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)

The Unique Case Of Green Bay Packers WR Charles Johnson

July 2, 2013 by

The Green Bay Packers drafted WR Charles Johnson in the 7th round of the 2013 NFL Draft.  Johnson played at Grand Valley State, but he has a lot of physical tools.

Analytically, his profile is that of a wide receiver with excellent physical measures, and a tremendous production score. His reliance metric and volume do present increased risk that must be factored in.  Overall, he presents good upside from where he was selected in the NFL Draft. Additionally, he is one of the unique cases (see RB Rex Burkhead, Cincinnati Bengals) in the NFL Draft to not have a direct close comparative at his position logged into our system.  The list of wide receivers on the outer fringes does make an intriguing list though.

Filed Under: Cincinnati Bengals, Football Analytics, Green Bay Packers, NFL Draft, Running Backs (RB), Wide Receivers (WR)

The Cleveland Browns, Trent Richardson, And An Alabama RB Discussion

June 28, 2013 by

NFL Data Consultants was not a fan of what the Cleveland Browns did with their 2013 NFL Draft.  Despite the selection of QB Brandon Weeden in the 2012 NFL Draft, they did come away with some talent on offense with RB Trent Richardson and WR Josh Gordon (supplemental draft).  Josh Gordon is a case where an organization needs to assign its risk level because he had meet the criteria analytically of a player worth taking, but had other concerns that would affect his long term potential.  At least the Cleveland Browns aren’t totally devoid of analytics.  They do have a single analytics guy, which is better than nothing but it makes his job challenging depending on the level of analytical buy-in from the organization and scouting department.

With RB Trent Richardson, the Cleveland Browns took the best all around running back of the three primarily talked about running backs of Trent Richardson, Mark Ingram, and Eddie Lacy in recent NFL Drafts.  Lacy has health concerns, and since I don’t have a medical team to put that into a proper measuring tool, I will speak about what can be seen analytically.  Lacy played the toughest competition of the three backs and was a hammer doing it.  His production metrics were outstanding, but they are only one piece of the puzzle.  His full picture compares him more to committee backs.  Richardson finished in the middle on production metrics, but presents the best overall package and the best ability of the three in the passing game.  Mark Ingram had the lowest competition score between the three and the lowest yards per carry.

Filed Under: Cleveland Browns, Football Analytics, NFL Draft, Quaterbacks (QB), Running Backs (RB), Scouting Department, Wide Receivers (WR)

What Is The Story On Oakland Raiders RB Latavius Murray?

June 20, 2013 by

Have you ever thought what it would be like to understand an additional dimension to the one you are viewing?  The easiest concept for that picture is imagining a 3D object in 2D world.  With Oakland Raiders RB Latavius Murray, this concept is valid.

Despite having good on the surface numbers, 5.5 yards per carry or greater over the past 3 seasons, a deeper look shows a different picture.  His rushing average dropped to 3.4 yards per carry in his challenge games, which raises a red flag.  It concerned me heavily until I took an analytical look encompassing a much higher dimensional space.  He compared to a group of running backs that had all been taken earlier than him with the closest comparison being RB Andre Brown of the New York Giants.  Without the analytical view using additional dimensional space, I would have wrote him off for poor performance in challenge games.  Using a view that encompasses additional dimensional space, he compares to Andre Brown and a little more loosely to a running back with multiple pro bowls.  As a 6th round selection at pick 181, the Raiders made a selection that has all the signs of arbitrage.

Filed Under: Football Analytics, New York Giants, NFL Draft, Oakland Raiders, Running Backs (RB), Scouting Department

Denver Broncos Having A Montee Ball

June 17, 2013 by

There are a lot of varying viewpoints on the Montee Ball selection by the Denver Broncos, but NFL Data Consultants is a fan after much analysis. One of the data points of contention with RB Montee Ball was his short shuttle. A number of sources reported 4.11 and a number of them reported 4.31 as his short shuttle time. This is one of the reasons that NFL Data Consultants believe in a holistic approach and multiple points of analysis.

I take a specific approach when looking at a player’s production. In that analysis, Ball was graded at 5.01 yards per carry despite a non-adjusted figure of 5.6 yards per carry. From a production standpoint, this is a very good measure, especially considering his competition, challenge, and reliance metrics were all very good. Thus, it meant further investigation into some of the physical measures, including the 4.66/4.51 split in his 40 times between the combine and pro day. The culprit? Medication and sinus infection. One of the interesting things we had to do was go to our scientific approach with comparative analysis to get a much better read on his physical profile. The human bias would have been to say he was too slow, but the analytical approach is key to removing human bias. At the end of the process, Ball compared as a plus on LeSean McCoy, a runner that has started 44 games and averaged 4.6 yards per carry.

The great thing about using science in comparative analytics is that you can get a much stronger indicator of what a player is capable of doing at the pro levels. The other benefit is the ability to do a qualitative analysis to see what the scouting reports were of the comparable player. A common theme on physical elements of McCoy was that he is plenty quick enough to get to the corner, but lacked the elite speed. Interestingly enough, in his first 3 years he posted longs of 60 or more yards in each. According to Sports Science, Montee Ball had the 2nd fastest burst through the line and a stiff arm of 21.7% more force than Vikings RB Adrian Peterson. So what does the analytical package say? It appears the Denver Broncos have a good running back of the future regardless of any mixed reports that you see out there.

Filed Under: Denver Broncos, Featured Articles, Football Analytics, Minnesota Vikings, NFL Draft, Running Backs (RB), Scouting Department