This article is a follow-up to a previous article released about the NFL Draft. Seeing as that analysis was conducted before the 2021 NFL Draft, I wanted to release this secondary article to apply that analysis to this year's trades. I recommend reading the first article before returning here.
As mentioned in the previous article, there are two main ways I will analyze these trades: Jimmy Johnson draft value chart and the Approximate Value regression I ran in the previous article. Of the thirty trades that were transacted over the three days of the NFL Draft, only twenty were suitable for this type of analysis. The trades selected involve only swaps of draft picks (meaning that the Sam Darnold trade or Carson Wentz trade were not included) and all the draft picks were pick 224 or higher since Johnson's draft value chart only goes that far.
Since some of the trades involved trading picks from future draft classes, I employed no time discounting when adding up the relative values. You can argue that teams may value picks more now as opposed to later, but this changes team to team based on their salary cap situation and overall competitive timetable. For instance, the 49ers traded first-round picks in the following two drafts to avoid having to take decently sized contracts on their books. With contract extensions for key pieces like Nick Bosa and Fred Warner coming up, avoiding extra salary in the future can keep the core of the team together. Additionally, I predicted the position of future year draft picks by using Vegas win total lines for next year. Teams expected to make an improvement like the 49ers and Colts is factored in through this method.
With all that out of the way, let's take a look at these trades:
Team Trading Up |
Team Trading Down |
Pick |
Value Lost Johnson |
Value Lost Appx. Val. |
---|---|---|---|---|
SF | MIA | 3 | 585 | 49.77 |
MIA | PHI | 6 | 520 | 24.47 |
PHI | DAL | 10 | 70 | 11.30 |
CHI | NYG | 11 | 938 | 44.19 |
NYJ | MIN | 14 | 45 | 15.82 |
DEN | ATL | 35 | 12 | 5.40 |
NE | CIN | 38 | 7 | 15.29 |
CHI | CAR | 39 | 24 | 7.20 |
MIA | NYG | 42 | 155 | 13.13 |
CLE | CAR | 52 | 7 | 1.17 |
CAR | PHI | 70 | 0 | 4.22 |
NO | DEN | 76 | -18 | 8.23 |
GB | TEN | 85 | 6 | 7.44 |
SF | LAR | 88 | -38 | 6.44 |
HOU | CAR | 89 | 41 | 15.30 |
TB | SEA | 129 | 0 | 2.70 |
ARI | BAL | 136 | 40 | 4.30 |
LV | NYJ | 143 | 3 | 2.88 |
PIT | MIA | 156 | 25 | 2.73 |
HOU | BUF | 174 | -5 | 1.97 |
The first two columns should be self-explanatory: the first is the team that traded up and the second is the team that traded down. The middle column is the pick that the team moving up received in the trade. For instance, the first row of the table refers to the 49ers trading up for the 3rd overall pick and selecting Trey Lance. The fourth and fifth columns refer to the value lost by the team trading up. Again looking at the first row, this means the 49ers lost 585 units of value by the Jimmy Johnson chart (about the value of the 32nd overall pick) and 49.77 units by approximate value (about the value of Jadeveon Clowney up to this point in his career). Positive values mean the team trading up lost value: every team moving up lost value according to my Approximate Value regression. Negative values indicate the team moving up actually won the trade.
Despite both models not liking San Francisco and Cleveland moving up for the 3rd and 11th picks, they ended up picking quarterbacks. If those picks pan out and those players become great, no one will look at these trades as a failure. Great quarterbacks can alter the course of the franchise for fifteen to twenty years especially with rule changes making the position less physical and advances in nutrition, conditioning, and sports science. Miami trading up for a receiver on the other hand is far more suspect, especially with the success rate of receivers being the lowest of any position group.
Either way, the variation in each of these picks is decently high that any of the minor differences down the list of trades shouldn't be taken too seriously. Teams often have to jockey for draft positions to take players that fit team needs. Ideal trades generate value for both teams by matching the needs of both teams. We will see in years to come how these trades pan out.
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