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Predicting how the QB draft prospect will do
Now this is an interesting read...
http://myespn.go.com/blogs/nfcnorth/...rd-debate.html Posted by ESPN.com's Kevin Seifert The experts are hedging. The fans are sweating. The team is making clear it is considering all of its options. There are 47 days remaining until the 2009 NFL draft, giving the Detroit Lions some 1,125 hours before they are required to make the No. 1 overall pick. The Lions might need every minute of that span, especially if their internal discussion at all reflects the raging public debate on Georgia quarterback Matthew Stafford. A classically built, strong-armed quarterback, Stafford has not yet caught on as the consensus No. 1 pick. ESPN.com draft analyst Todd McShay, for example, said recently the Lions face a "nightmare" decision because Stafford is "not mentally ready" to take on the pressures of being the No. 1 overall pick. McShay said that scouts from at least 10 teams agreed with that assessment and added: "I just don't feel great about building my organization around him." NFL Network draft analyst Mike Mayock told a Detroit radio station that "there are some things about him that bother me," and even Stafford's biggest supporter advocates with a negative argument. Yes, Mel Kiper Jr. said the Lions should select Stafford primarily because "there is nobody else to take." Even fans are getting into the act. On the day the Lions announced they were playing host to Baylor offensive tackle Jason Smith, Jim of Cincinnati wrote: Matthew Stafford? Why are people thinking he is a good fit for an 0-16 team? I have seen Stafford play. He gets rattled easily. His arm is ok but his leadership skills lack. Next year they can get a much better QB. This year they need to fill in the holes on defense and on the line. Why all of this generalist hate against Stafford, who by all accounts offers fine character as well as the draft's strongest arm? Our friends at ESPN Research have developed a method for fleshing out the debate with statistical analysis. Using time-honored performance standards to predict future success for "blue-chip" quarterbacks, the formula placed Stafford between Akili Smith and Cade McNown in a category reserved for busts. Does this mean Stafford is guaranteed to crash and burn? Of course not. But this evaluation documents in specific fashion the previously ill-defined criticisms of Stafford, helping to explain why there is so much disagreement about him with the draft little more than six weeks away. The formula takes into account three statistics: Career starts, completion percentage and touchdown-interception ratio. The theory is that experience, accuracy and production versus mistakes can provide substantive indicators for college quarterbacks. Formula Explanation ESPN Research developed this formula to measure quarterbacks relative to a baseline completion percentage of 60 and a touchdown-interception ratio of 2.25. The multipliers allow each figure to have equal weight with career starts, which provides an important measure of experience. The total score is the sum of the three adjusted figures. The separate parameters for BCS and non-BCS quarterbacks help level the statistical playing field. They are based on the assumption that NFL-caliber quarterbacks playing against non-BCS opponents are going to have inflated numbers." For those mathematically inclined -- it took me 10 readings to get it after having nightmare flashbacks to eighth-grade algebra -- here is the formula itself: For BCS quarterbacks Career Starts + [(Career completion pct. - 60)x5] +[(Career touchdown-INT ratio - 2.25)x10] For non-BCS quarterbacks Career Starts + [(Career completion pct. - 60)x2.5] + [(Career touchdown-INT Ratio - 2.25)x5] (For a complete explanation of the formula, see the text box on your right.) To test the formula, ESPN Research plugged in the 31 quarterbacks taken in the first round over the past 12 drafts, dating back to 1997. The results are below. You'll see the quarterbacks broken into three categories. If their college statistics translated into a value of 20 or more, there was a strong likelihood for success. (Alex Smith and Tim Couch notwithstanding.) A value between 1 and 19 essentially meant "iffy." But the most revealing category were those quarterbacks who finished with a value of 0 or less. Every one of them failed as NFL quarterbacks. Take a look: Scores of First-Round Quarterbacks, 1997-2008 Group I: Strong likelihood of success Player School Draft year Score Matt Leinart USC 2006 64.04 Philip Rivers NC State 2004 48.44 Tim Couch Kentucky 1999 47.64 Alex Smith Utah 2005 44.88 Aaron Rodgers California 2005 40.58 Peyton Manning Tennessee 1998 39.47 Jason Campbell Auburn 2005 38.75 Byron Leftwich Marshall 2003 36.39 Ben Roethlisberger Miami (Ohio) 2004 33.85 Chad Pennington Marshall 2000 33.53 Daunte Culpepper Central Florida 1999 30.00 David Carr Fresno State 2002 23.97 Joe Flacco Delaware 2008 23.92 Eli Manning Ole Miss 2004 23.14 Donovan McNabb Syracuse 1999 21.62 Group II: Hit-or-Miss Player School Draft year Score Brady Quinn Notre Dame 2007 18.93 JaMarcus Russell LSU 2007 18.64 Rex Grossman Florida 2003 18.39 Vince Young Texas 2006 18.21 Carson Palmer USC 2003 16.35 Matt Ryan Boston College 2008 9.14 Patrick Ramsey Tulane 2002 9.06 J.P. Losman Tulane 2004 7.86 Jay Cutler Vanderbilt 2006 2.39 Group III: Busts Player School Draft year Score Akili Smith Oregon 1999 0.00 Cade McNown UCLA 1999 -6.41 Joey Harrington Oregon 2002 -6.85 Michael Vick Virginia Tech 2001 -11.32 Ryan Leaf Washington St. 1998 -16.92 Jim Druckenmiller Virginia Tech 1997 -20.25 Kyle Boller California 2003 -50.67 Stafford scored a -4.45, putting him in unflattering surroundings to say the least. You never want to be on a list that includes Jim Druckenmiller and Akili Smith. Stafford's career completion percentage of 57.1 percent and his touchdown-interception ratio of 1.55 were primarily responsible for his poor showing. That left him rated well below USC quarterback Mark Sanchez and slightly behind Kansas State's Josh Freeman. Scores for 2009 Likely First-Round Quarterbacks Player School Score Mark Sanchez USC 32.63 Josh Freeman Kansas State 1.94 Matthew Stafford Georgia -4.55 Stafford's numbers were dragged down by a freshman season in which Stafford completed 52.7 percent of his passes and threw 13 interceptions against seven touchdowns. When McShay, Mayock and Jim from Cincinnati express their concerns about Stafford, it's primarily for these reasons: College quarterbacks don't typically improve their accuracy in the NFL. If his decisions were at all suspect against SEC opponents, then it's reasonable to wonder how he will react to professional defenses. Throw in the state of the Lions, who are coming off an 0-16 season and might feel pressure to start him immediately behind an offensive line that needs help, and you understand the genesis of the Stafford debate. Where will it lead? Luckily, we have 47 days to find out. |
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#16 |
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Stafford is NOT a "start in 09" guy. Neither is Sanchez, but if a team picks ANY college QB and throws him to the wolves on opening day, they deserve to be beaten.
And often. Nobody here expected either of these two guys to roll up in to Arrowhead and go to work/win games on day one of the 2009 season. We wanted someone who showed great upside and could be brought along and developed in the correct and proper NFL fashion. And that may still happen. Because of Herm and Carl's complete suckage over the last three years, the franchise HAS to win some games this year to dig itself out of a hole. Cassel can(possibly)bring those instant wins and at least get us rolling again.
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#17 | |
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Quote:
So it looks like this for him: 0 + [(57.58-60)X5] + [(0-2.25)X10 = -34.6 |
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#18 | |
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#19 |
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Good news, Tom Brandstater of Fresno State has a 39.2 ranking which places him right next to Eli Manning. Print 'em.
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#20 | |
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#21 |
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Jay Cutler Vanderbilt 2006 2.39
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#22 |
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Actually its 0+ [(60.6-60)x5] + [(0-2.25)x10] = -19.5
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#23 |
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The whole purpose of developing a predictive model is so it'll have predictive value. If you look at how they end up ranking the QBs, that model has almost no predictive value. Perhaps they need to improve it a little before they print it.
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#26 |
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Exactly what I thought.
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#27 |
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The only thing that could make this formula more ridiculous is if it were explained to you in a bar at 3:00 am by John Madden and he's completely hammered.
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