Pump the Brakes on the Free Agency Fantasies
We are in the middle of, in my opinion, the most exciting offseason in the modern NFL. There has been no shortage of blockbuster trades, of stalwart, franchise-defining players departing for greener pastures. Russell Wilson, Davante Adams, and Tyreek Hill top the list of notables, but the party continues far beyond this triumvirate. Allen Robinson, Robert Woods, Chase Edmonds, Raheem Mostert, Matt Ryan, Mitchell Trubisky, Carson Wentz, Christian Kirk, JuJu Smith-Schuster and more will be flying different flags in the fall.
This writer is concerned, naturally, with the fantasy fallout. Hope springs eternal, be it for a fantasy legend heading to a potentially upstart offense (Tyreek Hill to Miami) or a player with troubled production looking to benefit from a change of scenery (Christian Kirk to Jacksonville, Allen Robinson to Los Angeles, etc.). Unfortunately, I am here to tell you, with the sober perspective of available data, that it just doesn’t usually work out.
We’ll be considering all QBs, RBs, and WRs (there weren’t any really notable TE moves this offseason, unless you count Noah Fant catching passes / breaking up interceptions from Drew Lock or whoever else in Seattle) from 1999. I define ‘changing teams’ as a player who plays for one team (only) in year T and another team (only) in year T + 1; this allows us to consider offseason moves instead of muddying the waters with in-season transactions. Finally, we only include players that averaged at least 8 PPG over a full 16 game season in the year before switching teams and scored at least 25 points in the year after. This (mostly) eliminates irrelevant/backup players that get traded (not many are really interested in how Drew Lock will perform in Seattle) or end up missing significant time due to injury. All data is from nflfastR, and I count 260 players that meet these criteria.
Let’s jump right into it by comparing the distribution of points scored (over an entire season) by position. The blue mound constitutes players playing for a new team, the red mound players that stick with the same team:
Clearly, players changing teams represent a significant drop-off in production across all of the positions. To put numbers to it, just-traded QBs score 59 points less (27%), RBs score 42 points less (26%) and WRs score 32 points less (21%) than their same-team counterparts.
The boom-bust profiles are even more concerning. All positions have about double the probability of ‘busting’ (average less than 7 PPG) and half – or worse, quartered for QBs and RBs – of ‘booming’ (average 15+ PPG) when comparing the relative rates of players changing teams to same-team players.
Now you might be noting, correctly, that a crucial variable is missing: stage of career. It’s much less likely that a 33-year old, oft-injured Julio Jones will bring valuable production to his new team, but there is more hope for young bucks like 25-year old Christian Kirk. One could even imagine the opposite argument: three-year veteran Cedrick Wilson doesn’t have much of a track record, and thus we should be less certain that his skills will transfer to Miami, compared to eight-year veteran and (former) perennial WR1 Allen Robinson. Is there an effect in either direction? Let’s break down the above chart by years in the league:
Sadly, the short answer is no. Across all career arcs and all positions, the effect remains: players on new team perform worse. The nearest candidates are late-career WRs and RBs, who both score about 13% less post-trade. The trends are extremely cynical for early-career players: 41% lower for QBs, 26% for RBs, and 34% for WRs. This does not bode well for the aforementioned Cedrick Wilson.
What are the reasons for this? In short, they are many. Players are traded away or sign with a new team for a reason: usually, their contract no longer makes sense in the context of the production they provide to a team. Other teams are eager to make a deal, but this means a traded player has an entire new system, playbook, and team chemistry to contend with. Age plays a factor, as well as the team doing the trading away potentially ‘knowing something’. An interesting result in the data is that just-traded players have an average of 2.6 years left in the NFL, while players who haven’t been traded stick around for nearly a year more (3.5 years on average). This lends credence to the theory that teams won’t trade players they know will be available for longer.
Now, don’t hear what I’m not saying. There are reasons for hope: new schemes, new opportunities, improved play-calling and higher-skilled teammates all play a factor. While this story is mostly dire, there are players who buck the trend and break out post-trade. Brandon Marshall is probably the most notable example; indeed, his transition from the Chicago Bears to the New York Jets (he caught 14 touchdowns in New York) was the highest post-trade jump in our sample. Matthew Stafford is another example, re-invigorating his career with the Rams this past year.
I expect Russell Wilson and Allen Robinson to be the beneficiaries in this fashion for the upcoming season. Both are established players heading to teams with upgraded personnel and a concerted desire to maximize their talents. I wouldn’t draft Allen Robinson as high as he went last year (2nd or 3rd round pick) but he should see a real jump in production; same with Mr. Unlimited himself.
For the rest, though, this is a cautionary tale. You may recall Demarco Murray, who rushed for over 1800 yards with the Cowboys in 2014 only to depart for the division rival Philadelphia Eagles. Any catharsis found in fleeing to the enemy was a Pyrrhic victory for Murray, who notched just 720 yards on the ground with the birds the next season. This is an extreme example, but I, unfortunately, expect many of the hopes for high-flown free agents this year to fall similarly flat.
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Great article read, I wasn’t crazy high on adams and hill after the trades so it feels good to know there might be a reason why
Thanks for reading Keon! Yes, I agree…probably won’t be drafting them much this year.
Great read! The data bears out what Andy, Mike and Jason have oft mentioned on the podcast. Would be interested in seeing the T+2 data on early and mid career players who were traded. Perhaps these players have a bump in production?
Thanks for reading Amit! Yeah, that’s a good question…I can try to take a look.