WR3 vs Flex through 4 weeks
Methodology
Moving from a WR3 to a Flex position in our starting rosters makes it far easier to field a fully competitive lineup (on paper) from week to week. Injuries and Bye weeks become easier to manage with the vastly increased player pool, as does bench management. These are simple statements that only a moron would debate. But what about scoring value? Has one rule set shown to buoy league scoring more than the other? How exactly do I go about determining that?
I've looked back at the 2025 season and compiled data through 4 weeks for each owner's WR3, and then I've done the same for 2026 observing the Flex position. That's simple enough with a bit of clicking and a spreadsheet. But how exactly do I pick which receiver was the WR3, or which player was the Flex, for that matter?
For 2025 I've chosen the lowest projected WR from an owner's starting lineup for each week and called that, "WR3". This is consistent and easily repeatable. I can't simply look at the player in the WR3 slot, because not all owners align their starting rosters like that. Will there be a few instances where an owner chose a low projection to be their WR2 in theory before they picked between two higher projections for their WR3 slot? Sure, but I doubt too many. Not more than a similar thing happens at Flex, call it a wash.
For 2026 I've done a similar thing to remain consistent. If an owner started a RB in their Flex, I picked the lowest projected RB from their 3 starters and call it "Flex". Why? For instances like Week 4 when John had Nico Collins in his Flex spot. Is Nico a Flex? Hell no. Does it matter to his scoring which slot he's in? Hell no. But for this comparison, I'll need to pick the actual Flex from his group of three receivers. Which in the example given is Jaylen Waddle, who scored 9.5 to Nico's 23.8. Another example: I've had Kenneth Walker III in my Flex spot all season, but he was projected higher than Jonathan Taylor in Week 3 (by 0.1), so I've used Taylor as my Flex player for Week 3. Consistency is key here. Taylor scored 7.2 that week to Walker's 19.3.
Curiosity is the biggest draw when I dive into a statistical analysis like this. I'm curious what I'll find, will it match my expectations, will something surprise me, what interesting trends will emerge? So let's get to it!
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