!
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    My money is on the Rat.
     
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  15. Duke Silver

    Duke Silver Find safe haven in a warm bathtub full of my jazz.
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    Nothing kicks ass like a data fight based on some sportswriter opinions of teams he hasn't watched.
     
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  16. okierock

    okierock Cowboy

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    LIES... DAMN LIES.... STATISTICS
     
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  17. sc5mu93

    sc5mu93 WeaselMonkey
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    [​IMG]
     
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  18. lagershead

    lagershead Sheriff

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    agree on regression for parameter (weights) determination--although that may be fraught with probs too but it's probably the best option available.

    I don't think the weights by unit is the best way, i.e., OL is not 8.8 simply due to the sum of salaries. QB is a "unit" in the schema as is OL, CB. So the unit of observation matters (no pun intended).
     
  19. sc5mu93

    sc5mu93 WeaselMonkey
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    I sat down and looked at these numbers and I struggled. But then I picked up my stat book from college as well as a programming book, and I came up with a model which I think accurately breaks down the season with a standard deviation of like 4.

    So to join this cripple fight, here is my chart.

    Okstate 2017 chart.jpg


    This thread really needs moar chartz.
     
  20. LayWood

    LayWood Deputy

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    A stellar qb is no good if under duress the whole game. Look at how Pitt rattled MR - didn't set his feet and threw a ton of high balls. The old saying is it begins in the trenches on both sides.

    oSu
     
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