Allen Robinson Was the NFL’s Most Balanced Receiver Last Year
One of the most widely-used phrases in football analysis is where and how a player "wins."
Generally used in film watching, it’s an attempt to uncover how a player utilizes his skills to the fullest potential and where on the field this is most likely to happen.
Instead of taking a film-driven approach to this idea, I decided to dive into numberFire’s Net Expected Points (NEP) to see just where players "won."
Using data from the 2015 season, I broke down wide receivers who accumulated 125-plus targets by dividing the field into three sections (left, middle, and right).
We have to keep in mind that this only includes the past season, but this can still be viewed as a hyper-focused breakdown of the most heavily targeted wide receivers from last season.
Onto the numbers.
2015 Results
For each of the 23 receivers, we'll examine the targets, Reception NEP per target, and Success Rate (the percentage of catches that led to positive NEP gains) for each of the three areas on the field.
| Player |
Tar (L) |
Rec. NEP/T (L) |
SR% (L) |
Tar (M) |
Rec. NEP/T (M) |
SR% (M) |
Tar (R) |
Rec. NEP/T (R) |
SR% (R) |
|---|---|---|---|---|---|---|---|---|---|
| Julio Jones | 79 | 0.69 | 81.13% | 58 | 0.78 | 85.37% | 64 | 0.7 | 87.80% |
| Antonio Brown | 73 | 0.9 | 82.76% | 36 | 0.68 | 75.00% | 79 | 0.64 | 78.18% |
| DeAndre Hopkins | 88 | 0.67 | 94.12% | 26 | 0.59 | 88.89% | 75 | 0.84 | 97.56% |
| Demaryius Thomas | 74 | 0.56 | 78.26% | 36 | 0.74 | 82.61% | 60 | 0.66 | 81.82% |
| Brandon Marshall | 79 | 0.86 | 90.38% | 21 | 0.42 | 77.78% | 69 | 0.68 | 82.67% |
| Jarvis Landry | 54 | 0.55 | 76.47% | 40 | 0.53 | 84.62% | 63 | 0.43 | 67.44% |
| Odell Beckham | 49 | 0.96 | 85.71% | 39 | 1.38 | 87.10% | 67 | 0.69 | 89.19% |
| Allen Robinson | 54 | 0.92 | 93.33% | 23 | 0.91 | 92.86% | 74 | 0.78 | 94.44% |
| Calvin Johnson | 70 | 0.79 | 89.13% | 25 | 0.78 | 85.71% | 51 | 0.68 | 100.00% |
| Mike Evans | 52 | 0.62 | 95.83% | 29 | 0.71 | 86.67% | 62 | 0.54 | 93.55% |
| Larry Fitzgerald | 50 | 0.62 | 86.49% | 30 | 0.99 | 95.83% | 61 | 0.67 | 86.67% |
| Michael Crabtree | 37 | 0.55 | 81.82% | 22 | 0.82 | 84.62% | 82 | 0.51 | 80.43% |
| Emmanuel Sanders | 56 | 0.45 | 76.67% | 22 | 1.15 | 92.31% | 56 | 0.68 | 93.55% |
| T.Y. Hilton | 34 | 1.17 | 94.44% | 22 | 0.67 | 75.00% | 72 | 0.49 | 94.29% |
| A.J. Green | 50 | 0.93 | 87.10% | 17 | 1.26 | 100.00% | 62 | 0.74 | 95.00% |
| Eric Decker | 48 | 0.71 | 88.46% | 41 | 0.99 | 92.59% | 39 | 0.69 | 82.61% |
| Amari Cooper | 56 | 0.4 | 79.31% | 18 | 1.36 | 100.00% | 56 | 0.73 | 83.87% |
| Golden Tate | 40 | 0.27 | 66.67% | 36 | 0.78 | 84.62% | 49 | 0.55 | 82.35% |
| Randall Cobb | 49 | 0.53 | 70.37% | 32 | 0.94 | 95.45% | 48 | 0.25 | 56.67% |
| Brandin Cooks | 56 | 0.77 | 75.68% | 28 | 0.96 | 85.00% | 41 | 0.59 | 73.08% |
| Jordan Matthews | 45 | 0.52 | 87.50% | 28 | 0.44 | 75.00% | 52 | 0.77 | 72.73% |
| Kamar Aiken | 54 | 0.86 | 94.12% | 19 | 0.59 | 90.00% | 52 | 0.5 | 79.31% |
| Travis Benjamin | 45 | 0.8 | 82.61% | 21 | 0.91 | 90.00% | 56 | 0.39 | 80.00% |
There were 23 wide receivers that saw 125 or more targets last season. I would have liked to extend this study further out, but for brevity’s sake, I chose to narrow it down.
After examining the results, here are a few interesting observations.
Using this info, it’s fair to argue that Allen Robinson was the most evenly-efficient wide receiver among this group last season. He was the only one to top 0.75 Reception NEP per target in all areas of the field, as well as the only player to have a Success Rate of 90% or better in all three areas.
Jarvis Landry was consistently mediocre to poor in all areas of the field by NEP standards last season. He was most efficient on left-side targets (0.55 Reception NEP per target), which was the lowest high-water mark of any player in the cohort.
Antonio Brown was much more efficient on left-side targets (0.90) compared to middle (0.68) and right-side (0.64). In some cases, large differences in NEP can be attributed to uneven target distribution. In Brown’s case, however, he saw nearly as many targets on the left side (73) as on the right side (79).
DeAndre Hopkins has similar results as Brown's -- but on the opposite side of the field. He was much more efficient on the right side (0.84) on 75 targets as compared to the left side (0.67) on 88 targets.
With identical target totals (56) on both the right and left sides of the field, Amari Cooper was dramatically better on the right (0.73) compared to the left (0.40).
Golden Tate's NEP results strongly indicate that he’s best suited to play in the middle of the field. His 0.27 Reception NEP per target on 40 targets from the left side should cast some doubt on his viability as a boundary pass-catcher for Detroit.
Moving Forward
Because of the existence of crossing routes and their ability to skew results based on where a player lines up in formation pre-snap, using these types of statistics isn’t a perfect science, but it is one that should be worth valuing in some fashion.
Combining these results with pre-snap formation stats can help identify which coaching staffs may be ignoring where a player excels and instead putting him in positions not likely to produce the best results.
As mentioned earlier, with just one season’s worth of data, it’s difficult to make any sweeping statements about how this info can used to predict future outcomes for these individual players.
As we gain more information, however, this type of analysis could become extremely helpful in evaluating how players are used by their respective teams and determining which ones are being miscast and misused by their play-callers.
