What is the overlap between fantasy players and team W-L?

Do good teams produce more good running backs or wide receivers, and what can we learn? Michael Moore looks at the numbers.

| 3 months ago
(Justin K. Aller/Getty Images)

(Justin K. Aller/Getty Images)

What is the overlap between fantasy players and team W-L?

Stop me if you’ve heard this uttered at your fantasy draft before: “Receiver X is on a bad team which means they’ll be behind a lot and throwing it.” Or maybe “Running Back Y is on a good team, which means they will be running out the clock this season.” Both are extremely generic and short-sighted when it comes to evaluating the situation a player will be in during the upcoming season. Plus, there’s not much basis in reality for either one, at least when it comes to reviewing fantasy’s top fantasy running backs and receivers. In fact, the opposite is closer to the truth.

Top 12 WR Record Winning % Top-12 WR Top 12 RB Record Winning % Top-12 RB
2016 108-83-1 0.562 105-86-1 0.547
2015 107-85 0.557 96-96 0.500
2014 111-81 0.578 120-71-1 0.625
2013 100-91-1 0.521 105-85-2 0.547
2012 122-70 0.635 102-89-1 0.531
2011 116-76 0.604 99-93 0.516
2010 101-91 0.526 107-85 0.557
2009 125-67 0.651 98-94 0.510
2008 100-92 0.521 114-77-1 0.594
2007 127-65 0.661 106-86 0.552
1117-801-2 0.5816 1052-862-6 0.548

On average, top receivers over the last 10 years had a higher winning percentage. Over a 16-game season, that comes out to half a win more than running backs (9.31-8.76) and have cumulatively accrued at least 100 wins each season for a decade. Running backs failed to do so in three of them. At the very least, you could say successful fantasy receivers are more commonly on winning teams than successful running backs.

2016 was no different. Not only were fantasy’s top receivers winning more (again) but, look at the top players in both positions. David Johnson, fantasy’s top fantasy running back, finished on the 7-8-1 Cardinals, while Jordy Nelson, fantasy’s top receiver, played for the 10-6 Packers.

So what would happen if you had applied this thinking (receivers on winning teams at a more frequent rate than running backs) to the teams expected to do well or not so well? Let’s look at some players from the top and bottom five teams using win expectancy, heading into 2016.

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Michael Moore has written for PFF Fantasy since 2013, focusing primarily on dynasty content. He’s also hosted the PFF Fantasy Slant Podcast since 2014.

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