Bill traded up to pick 7 to get QB Josh Allen.

Josh Allen Trade
Buffalo Bills Buccaneers Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
7 32 12 35
53 22
56 19
Total 32 Total 76
44 2.38

~~~
The Cards moved up to pick 10 to draft Josh Rosen
~~~

Josh Rosen Trade
Cardinals Raiders Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
10 41 15 28
79 18
152 9
Total 41 Total 55
14 1.34

~~~
Saints move up to get Marcus Davenport, DE
~~~

Marcus Davenport Trade
Saints Packers Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
14 29 27 25
147 8
(25) 24
Total 29 Total 57
28 1.97

~~~
Bills go up to get Tremaine Edmunds
~~~

Tremaine Edmunds Trade
Bills Ravens Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
16 32 22 27
154 12 65 21
Total 44 Total 48
4 1.09

~~~
Packers trade again to get Jaire Alexander
~~~

Jaire Alexander Trade
Packers Seahawks Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
18 29 27 25
248 5 76 17
188 5
Total 34 Total 47
13 1.38

~~~
Titans trade up for Rashaan Evans
~~~

Jaire Alexander Trade
Packers Seahawks Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
18 29 27 25
248 5 76 17
188 5
Total 34 Total 47
13 1.38

~~~
Ravens trade 2019 assets to get their QB
~~~

Lamar Jackson Trade
Ravens Eagles Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
32 23 52 22
132 11 125 15
(48) 25
Total 34 Total 62
28 1.82
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There are a number of ways to analyze a draft trade. You can do it by comparing the actual players selected (though that takes time), you can do it by trade value, as measured by a trade chart, or you can do it by using the Pro Football Reference statistic approximate value. There are charts of approximate value per draft choice and those charts can be used to calculate trade values and risk immediately.

The recent blockbuster trade by the Jets involves substantially more risk than the last five major trade ups in the NFL (here, here and here). To make these calculations I assume the Jet’s pick next year will be the 10th pick in the second round, hence the 42nd pick.

Trade for 3rd Pick
Jets Colts Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
3 45 6 39
37 28
49 20
42 25
Total 45 Total 112
67 2.49

 

With a risk ratio of 2.7 2,5, the risk incurred by the Jets is a bit less to what Washington put up with in the RGIII trade. It’s also comparable to the Earl Campbell trade. The last two trades were high risk – never paid back kinds of trades (though with Earl Campbell, the team’s competitiveness during his peak years may have been enough emotionally for the Oilers).

Update: recalculated risk, which now stands at 2.5 instead of 2.7.

This would have been done earlier, but Pro Football Reference dropped its very handy chart of draft position versus AV. I started missing it more and more, and using the Wayback Machine I found it here.

The three major QB trades of 2017 were the trade for Mitch Trubisky, Patrick Mahomes, and Deshaun Watson. We will analyze them in sequence.

Mitchell Trubisky Trade
Chicago Bears 49ers Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
2 46 3 45
67 19
111 12
(71) 21
Total 46 Total 97
51 2.11

 

The Bears have a trade risk comparable to a typical trade for a #1 draft choice and a quarterback at that. The trade has less fundamental risk than Goff or Wentz. The comparable that comes to mind is Eli Manning. By contrast, the delta AV of the other two trades are substantially less.

Patrick Mahomes Trade
Chiefs Bills Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
10 41 27 25
91 17
(25) 24
Total 41 Total 66
25 1.61

 
Mahomes merely has to give six seven good years, and the trade ends up warranted. The issue in the case of Deshaun Watson is keeping him upright. A fistful of whole years almost as good as his freshman year in the NFL and he would end up bordering on Hall of Fame numbers.

Deshaun Watson Trade
Texans Browns Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
12 35 25 24
4 44
Total 35 Total 68
33 1.94

 

So here is wishing Deshaun Watson a healthy career from now on.

I didn’t expect another trade of this magnitude, and so quickly. But let’s crunch the numbers on this trade, and compare them to the 2016 Titans-Rams trade.

The Browns received from the Eagles, the #8, #77 and #100 picks in this draft. In 2017 they receive the Eagles first round pick. In 2018 they receive the Eagles 2nd round pick. The Eagles have received the #2 pick in this draft, and the Browns 4th round pick in 2017.

For the purposes of this calculation, we assume the Eagles will pick 20th in 2017 and 2018, and that the Brown in 2017 will rise from 2nd to 10th.

 

The AV costs of the 2016 Eagles Browns trade.
Eagles Browns Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
2 46 8 40
(138) 8 77 12
100 17
(20) 29
(52) 22
Total 54 Total 120
66 2.22

 

The Delta AV for both trades are the same, but since the Eagles received a lot less AV, the relative ratio of AV given to AV received is higher. The trade cost is the same, but the purchase is more highly leveraged.

Determining how to assess draft trades in the NFL is not hard (see here, here, and here). Ever since Pro Football Reference went through the trouble of determining what average AV can be assigned to a draft slot, it’s merely a matter of counting. The technique has some variance, as the draft slot of a future pick is not known. Even so, with a bit of conservative extrapolation, you can still get a feel for the overall cost of a trade.

 

First, the numbers:

 

The AV costs of the 2016 Rams Titans trade.
Rams Titans Results
Pick Average AV Pick Average AV Delta AV Risk Ratio
1 51 15 28
113 14 43 24
177 5 45 25
76 17
(20) 29
(84) 13
Total 70 Total 136
66 1.94

 

In the data above, we assume that the Rams will improve 5 slots in draft placement, so that the first and third they sent to the Titans would be picks 20 and 84. If the Titans end up 18th or 23rd, it’s notable that the difference in value at this point is less than the point-to-point deviation, so that kind of change won’t affect the calculation much. Pro Football Reference’s raw data are moderately noisy.

The Rams total investment is 136 AV, roughly equal to the career value of John Elway. That’s not entirely accurate, as the Rams actually received three picks in return, and if the other two return 19, then the player they pick at #1, to return the value of the investment, only has to yield 117 AV.Now, 117 points is about mid in between Phillip Rivers and Aaron Rogers in value.

Update: Johnny Unitas, at 114, is a closer comparable.

In terms of risk, the trade is riskier than the Eli Manning trade, and less risky than the RG III trade or the Earl Campbell trade. For 9 more AV than the RG III trade, they received 24 more AV in return.

Best of luck to the Rams. I hope their picks work out well for them.

This has been part of an ongoing conversation among Dallas fans, and perhaps among any of the 9 teams, from the Redskins to Patriots to the Vikings, that traded up in the first round of the 2012 NFL draft. There are some new tools for the analyst and the fan, and these include: (1) Pro Football Reference’s average AV per draft choice list, (2)  Pro Sports Transactions’ NFL draft trade charts, and (3) The Jonathan Bales’ article on Dallas Cowboys.com where he analyzes a series of first round trades up from 2000 to 2010. He concludes that in general, the trade up does not return as much value as it gives.

I suspect that Jonathan’s conclusion is also evident in the fantasydouche.com plot we reposted here. The classic trade chart of Jimmy Johnson really does overvalue the high end draft choices. You’re not paying for proven value, but rather potential when you trade up. I suspect by the break even metric we chose, comparing relative average AVs, that many draft trades never pay off, in part because people pay too much for the  value they receive. This is most evident in trading a current second or third and a future first for a current first round draft choice. These trades tend almost to be failures by design, and smack ultimately of desperation, true even when the player obtained (e.g. Jason Campbell) actually has some skills.

That said, how many of these players exceed the average abilities of the slot in which they were drafted? Now that we have the PFR chart, this is another question that can be asked of the first round players. Note that Jonathan Bales’ study doesn’t really answer the question of how good the player becomes, in part because the time frame chosen doesn’t allow the player adequate development. I started in the year 2000 1995, ended in the year 2007. I identified 67 players in that time frame, and I compared the AV for each player as given by the weighted average on the PFR player page. I’ll note that the player page and the annual draft pages do not agree on players’ weighted career accumulated value, so I assumed the personal pages were more accurate.

As far as a scale, we’re using the following:

AV relative to average Ranking
-25 AV or more Bust
-24 to -15 AV Poor
-14 to -5 AV Disappointing
-4 to +4 AV Satisfactory
+5 to +14 AV Good
+15 to +24 AV Very Good
+25 AV and up Excellent

 
Note there are some issues with the scale. Plenty of players from 1995 through 2007 are still playing, and their rankings are almost certainly going to change. In particular, Eli Manning at +24 and Jay Cutler at +23 have a great chance to end up scored as Excellent before the next season is over. Jason Campbell is at +19, and if he starts for a team for one season, he will end up with a ranking of Excellent. Santonio Holmes (+19) also has a shot at the Excellent category.

Players in the years 2006 and 2007 in lower categories (Manny Lawson at +7, Joe Staley at +4, Anthony Spencer at 0 ) could end up as Very Good, perhaps even Excellent if their careers continue.

The scoring ended up as

Scale Number Percent as Good Percent as Bad
Excellent 14 20.9 100.0
Very Good 9 34.3 79.1
Good 13 53.7 65.7
Satisfactory 10 68.7 46.3
Disappointing 7 79.1 31.3
Poor 5 86.6 20.9
Bust 9 100.0 13.4

 
Data came from the sources above. A PDF of these raw data is here:

NFL Trade Ups

Update: Increased the dates of players considered from 2000-2007 to 1995-2007. Moved Ricky Williams back to 1999.

There were, of course, two substantial trades of Ricky Williams. The first netted the Washington Redskins the whole of the Saints 1999 draft, plus the Saint’s first and third round picks of 2000. Three years later, Ricky was traded to the Miami Dolphins for a pair of first rounders, plus change. The first was obviously not paid off. How did the Miami Dolphins fare in their trade, using our new risk metrics?

Risk Ratio no longer makes sense as a term when you’re talking about someone already drafted. The important term becomes the net risk term, 52 AV. That’s 1 more AV than the typical #1 draft choice, and that’s the amount of AV Ricky had to generate in order for this trade to break even. And note, these calculations are derived from weighted career AV, not raw AV. So any raw AV we apply to these numbers is a rough approximation (A typical career summing to, say, 95 AV, might end up around 76 or so WCAV).

That said, Ricky Williams had a great first season with the Dolphins, generating 19 AV in that season alone. His total ended up somewhere around 57 AV. I’d suggest the second trade approximately broke even.

End notes: I’ve seen a lot of discussion around  this set of data, discussing the quality of draft picks on a per pick basis, posted in of all places, a Cav’s board. If this board isn’t the original source of these graphs, please let me know. An excellent resource for high quality NFL draft trade information is here. And finally, a reader named Frank Dupont writes:

I wrote a book about decision making in the NFL.  It’s sort of a pop science book because it seeks to make what happens in the NFL understandable via some work that people like David Romer, Richard Thaler, and Daniel Kahneman have done.  But because all pop science books make their point through narrative, I spend a lot of time looking at why football coaches are so old, but other game players like chess players and poker players are so young (Tom Coughlin is 65 and yet the #1 ranked chess player in the world is 21, the world’s best poker players are 25-ish).

The link for the book is here, if this topic sounds interesting to you. I’ll only note in passing  that while physics prodigies are common, biologists seem to hit their stride in their 60s.  Some areas of knowledge do not easily lend themselves to the teen aged super genius.