What To Make Of The Philadelphia Eagles Draft Selection Of QB Matt Barkley?

July 19, 2013 by

When the Philadelphia Eagles traded up to the first pick in the 4th round to select QB Matt Barkley, what did they know that all other teams did not?  Head Coach Chip Kelly is known for being an outside the box thinker, and if that translates to good personnel decisions, it will be great for the Philadelphia Eagles fan base.  Matt Barkley’s Quarterback analyical profile was the best in this class according to NFL Data Consultants.

Yes, it is the human bias in us all that would have to do a double take on a USC Quarterback.  My own human bias had me do a study comparison of him versus the other previous USC Quarterbacks, and there are some things that clearly demonstrate that he is different.  Even though he is NFL Data Consultants best Quarterback of the 2013 NFL Draft class, he may not even the best long term QB on his own roster.  Nick Foles was a Quarterback that I was very high on after an analysis that I did last year comparing him to an elite NFL QB; while he did not get a benefit that the comparison QB did, the other side of that comparison remains incomplete for now.  Regardless, the sooner that the Philadelphia Eagles move on from turnover king, Michael Vick, the better it will be long term for this organization.

Although the analysis is incomplete on Nick Foles, it is interesting to note the following quote from Reuben Frank of CSNPhilly.com: “Foles last year became the first rookie in NFL history to throw for at least 240 yards per game while completing 60 percent of his passes.” Both young QBs compare to Pro Bowl Quarterbacks and the position looks bright for the Philadelphia Eagles for the long term.

Filed Under: Featured Articles, Football Analytics, Head Coaches (HC), NFL Draft, Philadelphia Eagles, Quaterbacks (QB)

A Comparative Analysis Summary Of The New York Jets Quarterbacks Geno Smith And Mark Sanchez

July 18, 2013 by

The New York Jets have been stricken with a disease that is a cancer to an organization, known as bad quarterback play. Mark Sanchez is what I would label as a “flat liner”. If you chart his QB Rating rating progression against time, you get a small dip early from just over 70 to just below 70 and slight bounce back to just over 70 and then a pretty long pretty flat line. Entering the 2013 NFL season, Mark Sanchez sits at a career QB rating of 71.7.

Thus, as a response, the New York Jets drafted another Quarterback, selecting QB Geno Smith in the 2nd round of the 2013 NFL Draft with the 39th pick overall. One type of analysis I do is break down a prospect with a mix of known metrics, often with my own modifications, and a number of my own proprietary metrics plus a clear rule and methodology for inclusion. I can then compare this to all players at the position to find the closest comparisons for a draft prospect and get a clearer picture of a floor/ceiling; better yet, I can remove human bias that I may have about a player.

The quarterback comparisons for Geno Smith are all either backup quarterbacks or out of the league currently. This group combines for 22 games started and 49 games played in the NFL. The QB Rating of their cumulative stats is in the 60s with an upside into the low 70s. From an analytical perspective, it is hard to believe that Geno Smith is going to be the quarterback solution for the New York Jets. Perhaps he can overcome the odds.

Interesting enough, the cumulative NFL stats for Mark Sanchez’s comparison group, excluding Sanchez, nets a 72.6 QB rating; compare that to Mark Sanchez’s career QB rating of 71.7. The New York Jets organization faces tough obstacles and will need resolve to overcome.

Filed Under: Featured Articles, Football Analytics, New York Jets, NFL Draft, Quaterbacks (QB)

Why St. Louis Rams Wide Receiver, Stedman Bailey, Is Destined For NFL Success

July 17, 2013 by

The St. Louis Rams selected two wide receivers out of West Virginia in the 2013 NFL Draft, taking WR Tavon Austin with the 8th overall pick and WR Stedman Bailey in the 3rd round with the 92nd pick overall. While I have a unique perspective at looking at WR Tavon Austin, it is the selection of WR Stedman Bailey that I will cover here.

By the title, it is easy to note that the belief at NFL Data Consultants is that Stedman Bailey will be a special NFL player. Analytically, he personifies all of the characteristics of success. His Reliance score is positive, his production metric meets the threshold several times over, his metrics met the threshold for better validity, and his movement metrics are good enough to hold an overall comparison to a more athletic wide receiver that has had success in the NFL. Basically, Stedman Bailey is a better football player and wide receiver than a pure athlete, perhaps the reason he was still available in the third round.

Wide Receiver is one of the most misjudged positions in the league. If you don’t believe that, go review all of the first and second round wide receivers and compare that to their career results. It is a position where teams can take advantage of arbitrage because the market value and actual value often varies heavily. With this selection, the St. Louis Rams did just that. Stedman Bailey holds very little risk for failure as an NFL wide receiver and has a very high upside as well. Stedman Bailey’s analytical profile screams that he  is destined for NFL success.

Filed Under: Football Analytics, NFL Draft, St. Louis Rams, Wide Receivers (WR)

Jordan Reed, Is He The Future For The Washington Redskins At Tight End?

July 16, 2013 by

Jordan Reed has been highlighted on other sites that like to review players with an analytical approach. Since it is always fun to compare analysis, I will do so in my review of TE Jordan Reed.

Drafted in the 3rd round with the 85th selection overall by the Washington Redskins in the 2013 NFL Draft, the question is what to make of expectations for the future of Jordan Reed at Tight End. A comparative analysis of nearly 300 Tight Ends, puts him on an island by himself; he has no comparison close enough to classify as a direct comparison, although there are some interesting names that are on the periphery. With confidence, I can say that Aaron Hernandez is not a good comparison for Jordan Reed even though both Tight Ends played at Florida. In fact, the analytical profile of Owen Daniels would be a much closer comparison to the football potential of Aaron Hernandez.

Although there is no direct comparison, the nearest comparison would be a cross between Tony Moeaki and Dennis Pitta. Jordan Reed has a very high reliance metric score, and his production score is higher than both Moeaki and Pitta. The number of games included also adds validity to his metrics so there is plenty of upside.

The major concern for Jordan Reed’s long term prospects is the health of his knee and quad. Reading his own quotes about the injury, it sounds structural, but I lack the proper information to determine the risk level it adds for the long term. He has the physical and analytical profile to be a success in the league and be a long term answer as a move Tight End for the Washington Redskins. Thus, the answer to whether he is the future for the Washington Redskins at Tight End is strictly health dependent.

Filed Under: Football Analytics, NFL Draft, Tight Ends (TE), Washington Redskins

An Analytical Summary Of Running Back Kenjon Barner Of The Carolina Panthers

July 15, 2013 by

The Carolina Panthers selected RB Kenjon Barner in 6th round with selection number 182 overall. After seeing the results that RB Kenjon Barner put up on ESPN’s Sports Science, I had an additional personal interest in doing an analytical study. On that show, he had the high mark for getting through the first set of bags that weighed a combined 1500 pounds. This was impressive for a smaller back. He was also superb in the agility portion as well.

Looking at his physical measures, the strength and speed measures are also impressive. Where the risk starts to pile on is with other metrics. His challenge and reliance scores were both negative in the running game, which signals a huge red flag. On top of that, his yards per carry were just under 4.3. In the passing game, his challenge and reliance metrics both scored favorably.

It is obvious that Barner has special athleticism, although it appears the best use of it will be as a back in the passing game. With the comparative analysis, the running back he compared to had an NFL rushing average of 4.2 yards per carry, which would have been right in the middle of the league; the 14th-17th ranked teams all averaged 4.2 yards per rush. The running back that Sports Science used as a comparative was Warrick Dunn, who averaged 4.1 yards per carry in his career. Dunn had 510 career receptions (about 3 per game) as well.

It would appear the niche for Barner is in the passing game, as a 3rd down back, and as a returner. In a more passing oriented offense, he would have much better opportunity to carve out more early down work. His comparative back didn’t make it past his rookie contract, but Barner is a plus comparison. It will be interesting to track his career as a running back with the Carolina Panthers.

Filed Under: Carolina Panthers, Football Analytics, NFL Draft, Running Backs (RB)