Mike Bergsman


Another week, another Kareem Hunt explosion of fantasy output. Will he slow down?

As promised last week, we’d start to see some of the guys we are accustomed to seeing in the top tier of PPGAR. Tom Brady, Antonio Brown, Rob Gronkowski, Devonta Freeman, etc. are all working their way up the charts.

Despite this, with next week being the quarter mark of the season, Kareem Hunt, Todd Gurley, Chris Thompson, Ty Montgomery, and Stefon Diggs make up the top five players in terms of PPGAR through the first three weeks. Like a Donald Trump tweet, this season in Fantasy Football has been so unpredictable.1

One of the reasons RBs are ruling the roost so far this season is that RB output is down about a point per game compared to years passed. In the past five years, replacement tier PPG has been around nine for RBs. This year, replacement tier PPG for RBs has been about eight. Basically, the highest performing RBs are playing really well and the gap has widened between the highest tier and replacement tier output, compared to other positions.

Long gone are the days of Aaron Rodgers, Le’Veon Bell, and Antonio Brown atop the PPGAR rankings.

The top 10 players in terms of PPGAR so far this year are absolutely dumbfounding. I know it’s early, but c’mon, Sam Bradford, Alex Smith, Todd Gurley, Tarik Cohen, Jason Witten, and future first ballot Hall of Famer Kareem Hunt!?!

In all actuality, this trend is not new. Have a look at some of the best fantasy performers in week two of last year.

Just remember, the guys you drafted in the first few rounds or for the most money in your auction draft often have a couple of bad weeks per year. It’s rare that EVERY week you’ll get their “average” points per game. They call this crazy phenomenon “reversion to the mean.”

Let’s hope some of the guys you expected to shine all year will do some of that mean reversion black magic. Without further adieu, here’s the PPGAR rankings through week two.


I guarantee Alex Smith, Tarik Cohen, and Sam Bradford were not the sleeper picks you had in mind this year.

Week one of the 2017 fantasy football season was….odd. Only one of the top ten players in terms of total points from 2016 are in the top ten of PPGAR in week one.1

Here are your week one PPGAR leaders.

Show of hands: how many of you have done fantasy drafts in Madden? I know I can’t be the only one. So the other day I was thinking about how great it feels to draft the best possible team, sit back and marvel at the juggernaut I’ve built. I rarely ever play the actual games; usually, I just simulate the season. If the team isn’t any good, I can always restart the season until it works out.1

Fantasy football scratches the same itch except that when I’m playing real fantasy football – by which I mean real fantasy football, not video game football2 – I can’t restart when things don’t go my way. Which sucks. To avoid that misery, my fellow fantasy players and I go to great lengths to build strong teams.3 All of which begs the question: can these two types of team building be combined? Can Madden ratings provide insight into future fantasy success?

It happens almost every year. A first round draft pick who’s expected to change the fortunes of a perennial basement dweller and sure enough, they’re nothing but hot garbage. Or you’ll see an almost nobody fifth rounder come out of nowhere and make the Pro Bowl.1

Over the last five years, there have been some pretty outstanding rookies that have made their way onto the field. And they’ve come from all throughout the draft. They’ve made a huge impact on both real, live-action football, the one that we all used to watch, and Fantasy Football, the one we’re willing to trade our first born for.

Here’s a look at how every single offensive rookie measured up in terms of first year output since the 2012 season:

Obviously, rookie performance runs the gamut from earth shatteringly good2 to holy shit, why did the Browns draft you in the first round, there had to have been other options, right?3

Almost nothing in fantasy hurts worse than being let down by a highly drafted player. In Dead or Alive, we’ll take a look at some of 2016’s most underwhelming performers and try to predict how they’ll fare in the upcoming season. (But if you get burned again, that’s totally on you.)

Do you remember 2015? Back when DeAndre Hopkins was third in receiving yards behind Julio Jones and Antonio Brown? When he averaged 20.1 PPG in PPR scoring, good enough for sixth among all non-QBs? When he seemed like a complete and total beast? I do too, but barely. These days it seems like it was a long time ago when everyone had Nuk pegged as a top five WR heading into 2016. When literally every major fantasy football site saw him as a can’t miss receiver.1

So many fantasy players drafted Hopkins early last year hoping that he’d build on his fantastic 2014 and 2015 seasons only to be left completely despondent. After his slow start, a lot of players tried to buy low in a trade, thinking he had to get better given what he’d done in the past.2 You can almost imagine a budding fantasy football analyst thinking exactly that and then trading a top-15 RB for Hopkins, dreams of “upside” swimming in his head.

Boy did I get burned, because he didn’t get better. The people who thought he would3were wrong. Not just kind of wrong. Like, disturbingly, maddeningly, outrageously wrong. So what the hell happened?

Have you ever wondered how your alma mater stands up against other schools in terms of fantasy output? I personally have not, as Northwood University and the University of Detroit Mercy are apparently not producing NFL caliber talent at an alarming pace. But for all the students and alums of our nation’s great football schools, here’s a look at five years of fantasy output sorted by school, conference and state.

I’m surprised by this because it’s been a long time since Miami stopped being the powerhouse it once was. Then again, a big chunk of Miami’s fantasy output in the last five years comes from Andre Johnson, Jimmy Graham, Frank Gore, Greg Olsen and Reggie Wayne.

If you look at the last five years, Miami’s output is certainly trending down. Being that Miami isn’t churning out NFL talent like they used to and that the players above are aging (or already out of the league), it’s a lock that Miami will fall in these rankings over the next few years. And if California at number two feels surprising to you, I’ll ask you to remember that the likes of Aaron Rodgers and Marshawn Lynch went to Cal.

Consistency, consistency, consistency.

My strategy for Fantasy Football as I’ve grown into a wannabe-Guru has led me to the realization that consistency, rather than high risk, high ceiling, is the key attribute to shoot for when drafting or targeting players for waivers or trades.

Yards per catch can signify trouble ahead if it’s too high. For example, as of week three in 2016, Marvin Jones , was on pace for 2,176 receiving yards and an average YPC of 23. Without looking into anything further I can already make an assumption that he will revert to the mean YPC across the league of 11. Jones was brought into to fill the void Calvin Johnson left, not shatter NFL records.

YPC is a nice thing to look as more of an ancillary statistic, but if you really want to understand consistency, you have to understand distributions of YPC. The reason for this is twofold:

Today we’re going to look at points per touch (PPT) which is a particularly relevant metric for RBs in PPR leagues, since PPR rules allow RBs to be extremely valuable even with a limited amount of touches per game. For reference, I’m defining points per touch as a player’s total number of points divided by their total touches (rushes and receptions). By reviewing PPT, we should be able to compare both receiving backs and bell-cow, run-between-the-tackles backs on the same scale.

Additionally, this PPT data should help us to identify some potential 2017 breakout candidates. With running back platoons in vogue, there were a number of backs that handled less than 50% of the carries for their team but were far more effective on a per touch basis than their backfield colleagues. Some of these players may have earned an increased workload in 2017 or may even be given the opportunity to take over as a lead back. Alternatively, PPT should help us to isolate the more inefficient RBs from 2016. Finding these players allows us to find not only players to avoid in 2017 but also players who may benefit from an off season of roster turnover: if a player was inefficient in 2016 and their team bolstered its offensive line, a more efficient season may be on the way.

With all that said, let’s take a look at the data.