It’s been awhile, but time for another post in the Thought Experiments category. Assume the following:

- On May 1st, 2013, an average owner, average general manager and average coach are assigned an expansion team. They are randomly assigned 24 players: one from each of the seven rounds of the 2011, 2012, and 2013 drafts. So this expansion team has a 1-in-32 shot at getting Cam Newton from the 2011 first round and a 1-in-32 chance of getting Green Bay offensive lineman Derek Sherrod. There’s a 1-in-32 chance the sixth round pick from the 2012 draft lands on the Alfred Morris pocket, but more likely than not Lady Luck will give them a generic sixth rounder. As for the final three players, the team is randomly assigned from each draft class one of the X number of undrafted players that ended up making an opening day roster that year. So while it is technically possible this team could get someone like Vontaze Burfict, it’s much more likely to be a Junior Hemingway, David Douglas or Martell Webb. Finally, assume in this magical world that while random, the 24 picks work out in this team’s favor as far as spreading the roster: they don’t end up with 6 quarterbacks and zero defensive lineman, and instead things are magically balanced.
- On May 2nd, this team is able to poach anyone on any roster
*provided*that such player is making the veterans minimum. The team can also sign players currently not on any roster, but it must be of the veterans minimum variety. The team can sign anywhere from 29 to 50 of these minimum players, with the spread based on how many of the 24 players from above the team decides to roster (and they can roster more in training camp, but must be at 53 by the start of the season).

**Suppose we simulate this process and play out the 2013 season 10,000 different times. On average, how many games does this mean win per season?**

One thing that you might want to keep in mind. While some teams have gone 1-15 and the 2008 Detroit Lions went 0-16, those records do not represent the true winning percentages of those teams. If we simulated the 2008 Detroit Lions season 10,000 times, they wouldn’t go 0-160,000. When Neil talked about the Tangotiger Regression Model, he added 11 games of .500 football to get an estimate of a team’s true ability level. That would put the ’08 Lions at a .204 winning percentage, or 3.26 wins in a 16-game season. The Lions also has a Pythagorean record of 2.8-13.2, so perhaps we can say they were a 3-win team that was really unlucky. On the other hand, Brian Burke had those Lions at 1.8 wins and Football Outsiders had them at 2.1 wins.

Of course, there are many differences between the 2008 Lions and our mythical expansion team. Just food for thought.

{ 17 comments… read them below or add one }

If you want just a spitball, I would guess in the neighborhood of 4.5-5 wins as the average.

That seems a little high to me. Sigmund Bloom and Mike Clay both said 3 wins on twitter, which seems a bit closer to what my gut says. I think the issue is you’ve got a roster with 45+ scrub-type players.

I expect that I’m going to be guessing higher than most.

I think that talent gaps in the NFL are generally overstated and the worst team performances are actually the result of poor front offices and coaching more than talent level.

I was thinking around 5 wins. It’s really tough to average less than four wins, and this is going to be a pretty bad team (at least early on…)

It’s hard because this is just theoretical: we’ve never seen some really terrible teams be simulated 10,000 times, so our views are a little biased. One person on twitter said 0-1 wins, but that seems crazy low to me. But there’s no real way of proving wrong or right.

Well Aaron Schatz has probably simulated terrible teams 10,000 times. Each year in his pre-season book, he has run the season 10k times and it’s rare for each year’s worst team to be projected for less than 4 wins – just as the vegas lines illustrate. So even when there are really bad teams around, 4 wins is basically the floor.

I think the hard part is gaging just HOW terrible this team would be. If this team is WOAT material, which is certainly within reason, I think you’d have to go with slightly less than 4 wins. If it is slightly better than WOAT – which i think is reasonable – you arrive somewhere around 5 wins. But it’s certainly a crapshoot and, therefor perhaps, a great though experiment.

The Texans do seem to be a fair comp, and they got about as unlucky with their 1st overall QB as you can get, and still STILL won 4 games.

But, Danish, in Schatz’ sims, he is using real rosters. Real teams that have guys like Rivers, Brady, Brees, Rodgers, Steven Jackson, Ray Rice, DeMarcus Ware, Patrick Willis, etc. etc. Guys who have been around for longer than 3 years. This hypothetical team is going to have zero quality players with more than 3 years experience.

Yes, but teams that are as bad as this one, is not going to have many players like that, not in reality or in experiment (except for Steven Jackson on the crappy Rams).

In 2008 the Lions won zero games. On their roster was by my rough count 6 players that had +3 years of experience and were not replacement level talent: Dominic Raiola (30), Jeff Backus (31), Roy Williams (27, traded midseason), Jason Hanson (38), Cory Redding (28), Leigh Bodden (27). This is 2008 Lions quality veterans. None of these are players I’d have trouble swapping for a random newly drafted player.

The story is about the same in 2009: 4 guys; Backus, Raiola, Julian Peterson (31) and Larry Foote (29). Again this is production that can easily be substituted with minimum guys and young players.

The point of all this: While I don’t have those particular volumes of Pro Football Prospectus/FO Almanac, I’d be surprised if the 2008, 2009 or 2010 Lions were projected to win less than 4 games – even with these ridiculously terrible teams that are certainly comparable to this experiment team. The fact that they won 0 and 2 games is somewhat academic – it’s the projection we’re after.

I would think the Texans would be a good base for the experiment. The description fits them starting out fairly effectively just with different draft years.

True — that team had very little, and did manage to win four games. http://www.pro-football-reference.com/teams/htx/2002_roster.htm

You could also use players that fit the description and use their WPA and EPA, from AFS, to fill in numbers for the team and simulate it out. It might take a few of simulations varying on where they got their QB (1st round draft, vet. min. scrub, etc.).

*ANS not AFS

I would estimate around 3 wins on average. I just don’t think a team is going to be very successful with a pile of guys who have been in the league 3 years or less. You need some veteran studs to make a team decent.

Surely, there’s some math that relates AV to wins or pythagorean wins or whatever. If we used the ’10 to ’12 drafts instead of the ’11 to ’13 drafts, then all you have to do is turn the thought experiment into real rosters (e.g., move the random picks from their current teams to the expansion team, have the expansion team randomly acquire 29 guys playing in ’13 at the veteran minimum, etc.), use the math to produce new values of “team quality” for each team, and run the 10,000 simulations. Main obstacle — besides the headache of doing all that — would be how to divine a 33-team NFL schedule…

…and also, don’t call me Shirley.

Here are the adjusted wins* for the expansion teams since 1960:

DAL, 1960 = 0.7

MIN, 1961 = 3.4

ATL, 1966 = 3.4

MIA, 1966 = 3.4

NOR, 1967 = 3.4

CIN, 1968 = 3.4

SEA, 1976 = 2.3

TAM, 1976 = 0.0

JAX, 1995 = 4.0

CAR, 1995 = 7.0

CLE, 1999 = 2.0

HTX, 2002 = 4.0

My gut is these 12 seasons capture the rough range of possible outcomes, 0 to 7 wins. A 10,000 season simulation would probably give you a few more high-win outliers and a number of zero-win seasons which would outnumber the count of 7+ win seasons. The average would be around 3 wins. The ’60s expansion teams were remarkably consistent around this number and my sense is you’re postulating a talent pool close to what they had to work with.

A big advantage for your team is that it would have an owner, GM, and HC better than half of the NFL teams, so maybe my gut is under-estimating how much they could do with the talent available.

*Adjusted wins = # of actual wins plus 0.5 times # of actual ties converted to a 16 game schedule. For example, 1-12-1 equals 1.7 adjusted wins.

Interesting stuff. Thanks.

3 sounds about right. I know the point is that we don’t know exactly who the players are, but it does seem like there could be *wild* variations based on the quarterback alone. If a team like this ends up with, say, Brandon Weeden at quarterback? 1-2 wins sounds about right. The other thing is that a team like this would be particularly vulnerable to injuries. There are going to be a lot of really bad players on the rosters, and a few injuries (losing at least 3-4 guys for significant amounts of time seems like at least the median injury situation for an NFL season) would be seriously disastrous.

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