One of my favorite aspects of Superflex leagues is that I believe the extra Quarterback position helps facilitate trading, which happens to be one of the things I love most in life. Lately, one specific type of trade has become my move. Moving Quarterbacks within the same tiers. Sometimes I’ll even drop down a tier, depending on the return.
I’m sure I’m not the first fantasy player to think of this. I’m not claiming to have created anything unique or to have found a cheat code. I also know that sometimes the most obvious moves elude me while I plot and scheme a way to knock out a seven-team trade that will net me Saquon Barkley and only cost me Allen Hurns. If your brain is wired incorrectly like mine hopefully this helps connect those synapses.
Only One QB Tier?
While we devalue the Quarterback position in single start QB leagues (as we should), we are just as guilty of overvaluing the position in Superflex leagues. Discussing a recent trade, I completed (we’ll get to that later) on the latest DynastyTradesHQ episode our guest Andy Singleton noted that quarterbacks are all basically in one tier from 1-20. Though that is a bit of a stretch for me, I do agree with the sentiment. Using FFToday’s PPR scoring for QBs we see that the #1 overall scoring QB in 2017 averaged 28.6 per game (Deshaun Watson) while the 20th highest scoring averaged 19.2 points per game (Case Keenum).
That’s a significant drop in scoring average, 9.4 points per game, so I wouldn’t advocate trading away Watson for Keenum for many reasons, age, pedigree, draft capital, etc. Unless of course, you are getting something included with Keenum to bulk up the rest of your roster. That 9.4 drop in scoring comes with a caveat as well. Watson’s TD% rate of 9.3% was compiled in an extremely small sample size and is not a sustainable ratio over a full season. Don’t believe me? Using the best site there is to extract fantasy football data, FF Statistics shows us that 9.3% TD rate exceeds even the career-best Aaron Rodgers put up in 2011 of 8.96%. That was a season that saw Rodgers throw for 45 TDs.
Call me a skeptic, but I don’t believe Deshaun Watson is the next Aaron Rodgers. Raining on the Watson parade some more, Watson would have had tied for the 12th highest single-season TD rate of all time if he played a full season. As an aside now would be a great time to sell high on Watson. You should read this, to help you decide whether Watson is a sell high. Unless of course, you think Watson is a future Hall of Famer.
If we go way back to 2016, again utilizing FFToday scoring the difference between QB1 and QB20 falls to 7.3 points per game. In 2015 the difference was 7.2 points, and in 2014 the difference was 7.5 points per game between QB1 and QB20. Even though I’m not comfortable dropping from the QB1 to the QB20. Stil Andy’s point is well taken. If you can pull off a trade to bolster your roster in multiple positions, you should be able to make-up for that loss in QB scoring.
What I’m talking about doing though is slightly less adventurous. Using 2017 as a baseline, if you owned the Quarterback 5 overall, Aaron Rodgers he gave you 22.9 points a week. The quarterback 13, Jameis Winston scored 20.8 points per game. If you traded Rodgers for Winston straight up, while taking into account you’re moving down a full tier from a QB1 to a QB2, it would have only cost you 2.1 points per week. Assuming you have the good sense to acquire an additional asset for trading away Rodgers for Winston, you should pick up more than those 2.1 points every week, thus improving your overall weekly scoring.
So far this has all been in the abstract. I prefer real world results to use as examples; it’s easier to process for my feeble brain. I decided to poll Dynasty Twitter on this topic to help prove a point.
How would Dynasty Twitter feel about trading the 2017 QB6 Cam Newton, for the QB14 Dak Prescott and Devin Funchess who finished as the WR20 in overall scoring? This should be a slam dunk on the Prescott side. The trade involves quarterbacks separated by 2.4 fantasy points per game and a WR who averages 12.2 points per game.
Twitter did not agree with my assessment. Though not exactly a landslide, the Cam Newton side won handily.
Dak Prescott is coming off a perceived down season, even though as noted above he scored just 2.4 fantasy points per game behind Newton. I decided to run another Twitter poll to see how this trade would fare swapping out Prescott for Matt Stafford. Stafford finished as the QB10 scoring 21.8 points per game, one point per game less than Newton.
Even though the Stafford side won going away, I’m still a little perturbed by these results. I see this trade as one that should have garnered north of 80% for the Stafford side. Matt Stafford and Cam Newton are players of similar age, Newton is 29 years of age and Stafford is 30 years old. They have similar production over the last five seasons. Outside of Newton’s otherworldly 2015 season, Newton and Stafford have finished separated by no more than 2.2 points per game.
By trading Newton for Stafford and Funchess, you’re swapping comparable quarterbacks AND adding a WR2 to your roster. You know you like WR2s. They’re no WR1s, but they’re still pretty special.
Let’s use an actual real-world example. Recently I traded Marcus Mariota and a 2019 2nd round rookie pick for Blake Bortles, Calvin Ridley, and Tarik Cohen. There is a 100% chance that all three players will see many weeks in my starting lineup together. Bortles slides into the QB/Superflex position, while Cohen and Ridley will kick the likes of Mike Wallace, Tyrell Williams or Bilal Powell to the bench where they belong. As much as I love Mariota, this is a trade I will make every day of every week in every Superflex league I play in.
Admittedly some of this tactic relies on more than just overvaluing of the QB position in Superflex leagues. Recency bias and name cache certainly affect these types of trades, but no more so than in typical trades. I’ll be hunting for more trades similar to my Bortles (plus) for Mariota trade mentioned above. Here’s hoping that this is a winning strategy!
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