wgbeethree Posted May 18, 2019 Share Posted May 18, 2019 14 hours ago, blueswedeshoes said: My god we are! It’s like the Packer version of Big Bang Theory. Next name change season I have dibs on “Bill Schröedinger’s Cat”. Looks around at all the smugness and complete lack of humor on the board.... 2 Quote Link to comment Share on other sites More sharing options...
Norm Posted May 18, 2019 Share Posted May 18, 2019 Smudgeness* Quote Link to comment Share on other sites More sharing options...
Uffdaswede Posted May 18, 2019 Share Posted May 18, 2019 2 hours ago, wgbeethree said: Looks around at all the smugness and complete lack of humor on the board.... Idiosyncratic Humor uses the forum’s Extreme Gravity to create a slingshot effect. One doesn’t function without the other. Quote Link to comment Share on other sites More sharing options...
festiveonion Posted May 19, 2019 Share Posted May 19, 2019 4 hours ago, blueswedeshoes said: Idiosyncratic Humor uses the forum’s Extreme Gravity to create a slingshot effect. One doesn’t function without the other. ........takes one to know one Swish! Quote Link to comment Share on other sites More sharing options...
HyponGrey Posted May 19, 2019 Share Posted May 19, 2019 On 5/17/2019 at 11:50 PM, incognito_man said: Brian Brohmian Mechanic here Being nowhere near as clever as y'all, I'll take SphericalChickens Quote Link to comment Share on other sites More sharing options...
AlNFL19 Posted May 19, 2019 Share Posted May 19, 2019 Do you all think this is a pretty good track record for a statistical model? The results here are my WR projection model's projected bust chance and Pro Bowl chance against their NFL Approximate Value. A "Bust" is defined as <5.0 AV (average of years 3-4) for the purposes of the model, and "Pro Bowl" is defined as 10.0+. The "NFL AV" column is the player's average AV in Years 3-4, with "Busts" in red and "Pro Bowlers" in purple (green = hit, so just not a bust). 2006-2015 WR Model Results GROUP: Moderate Risk I (Projected Bust Chance: <50%) Results: 26.83% (11/41) Busts Year Name College NFL AV Bust Chance PB Chance 2010 D. Bryant Oklahoma State 11.5 6.56% 21.58% 2010 D. Thomas Georgia Tech 13.5 6.77% 21.53% 2015 A. Cooper Alabama 4 8.04% 21.21% 2012 K. Wright Baylor 4 21.61% 17.80% 2013 S. Bailey West Virginia 0.5 22.67% 17.53% 2007 C. Johnson Georgia Tech 8.5 24.79% 17.00% 2014 D. Adams Fresno State 9 25.85% 16.73% 2012 J. Blackmon Oklahoma State 0 29.25% 15.88% 2014 B. Cooks Oregon State 12 31.79% 15.24% 2014 J. Matthews Vanderbilt 5 32.43% 15.08% 2009 H. Nicks North Carolina 9 33.70% 14.76% 2013 D. Hopkins Clemson 9 34.12% 14.65% 2015 T. Lockett Kansas State 8 35.18% 14.38% 2014 S. Watkins Clemson 5 37.09% 13.90% 2015 N. Agholor USC 7 37.52% 13.80% 2013 T. Williams Baylor 5.5 38.15% 13.64% 2008 J. Nelson Kansas State 10 38.79% 13.48% 2010 G. Tate Notre Dame 8.5 39.21% 13.37% 2006 G. Jennings Western Michigan 11.5 39.42% 13.32% 2014 J. Landry LSU 8.5 39.85% 13.21% 2012 A.J. Jenkins Illinois 0.5 40.06% 13.16% 2010 J. Shipley Texas 1 40.27% 13.10% 2013 T. Austin West Virginia 5.5 41.12% 12.89% 2008 J. Hardy Indiana 0 42.39% 12.57% 2015 K. White West Virginia 0.5 42.39% 12.57% 2009 J. Maclin Missouri 6.5 43.45% 12.30% 2009 M. Crabtree Texas Tech 9.5 44.51% 12.04% 2007 J. Jones San Jose State 5 45.36% 11.82% 2007 D. Bowe LSU 8 46.21% 11.61% 2011 J. Jones Alabama 9.5 46.21% 11.61% 2007 R. Meachem Tennessee 7 46.42% 11.56% 2012 M. Floyd Notre Dame 7 47.06% 11.40% 2009 P. Harvin Florida 10.5 47.06% 11.40% 2009 K. Britt Rutgers 3 47.48% 11.29% 2008 D. Avery Houston 0 47.69% 11.24% 2014 O. Beckham Jr. LSU 6 47.90% 11.18% 2014 M. Evans Texas A&M 9 48.12% 11.13% 2008 D. Thomas Michigan State 0 48.33% 11.08% 2014 K. Benjamin Florida State 6.5 48.96% 10.92% 2006 S. Holmes Ohio State 9 49.18% 10.86% 2012 R. Randle LSU 7.5 49.81% 10.70% GROUP: Moderate Risk II (Projected Bust Chance: 50-60%) Results: 60.87% (14/23) Busts 2014 A. Robinson Penn State 3 50.87% 10.44% 2012 S. Hill Georgia Tech 0 51.08% 10.38% 2011 T. Smith Maryland 7.5 51.08% 10.38% 2007 M. Sims-Walker UCF 7 51.30% 10.33% 2014 P. Richardson Colorado 4 51.30% 10.33% 2007 S. Rice South Carolina 8 51.51% 10.28% 2012 M. Sanu Rutgers 6.5 51.93% 10.17% 2006 C. Jackson Florida 0 52.57% 10.01% 2011 L. Hankerson Miami 1 53.42% 9.80% 2015 D. Green-Beckham Missouri 0 54.05% 9.64% 2007 J. Lee Higgins UTEP 1.5 54.26% 9.58% 2013 M. Wheaton Oregon State 3 55.33% 9.32% 2008 M. Manningham Michigan 6 55.54% 9.26% 2007 T. Ginn Jr. Ohio State 4 55.54% 9.26% 2007 D. Jarrett USC 1 55.54% 9.26% 2011 T. Young Boise State 0 55.75% 9.21% 2014 J. Huff Oregon 1 55.75% 9.21% 2011 V. Brown San Diego State 3 55.96% 9.16% 2011 A.J. Green Georgia 11 55.96% 9.16% 2010 E. Sanders SMU 6 56.17% 9.10% 2015 J. Strong Arizona State 0 56.39% 9.05% 2010 B. LaFell LSU 6 57.66% 8.73% 2013 R. Woods USC 5.5 58.72% 8.46% GROUP: High Risk (Projected Bust Chance: 60-80%) Results: 76.32% (29/38) Busts 2007 S. Smith USC 7.5 60.20% 8.09% 2015 D. Smith Ohio State 0 60.84% 7.93% 2011 A. Pettis Boise State 2.5 61.26% 7.82% 2012 A. Jeffery South Carolina 8 62.32% 7.56% 2015 B. Perriman UCF 1.5 62.53% 7.50% 2012 R. Broyles Oklahoma 0 62.96% 7.40% 2009 B. Robiskie Ohio State 0 63.17% 7.34% 2006 B. Williams Wisconsin 0 63.17% 7.34% 2013 J. Hunter Tennessee 2 63.38% 7.29% 2006 M. Stovall Notre Dame 1 63.38% 7.29% 2009 J. Iglesias Oklahoma 0 63.59% 7.24% 2012 T.Y. Hilton FIU 10 63.81% 7.18% 2014 C. Latimer Indiana 1.5 64.23% 7.08% 2010 D. Williams USC 2 64.23% 7.08% 2007 A. Gonzalez Ohio State 0.5 64.23% 7.08% 2009 M. Massaquoi Georgia 2 65.08% 6.86% 2008 M. Kelly Oklahoma 0 65.50% 6.76% 2008 E. Bennett Vanderbilt 4 66.99% 6.38% 2006 D. Hagan Arizona State 0.5 67.20% 6.33% 2015 P. Dorsett Miami 2.5 67.83% 6.17% 2011 J. Baldwin Pittsburgh 0 68.47% 6.01% 2015 D. Funchess Michigan 6.5 69.53% 5.74% 2007 C. Davis LSU 2 70.59% 5.48% 2009 P. Turner USC 0.5 70.59% 5.48% 2014 M. Lee USC 6.5 71.86% 5.16% 2008 H. Douglas Louisville 4 72.50% 5.00% 2008 A. Caldwell Florida 3 72.50% 5.00% 2008 D. Jackson California 9.5 73.77% 4.68% 2015 C. Conley Georgia 3 74.20% 4.57% 2011 J. Jernigan Troy 1 74.62% 4.46% 2009 M. Wallace Mississippi 8.5 75.68% 4.19% 2015 D. Parker Louisville 3.5 75.89% 4.14% 2010 T. Price Ohio State 0 76.53% 3.98% 2009 D. Butler Penn State 0 76.95% 3.87% 2009 D. Heyward-Bey Maryland 6 78.01% 3.61% 2014 D. Moncrief Mississippi 3 78.44% 3.50% 2010 E. Decker Minnesota 11.5 79.71% 3.18% 2006 S. Moss Miami 1 79.92% 3.13% GROUP: Very High Risk (Projected Bust Chance: 80-99.99%) Results: 94.74% (18/19) Busts 2013 C. Patterson Tennessee 3.5 81.83% 2.65% 2008 E. Doucet LSU 3.5 82.46% 2.49% 2013 A. Dobson Marshall 0.5 83.95% 2.11% 2015 S. Coates Auburn 0 84.37% 2.01% 2007 J. Hill Washington State 2 85.86% 1.63% 2011 R. Cobb Kentucky 10 86.28% 1.53% 2008 E. Royal Virginia Tech 3.5 87.13% 1.31% 2010 A. Benn Illinois 0 88.61% <1.00% 2009 D. Williams Penn State 0 89.25% <1.00% 2012 T.J. Graham N.C. State 0.5 90.73% <1.00% 2006 W. Reid Florida State 0 97.73% <1.00% 2007 Y. Figurs Kansas State 0 99.64% <1.00% 2013 M. Goodwin Texas 2 >99.90% <1.00% 2008 L. Sweed Texas 0 >99.90% <1.00% 2006 T. Wilson Oklahoma 0 >99.90% <1.00% 2011 G. Little North Carolina 2 >99.90% <1.00% 2012 D. Posey Ohio State 0 >99.90% <1.00% 2007 P. Williams Fresno State 0 >99.90% <1.00% 2009 B. Tate North Carolina 1.5 >99.90% <1.00% 1 Quote Link to comment Share on other sites More sharing options...
boratt Posted May 19, 2019 Share Posted May 19, 2019 What is factored in? Quote Link to comment Share on other sites More sharing options...
incognito_man Posted May 19, 2019 Share Posted May 19, 2019 Seems like a solid track record. Did you develop the criteria logically and apply and record? Or tweak it after seeing results and try to fit it to the known results though? Quote Link to comment Share on other sites More sharing options...
boratt Posted May 19, 2019 Share Posted May 19, 2019 You could factor in some production pieces too, like: yards per game % of total offense ypg to account for just being a part of a bad passing attack Power conferences could get a little edge NFL style offenses could get a little edge touch downs adjusted for total passing offense If you added that in, I would think you could get even closer. Quote Link to comment Share on other sites More sharing options...
AlNFL19 Posted May 19, 2019 Share Posted May 19, 2019 (edited) I didn't tweak it, I just saw that it worked and called it done. It factors in: Draft Position Volume Statistics like Yards, Touchdowns*, Receptions Market Share Statistics like Yards per Team Attempt*, TDs per Team Attempt*, Receptions per Team Attempt* Mass in Terms of Weight/Height * Means it actually has a higher correlation to AV than Draft Position. It doesn't include any combine testing because none of it really correlated very well at all to a higher AV. @boratt @incognito_man Edited May 19, 2019 by AlNFL19 1 Quote Link to comment Share on other sites More sharing options...
boratt Posted May 19, 2019 Share Posted May 19, 2019 (edited) First of all, nice work. You found combine performance not to matter much? draft position sort of goes against what we do here. I would like to see both, one with draft position factored in and another without. To see how NFL teams picked against your model. I wonder if you could make a slight modifier for large schools and for schools with nfl style offenses? i wonder if you could make a slight athletic performance modifier too? Slight, just to affect the AV in the small degree in which it is applicable. I would guess your draft position inclusion already does that, but again, I’d want to see your model against their picking, to see where they fall. Edited May 19, 2019 by boratt Quote Link to comment Share on other sites More sharing options...
HighCalebR Posted May 19, 2019 Share Posted May 19, 2019 (edited) Interesting that 3/8 of the pro bowlers didnt get a 2nd contract with their drafting team. Where was Antonio Brown? Interesting that Stedman made it but his higher drafted counterpart Tavon didnt. Kindve feels like an incomplete data set. Shouldnt injury busts be removed from the data set? What are these last few years %'s? Edited May 19, 2019 by HighCalebR Quote Link to comment Share on other sites More sharing options...
AlNFL19 Posted May 19, 2019 Share Posted May 19, 2019 1 minute ago, boratt said: First of all, nice work. You found combine performance not to matter much? Yeah. A lot of workout-warrior receivers suck in the NFL, and plenty of terrible combine performances come from NFL studs. Granted, I think WR is actually one of the least combine-reliant positions. Even 40 time barely mattered. draft position sort of goes against what we do here. I would like to see both, one with draft position factored in and another without. To see how NFL teams picked against your model. I can try to find the correlation without draft position in a second. I wonder if you could make a slight modifier for large schools and for schools with nfl style offenses? i wonder if you could make a slight athletic performance modifier too? Slight, just to affect the AV in the small degree in which it is applicable. I would guess your draft position inclusion already does that though. Yeah, these two things might be on the checklist for the future but not for right now. First I'd need to see if an NFL-style-offense or large-school boost has much of a merit before determining how to go about that. Thanks for the feedback. Quote Link to comment Share on other sites More sharing options...
AlNFL19 Posted May 19, 2019 Share Posted May 19, 2019 3 minutes ago, HighCalebR said: Interesting that 3/8 of the pro bowlers didnt get a 2nd contract with their drafting team. What are these last few years %'s? These last few years don't have concrete results because since 2016 no WR drafted has played 4 years yet, obviously. Here's the projections: 2016-19 WR Model Results GROUP: Moderate Risk I (Projected Bust Chance: <50%) Year Name College Projected AV Bust Chance PB Chance 2017 C. Davis Western Michigan 6.66 4.23% 22.17% 2016 C. Coleman Baylor 5.82 22.04% 17.69% 2017 T. Taylor Western Kentucky 5.66 25.43% 16.84% 2017 J. Ross Washington 5.56 27.55% 16.30% 2019 A. Isabella Massachusetts 5.33 32.43% 15.08% 2018 A. Miller Memphis 5.31 32.85% 14.97% 2017 Z. Jones East Carolina 5.17 35.82% 14.22% 2017 C. Henderson Louisiana Tech 5 39.42% 13.32% 2016 W. Fuller Notre Dame 4.93 40.91% 12.94% 2019 M. Brown Oklahoma 4.85 42.60% 12.52% 2018 D.J. Moore Maryland 4.74 44.94% 11.93% 2016 S. Shepard Oklahoma 4.7 45.78% 11.72% 2017 M. Williams Clemson 4.68 46.21% 11.61% 2016 J. Doctson TCU 4.62 47.48% 11.29% 2018 J. Washington Oklahoma State 4.54 49.18% 10.86% GROUP: Moderate Risk II (Projected Bust Chance: 50-60%) 2016 T. Boyd Pittsburgh 4.47 50.66% 10.49% 2019 J.J. Arcega-Whiteside Stanford 4.44 51.30% 10.33% 2016 L. Treadwell Mississippi 4.43 51.51% 10.28% 2019 N. Harry Arizona State 4.43 51.51% 10.28% 2018 M. Gallup Colorado State 4.4 52.14% 10.12% 2017 C. Samuel Ohio State 4.33 53.63% 9.74% 2019 P. Campbell Ohio State 4.26 55.11% 9.37% 2018 C. Ridley Alabama 4.19 56.60% 9.00% 2017 C. Godwin Penn State 4.17 57.02% 8.89% 2018 C. Sutton SMU 4.16 57.23% 8.84% 2018 T. Smith UCF 4.16 57.23% 8.84% 2016 M. Thomas Ohio State 4.13 57.87% 8.68% 2017 K. Golladay Northern Illinois 4.11 58.29% 8.57% 2019 A.J. Brown Mississippi 4.11 58.29% 8.57% GROUP: High Risk (Projected Bust Chance: 60-80%) 2019 D. Samuel South Carolina 4.02 60.20% 8.09% 2018 C. Kirk Texas A&M 4.01 60.41% 8.04% 2018 D. Pettis Washington 3.88 63.17% 7.34% 2017 J. Smith-Schuster USC 3.87 63.38% 7.29% 2017 A. Stewart Alabama 3.7 66.99% 6.38% 2016 L. Carroo Rutgers 3.53 70.59% 5.48% 2019 M. Boykin Notre Dame 3.49 71.44% 5.26% 2017 A. Darboh Michigan 3.48 71.65% 5.21% 2019 D. Johnson Toledo 3.4 73.35% 4.78% 2019 J. Hurd Baylor 3.28 75.89% 4.14% 2018 D.J. Chark LSU 3.27 76.10% 4.09% 2019 M. Hardman Georgia 3.15 78.65% 3.45% GROUP: Very High Risk (Projected Bust Chance: 80-99.99%) 2019 T. McLaurin Ohio State 3.02 81.40% 2.75% 2019 D.K. Metcalf Mississippi 2.45 93.49% <1.00% 2016 B. Miller Ohio State 2.21 98.58% <1.00% Quote Link to comment Share on other sites More sharing options...
boratt Posted May 19, 2019 Share Posted May 19, 2019 Thanks for the work man! It’s interesring for sure! 1 Quote Link to comment Share on other sites More sharing options...
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