NFL

# 6 Quarterbacks Who Should See Their Fantasy Points Per Game Averages Fall and Rise in 2016

After a down season in Atlanta, is Matt Ryan ready to bounce back and become a fantasy football relevant quarterback?

Every year, there are quarterbacks that surprise us with their play.

While there isn't anything we can do about these shocking performances once the season has begun, it's critical to re-evaluate these players as we look forward to the next year.

As a result, I wanted to develop a system to help identify these passers for fantasy football purposes, and to keep bias out of that re-evaluation process.

Insert Passing Fantasy Points Per Game over Expectation (PFPPGoE).

### What is PFPPGoE?

Before I start giving you the implications of PFPPGoE (sorry for the mouthful), let's look at how the statistic works.

Here at numberFire, we have a metric known as Net Expected Points (NEP). On every play, there's an expected point value an NFL team has for the drive based on yard line, down, and distance. What happens on that play can change the expected point value on said drive. What NEP does is aggregate the values gained or lost on every play into a single, net number.

For the purpose of this experiment, I was looking specifically at Passing NEP, which is how many expected points a player gains through passing -- I wanted to see how well Passing NEP correlated to fantasy points per game. I looked at quarterbacks with a minimum of 200 pass attempts between 2011 and 2015 (181 total) and plotted their Passing NEP totals against their fantasy points per game. To eliminate any edge received by running quarterbacks, I isolated fantasy scoring to just points accrued through the air. The results were not that surprising.

The correlation between Passing NEP and passing fantasy points per game was incredibly strong, coming in a shade over 0.75. I used the regression equation pictured above (with Passing NEP as "x") to create Expected Passing Fantasy Points Per Game (EPFPPG). Then, all I had to do was subtract a player's actual fantasy scoring by his expected scoring to arrive at Passing Fantasy Points Per Game over Expectation.

### Can PFPPGoE Be Predictive?

Looking at PFPPGoE is nice because it allows us to see how players did in fantasy with respect to how they actually did on the field. In theory, passers with a lower expected than actual passing fantasy points per game did better than their play on the field would suggest, while those with a higher expected than actual passing fantasy points per game left some fantasy scoring on the field.

But is this useful in telling us what can happen the year after?

Well, of the 108 quarterbacks who qualified for study in consecutive years, exactly half of them increased in passing fantasy points per game. On the whole, PFPPGoE was only slightly better than random chance at predicting improvement or regression (about 52 percent in either case).

However, at the extremes, who was "lucky" and who was "unlucky" was a lot clearer. Of the nine quarterbacks to record a PFPPGoE greater than 2.5 -- meaning, they were scoring 2.5 more points per game or more than they should have -- seven of them dropped in fantasy scoring the following year (78 percent). Meanwhile, there were five signal-callers to record a PFPPGoE less than -2.5 in the subset, and four of them improved in scoring the following year (80 percent).

It would seem that at these extremes, PFPPGoE is fairly predictive.

There were six quarterbacks in 2015 with a PFPPGoE absolute value of 2.5 or greater to go along with likely opportunity. Let's see what it could mean for their 2016 prospects.

### Blake Bortles, Jaguars -- PFPPGoE: 3.83

Blake Bortles is the poster child for 2016 regression, as he led 2015 quarterbacks with a PFPPGoE of 3.83. His Passing NEP of 47.67 was closer to the likes of Alex Smith and Sam Bradford than that of a top five fantasy passer. Currently being selected as a top-10 passer, he's a pretty clear guy to avoid in 2016 drafts.

### Andrew Luck, Colts -- PFPPGoE: 3.81

This one was somewhat surprising, as I think people already associate Luck with a disappointing fantasy season after early poor play was followed by a season-ending injury. However, he still managed to score well above what he was expected to considering that poor play.

Sure, Luck will more than likely bounce back in 2016, but it's not as though you'll be getting a discount in drafts. This analysis would say you're better off playing it safe and selecting one of the other elite fantasy passers over him.

### Colin Kaepernick, 49ers -- PFPPGoE: -2.94

Colin Kaepernick truthers unite!

While his poor play in 2015 cost him his job before an injury ended his season, it appears as though Kap was somewhat unlucky as a passer. He was already a candidate for improvement with Chip Kelly at the helm in San Francisco, and this analysis says he may not be completely rushing dependent in 2016.

### Matt Ryan, Falcons -- PFPPGoE: -2.72

After years of overrating Matt Ryan, the fantasy community has actually been pretty harsh on him this offseason. However, it appears as though his play wasn't as bad as we thought. Especially if the Falcons can add another pass-catcher in the draft, expect Ryan to bounce back a lot from his QB28 finish in fantasy points per game in 2015.

### Derek Carr, Raiders -- PFPPGoE: 2.72

Carr was one of fantasy's most pleasant surprises in 2015, but it may have been more luck than tremendous growth in skill. His Passing NEP was very close to Ryan Tannehill and Brian Hoyer despite his QB14 finish. Fantasy players are actually projecting growth for Carr in 2016, taking him at QB12 in early drafts according to MyFantasyLeague.com. That appears to be unwise.

### Teddy Bridgewater, Vikings -- PFPPGoE: -2.51

The always-underrated Bridgewater played much better than it seemed in 2015, and this gives hopes to truthers (like myself) who are hoping for him to be fantasy viable in the near future. If Adrian Peterson finally hits the age wall in 2016, an increase in both volume and luck could yield some startable fantasy value for Bridgewater.