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AlNFL19

Tight End Statistical Projections

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Posted (edited)

The last one of these got zero replies, so of course it's a great idea to do another one.

Basically, this model projects a player's average Approximate Value in years 3-4 based on the 2006-2015 drafts. It is correlated to NFL AV at 0.54, which is mediocre but better than draft position (-0.33). It also includes a Bust Chance (<5.0 AV) and Pro Bowl Chance (10.0+). It works for tight ends drafted in Rounds 1-3.

It includes:

  • Draft Position
  • Volume statistics like Yards, Touchdowns
  • Efficiency statistics like Yards per team attempt and Receptions per team attempt
  • Speed Score
  • Some of the Waldo EDGE Formulas (Speed 10, Speed 40, Speed Average, Agility Score)

Side note: the Combine is actually very telling for tight ends compared to other positions.

Worth noting: the model is very, very conservative because tight ends don't typically have much NFL success. The average among the players listed in real AV is around 2.0. No TE has ever had a projection above 5.0 AV.

Here's the historical data (the colored-in column is the "important" one with their NFL results):

Moderate Risk I (<50% Bust Chance)

Year Name College NFL AV Proj. Bust % Proj. PB %
2006 V. Davis Maryland 6 20.11% 16.61%
2011 R. Housler Florida Atlantic 2.5 33.01% 14.07%
2012 C. Fleener Stanford 5.5 42.59% 12.18%
2010 J. Gresham Oklahoma 5.5 46.65% 11.38%
2009 J. Cook South Carolina 5 47.76% 11.16%
2006 T. Scheffler W. Michigan 4.5 49.23% 10.87%

Moderate Risk II (50-60% Bust Chance)

Year Name College NFL AV Proj. Bust % Proj. PB %
2008 D. Keller Purdue 5.5 50.34% 10.65%
2010 J. Graham Miami 9.5 52.55% 10.21%
2007 G. Olsen Miami 4.5 53.29% 10.07%
2013 T. Kelce Cincinnati 9.5 56.97% 9.34%
2011 L. Kendricks Wisconsin 2 57.71% 9.20%
2010 R. Gronkowski Arizona 6.5 58.45% 9.05%
2014 A. Sefarian-Jenkins Washington 2 59.18% 8.90%
2008 F. Davis USC 4 59.18% 8.90%

High Risk (60-80% Bust Chance)

Year Name College NFL AV Proj. Bust % Proj. PB %
2014 E. Ebron North Carolina 5.5 63.24% 8.10%
2012 M. Egnew Missouri 0 65.08% 7.74%
2013 Z. Ertz Stanford 6.5 66.19% 7.52%
2006 D. Thomas Texas 2.5 67.30% 7.31%
2010 E. Dickson Oregon 2 68.03% 7.16%
2013 T. Eifert Notre Dame 4.5 68.40% 7.09%
2008 C. Stevens California 1 69.51% 6.87%
2006 L. Pope Georgia 1 69.88% 6.80%
2009 T. Beckum Wisconsin 0.5 71.35% 6.51%
2014 J. Amaro Texas Tech 0.5 71.72% 6.43%
2008 M. Bennett Texas A&M 1.5 72.09% 6.36%
2013 J. Reed Florida 7 73.19% 6.14%
2015 M. Williams Minnesota 1 74.30% 5.92%
2006 M. Lewis UCLA 4.5 77.99% 5.20%
2013 V. McDonald Rice 2.5 79.46% 4.91%

Very High Risk (80-99.9% Bust Chance)

Year Name College NFL AV Proj. Bust % Proj. PB %
2010 T. Moeaki Iowa 1.5 80.20% 4.76%
2006 J. Klopfenstein Colorado 0.5 81.67% 4.47%
2014 C.J. Fiedorowicz Iowa 2.5 83.15% 4.18%
2013 G. Escobar San Diego State 0 83.15% 4.18%
2008 B. Cottam Tennessee 0 83.15% 4.18%
2015 C. Walford Miami 0.5 84.62% 3.89%
2012 D. Allen Clemson 2 90.52% 2.72%
2009 B. Pettigrew Oklahoma State 5.5 90.52% 2.72%
2007 Z. Miller Arizona State 2 91.26% 2.58%
2011 K. Rudolph Notre Dame 2.5 92.36% 2.36%
2009 C. Coffman Missouri 0 92.36% 2.36%
2008 J. Finley Texas 6 93.10% 2.22%
2006 A. Fasano Notre Dame 3.5 93.47% 2.14%
2015 T. Kroft Rutgers 1.5 93.84% 2.07%
2008 J. Carlson Notre Dame 1.5 96.79% 1.49%
2014 T. Niklas Notre Dame 0.5 97.53% 1.34%
2007 M. Spaeth Minnesota 0.5 97.89% 1.27%
2015 J. Heuerman Ohio State 1.5 >99.9% <1.00%
2006 D. Byrd USC 0 >99.9% <1.00%
2014 R. Rodgers California 2.5 >99.9% <1.00%
2014 C. Gillmore Colorado State 0 >99.9% <1.00%
2009 R. Quinn North Carolina 0 >99.9% <1.00%

I think that's a pretty good track record. I have this data for other positions I've done too if anybody cares.

Now, on to this year's projections:

1. NOAH FANT, IOWA

N. Fant, TE, Iowa
Statistic Figure
Projected AV 4.50
Bust Chance 29.32%
PB Chance 14.79%

A sub-five projection doesn't seem like much, but this is the second-highest TE projection since 2006, to only Vernon Davis. Fant's raw statistics were pretty good, but his workout numbers drive up this projection. A 4.50 40-yard dash and 6.81 3-cone is flying for a tight end, and Fant isn't a terribly small tight end either. Overall, the model is banking on Fant more than anyone else in the class, including the latest Lions' top-ten-pick tight end.

2. IRV SMITH JR., ALABAMA

I. Smith Jr., TE, Alabama
Statistic Figure
Projected AV 3.56
Bust Chance 63.98%
PB Chance 7.96%

From Fant to everybody else is a gap plummeting from the moderate risk group to the high risk one (60-80% bust chance). Smith's projection only beats T.J. Hockenson's by a little, but it's enough to give him the No. 2 spot in the class. Smith's efficiency statistics are better than either Iowa TE's, and his 710 yard, 7 TD last season is nothing to scoff at from a statistics perspective. However, Smith fell a little at the Combine. His 7.32 3-cone drill (a fairly predictive drill for TEs) was last of the group, leading to an Agility Score that projects to 2.22 AV. 

3. T.J. HOCKENSON, IOWA

T.J. Hockenson, TE, Iowa
Statistic Figure
Projected AV 3.56
Bust Chance 63.98%
PB Chance 7.96%

Hockenson falls just a bit short of Smith, and had similar efficiency statistics. Hockenson also had 5 more receptions for 50 more yards than Smith, but he scored 6 times to Smith's 7. A 4.70 is slower than the model wants to see for a highly-drafted tight end, and Hockenson takes a fall for it into the High Risk group. Overall, Hockenson was outdone by others at the Combine, and failed to distance himself.

4. JOSH OLIVER, SAN JOSE STATE

J. Oliver, TE, San Jose State
Statistic Figure
Projected AV 3.46
Bust Chance 67.66%
PB Chance 7.23%

Oliver performed similarly overall to Hockenson and Smith, in the 700s for yardage and with middling testing numbers, but more receptions than either. However, San Jose State's higher attempts per game rate means Oliver's efficiency statistics suffer more. Oliver also only turned in 4 touchdowns in his final college season, not enough to inspire much confidence. Overall, as a third-round pick, Oliver offered pretty good value as a flier with roughly a 1/3 chance to make it in the league.

5. DAWSON KNOX, OLE MISS

D. Knox, TE, Mississippi
Statistic Figure
Projected AV 3.38
Bust Chance 70.61%
PB Chance 6.65%

Running a 4.59 40-yard dash with a 1.57 10-yard split, Knox was a bit of a workout warrior, but his projection suffers from on-field mediocrity (at best). In a somewhat crowded offense also featuring A.J. Brown and D.K. Metcalf, Knox only caught 15 passes for 284 yards despite Ole Miss' tendency to throw the ball quite a bit. This hurt his efficiency and volume projections, putting him firmly in the high risk group. The biggest knock on Knox, though, is that he scored 0 touchdowns in 2018.

6. KAHALE WARRING, SAN DIEGO STATE

K. Warring, TE, San Diego State
Statistic Figure
Projected AV 3.24
Bust Chance 75.77%
PB Chance 5.63%

Warring was generally well-liked across the threads I've read, but his projection isn't very high. Overall, Warring was very mid-to-low at everything - 372 yards, 3 touchdowns, 4.67 40 time, 7.21 3-cone. Not much stood out in terms of Warring's numbers, and neither does his projection.

7. JACE STERNBERGER, TEXAS A&M

J. Sternberger, TE, Texas A&M
Statistic Figure
Projected AV 3.08
Bust Chance 81.67%
PB Chance 4.47%

Sternberger falls into the Very High Risk group, exactly the one you don't want to fall into. He's on the good end, though, if there is one - though the group has had 2 of 22 players (9.09%) not bust, Sternberger's chance to succeed is higher at 18.33%. Still not exactly great. Sternberger's 832 yards and 10 touchdowns were class-bests (Rounds 1-3), but those weren't enough to save him from a mediocre-at-best combine that included a group-worst 4.75 40.

8. DREW SAMPLE, WASHINGTON

D. Sample, TE, Washington
Statistic Figure
Projected AV 3.02
Bust Chance 83.89%
PB Chance 4.03%

The numbers say Sample was overdrafted, and I have to agree. Sample's 252 yard, 3 touchdown season is far from good, as is a 4.71 40-yard dash. Sample's highest single-stat projection, just a 3.22, came from his mediocre Agility Score. Sample falls squarely into a risky group, and it'll be a challenge for him to become much more than a blocking tight end, if the model is on to anything.

Probably just preaching to the choir at this point, but please feel free to check these out: 

 

 

 

Edited by AlNFL19

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This is very interesting, I appreciate you posting this. It's interesting that you have J. Finley and Sternberger in the v. high risk group because they're both 3rd round picks of the Packers. I think Finley isn't the worst comp for Sternberger, too. 

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awesome stuff...   I'm curious to see where OJ Howard projects.   I dont see him but I could have overlooked.   Thanks!

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14 minutes ago, sryan66611 said:

awesome stuff...   I'm curious to see where OJ Howard projects.   I dont see him but I could have overlooked.   Thanks!

Sure thing. The data above is 2006-2015 because that's a 10 year sample but guys drafted after 2015 haven't played 4 years yet (projection is average AV in years 3-4).

O.J.'s projection is pretty damn good:

O.J. Howard, TE, Alabama
Statistic Figure
Projected AV 4.19
Bust Chance 40.75%
PB Chance 12.54%

That falls into the Moderate Risk I group (the best one - <50% chance to bust) with a Top-5-since-2006 projection (behind Vernon Davis, Noah Fant, draft-class-mate Evan Engram, and Rob Housler).

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2 hours ago, AlNFL19 said:

Sure thing. The data above is 2006-2015 because that's a 10 year sample but guys drafted after 2015 haven't played 4 years yet (projection is average AV in years 3-4).

O.J.'s projection is pretty damn good:

 

O.J. Howard, TE, Alabama
Statistic Figure
Projected AV 4.19
Bust Chance 40.75%
PB Chance 12.54%

That falls into the Moderate Risk I group (the best one - <50% chance to bust) with a Top-5-since-2006 projection (behind Vernon Davis, Noah Fant, draft-class-mate Evan Engram, and Rob Housler).

Oh, so thats why I didn't see it lol.   thanks for posting it though.  

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Oo, very surprised with TJ Hock, who I had as bust-proof effectively, with being such a useful player in many aspects of the game.

 

I like your stuff though. What did you have on Kittle, if anything?

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I love analytics. I do professional research on the topic. 

I think that you need to do a better job of validating your tool. Sure...you put a bunch of numbers together, but do your predications have any correlation at all with outcomes? To my blind eye...I’m skeptical. You need to educate yourself on statistics and do a multi variant analysis to improve and validate your tool. 

But I really do appreciate your effort and you’re on the right track. 

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6 minutes ago, sammymvpknight said:

I love analytics. I do professional research on the topic. 

I think that you need to do a better job of validating your tool. Sure...you put a bunch of numbers together, but do your predications have any correlation at all with outcomes? To my blind eye...I’m skeptical. You need to educate yourself on statistics and do a multi variant analysis to improve and validate your tool. 

But I really do appreciate your effort and you’re on the right track. 

I could be misunderstanding, but isn’t the first half of the post comparing bust percentages with NFL AV from a ten year sample?

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4 hours ago, Hunter2_1 said:

Oo, very surprised with TJ Hock, who I had as bust-proof effectively, with being such a useful player in many aspects of the game.

 

I like your stuff though. What did you have on Kittle, if anything?

The model was made for Rounds 1-3 draft picks, so Kittle doesn't have an official projection, but if you run the numbers you get this:

G. Kittle, TE, Iowa
Statistic Figure
Projected AV 3.66
Bust Chance 60.29%
PB Chance 8.69%

He put up some freak numbers at the combine (4.52 40, 1.59 10-yard split, 6.76 3-cone at Pro Day), but the bottom line is that his projection won't be through the roof because he wasn't drafted until Round 5. Also, he didn't put up very good numbers on the field at Iowa. Take this with a grain of salt though, because the model isn't really built on or for data from Day 3 picks. It's functional, though. Still a very good projection, especially considering draft position - it would rank 2nd in this year's class.

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1 hour ago, deathstar said:

I could be misunderstanding, but isn’t the first half of the post comparing bust percentages with NFL AV from a ten year sample?

I think you may be right. It’s a little difficult to follow 

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9 minutes ago, sammymvpknight said:

I think you may be right. It’s a little difficult to follow 

Yes, that's right. Sorry it's not super well-organized.

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Fascinating. Thanks for posting, I enjoy analysis like this.  

 

I think the flaw here is that this analysis weighs physical measurables so highly as a predictor of success. Dedication and hard work are big determining factors which cannot be measured with much accuracy. I know you put in college stats which may capture that, but lots of variables like QB quality and other WR/TE options (would Hockenson have done better if Fant not on the team?)

 

Tough factors to gain metrics on.

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2 minutes ago, VegasDan said:

Fascinating. Thanks for posting, I enjoy analysis like this.  

 

I think the flaw here is that this analysis weighs physical measurables so highly as a predictor of success. Dedication and hard work are big determining factors which cannot be measured with much accuracy. I know you put in college stats which may capture that, but lots of variables like QB quality and other WR/TE options (would Hockenson have done better if Fant not on the team?)

 

Tough factors to gain metrics on.

Physical measurables are influenced, not entirely but partially, by hard work and dedication. Nothing's perfect, because as we know Jace Sternberger is going to be a hall of famer, but it's got an interesting hit rate over 10 years.

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5 hours ago, VegasDan said:

Fascinating. Thanks for posting, I enjoy analysis like this.  

 

I think the flaw here is that this analysis weighs physical measurables so highly as a predictor of success. Dedication and hard work are big determining factors which cannot be measured with much accuracy. I know you put in college stats which may capture that, but lots of variables like QB quality and other WR/TE options (would Hockenson have done better if Fant not on the team?)

 

Tough factors to gain metrics on.

To be fair, it weights measurables highly because they have a high historical correlation to success at TE. That obviously isn’t true for all positions - my WR model, for example, doesn’t include any measurables because the track record there is spotty at best and nothing truly correlates highly. 

Answering the Hockenson / Fant thing, I think using market share statistics tells you a lot about things like how reliant a team was on a player. Players that can shoulder a bigger load of the offense in college are more likely to be good as pros. Plus, college coaches are obviously good judges of talent, so if they see a player as worth a big target share, there’s a reason why. But you’re right, it’s hard to gauge those things overall.

As a side note, Jim Cobern (CommonManFootball) does a lot with market share statistics and thresholds and whatnot on YouTube. I’d recommend checking his stuff out if you like that kind of analysis.  

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Very interesting and looks like you spent a lot of time on this. Kudos!

 

That being said, this game is incredibly dependant on mental capacity and that isn't measured in any of these analytical things. I think analytics are kind of dumb, but it doesn't mean it's not a cool tool to use. I would literally never use it to skew my thoughts on a prospect though.

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