When it comes to football analysis, we can often make excuses for players with established names who are underperforming.
Conversely, we can downplay a player's impact because of any number of variables: his team, his raw numbers, or even just his name and past struggles.
But what happens when you look at the numbers without the name? Some interesting things pop up when aligning similar stat lines.
Of course, I won't be looking into yards and touchdowns but rather Net Expected Points (NEP), which is our metric for quantifying on-field production. NEP factors in game variables such as down and distance and score and calculates whether a player's production helps add to his team's expected point total or not. Check out our glossary if you need more schooling.
Quarterbacks
| Player | Passes | Pass NEP | Pass NEP/P | Pass Successes | Pass Success Rate |
|---|---|---|---|---|---|
| Player A | 332 | 49.51 | 0.15 | 164 | 49.40% |
| Player B | 494 | 47.65 | 0.10 | 212 | 42.91% |
The sample size of drop backs isn't too close, but based on cumulative Passing NEP, Passing NEP per drop back, and Pass Success Rate (which is the percentage of drop backs that lead to positive NEP gain), Player A had the better passing season even though he's got major criticism in his past. Oh, and Player B was about a yard away from a second consecutive Super Bowl ring.
Yep. Player B is Russell Wilson. Player A? Mark Sanchez. I'm not saying Sanchez is better. I'm not. But he did have a more efficient passing season.
| Player | Passes | Pass NEP | Pass NEP/P | Pass Successes | Pass Success Rate |
|---|---|---|---|---|---|
| Player A | 548 | 188.41 | 0.34 | 293 | 53.47% |
| Player B | 101 | 35.12 | 0.35 | 55 | 54.46% |
The sample size couldn't be much different, of course, but in terms of efficiency (Passing NEP per drop back) and Pass Success Rate. Player A is considered one of the best -- if not the -- best in the game. Player B isn't even a starter.
Who are they? Aaron Rodgers and Derek Anderson.
| Player | Passes | Pass NEP | Pass NEP/P | Pass Successes | Pass Success Rate |
|---|---|---|---|---|---|
| Player A | 463 | 20.60 | 0.04 | 205 | 44.28% |
| Player B | 480 | 19.65 | 0.04 | 215 | 44.79% |
| Player C | 212 | 19.58 | 0.09 | 101 | 47.64% |
| Player D | 487 | 18.40 | 0.04 | 226 | 46.41% |
These quarterbacks were closely linked in Passing NEP, and three of them had nearly identical per drop back Passing NEP. Pass Success Rates weren't too far off, but one of them is retired, two may or may not have jobs, and one is a superstar.
Player A is Brian Hoyer. Player B is Kyle Orton. Kirk Cousins is Player C. The superstar of the bunch?
Player D: Cam Newton.
Running Backs
| Player | Rushes | Rush NEP | Rush NEP/P | Successes | Success Rate |
|---|---|---|---|---|---|
| Player A | 205 | 22.10 | 0.11 | 99 | 48.29% |
| Player B | 222 | 20.63 | 0.09 | 108 | 48.65% |
These two backs were some of the best in the league, and they had similar Success Rates, which means they move the ball forward at similar clips even though they don't really "appear" to play similarly. Player A has been one of the league's elite backs for years, and Player B was a rookie.
Jamaal Charles is Player A, and you've probably guessed by now that Player B is Jeremy Hill. Seriously, Jeremy Hill was amazing this year and finished fourth among backs in Rushing NEP. Yes, please.
| Player | Rushes | Rush NEP | Rush NEP/P | Successes | Success Rate |
|---|---|---|---|---|---|
| Player A | 392 | 10.48 | 0.03 | 183 | 46.68% |
| Player B | 226 | 9.88 | 0.04 | 103 | 45.58% |
Player A's carries are a dead giveaway, so I won't pretend like it's not DeMarco Murray, but really, Player B was slightly better on a per-carry basis, and his Success Rate wasn't too far off the pace of Murray.
Unfortunately, he's got plenty of backfield competition again even though it seemed like his chances were set to increase this year.
Yep. That's Mark Ingram.
| Player | Rushes | Rush NEP | Rush NEP/P | Successes | Success Rate |
|---|---|---|---|---|---|
| Player A | 160 | -19.99 | -0.12 | 56 | 35.00% |
| Player B | 170 | -21.20 | -0.12 | 59 | 34.71% |
On the other end of the spectrum, here are two backs whose metrics are nearly identical but not exactly promising. However, one has been talked up as a potential workhorse back for 2015, and the other is firmly supplanted behind one of the league's best rushers.
Player A? Branden Oliver. Player B? That's Alfred Blue. What a difference team situation and big games can make in terms of how we view production.
Wide Receivers
| Player | Rec | Rec NEP | Tar | Target NEP | Rec NEP/Tar | Catch Rate | Success Rate |
|---|---|---|---|---|---|---|---|
| Player A | 59 | 80.64 | 99 | 40.27 | 0.81 | 59.60% | 96.61% |
| Player B | 69 | 80.25 | 116 | 16.52 | 0.69 | 59.48% | 89.86% |
Wide receiver comparisons didn't quite jump off the spreadsheet because of the variances in Reception NEP per target, Catch Rate, and Reception Success Rate between possession players and big-play guys, but this was a nice reminder of how good one of the league's former best stacked up against one of the league's current best who struggled with injury all season.
Player B is A.J. Green. Player A is a player who is still performing at a high level even though he's overlooked at this point in his career: Marques Colston.
| Player | Rec | Rec NEP | Tar | Target NEP | Rec NEP/Tar | Catch Rate | Success Rate |
|---|---|---|---|---|---|---|---|
| Player A | 26 | 45.82 | 48 | 29.72 | 0.95 | 54.17% | 80.77% |
| Player B | 30 | 42.70 | 46 | 29.28 | 0.93 | 65.22% | 96.67% |
Here are two young, low-volume, big-play options with impressive Reception NEP per target numbers. (For comparison, Kenny Stills led the league at 1.05.) Player A is a 6'4" touchdown machine playing alongside a veteran quarterback while in his rookie season in 2014. Player B is a 5'10" second-year player with one touchdown to his name but who still added nearly the same amount of NEP through his receptions as Player A did.
Player A, unsurprisingly, is Martavis Bryant. Player B is Stedman Bailey. I'm not sure if the perception of these two could be much different, but that's the way it is.
Tight Ends
| Player | Rec | Rec NEP | Tar | Target NEP | Rec NEP/Tar | Catch Rate | Success Rate |
|---|---|---|---|---|---|---|---|
| Player A | 85 | 73.56 | 125 | 24.43 | 0.59 | 68.00% | 90.59% |
| Player B | 90 | 72.40 | 128 | 20.07 | 0.57 | 70.31% | 76.67% |
Player A is a big-time tight end but who -- well, any hints I give will be obvious, really. It's Jimmy Graham. And, honestly, Player B isn't hard to figure out, either, based on the receptions and Targets. It's Martellus Bennett.
What drew the stat lines to my eye, though, is when sorting things by Reception NEP per target. Among the 25 tight ends with at least 30 catches in 2014, Graham and Bennett ranked just 14th and 15th, respectively. We can be impressed by their reception numbers, but neither was very efficient this year.
| Player | Rec | Rec NEP | Tar | Target NEP | Rec NEP/Tar | Catch Rate | Success Rate |
|---|---|---|---|---|---|---|---|
| Player A | 82 | 112.45 | 131 | 66.62 | 0.86 | 62.60% | 92.68% |
| Player B | 67 | 72.26 | 87 | 58.23 | 0.83 | 77.01% | 95.52% |
Player B doesn't have the usage totals that Player A does, but in terms of efficiency, he's pretty dang close. His Reception NEP per target is just 0.03 off the pace, but his Catch Rate and Reception Success Rate is better. If I threw posted their measurables and combine stats, they'd look about as close as their 2014 numbers look.
Player A is fairly obvious: Rob Gronkowski. Player B? The next big thing at the tight end position Travis Kelce.