Way back in August of 2009, I tried to evaluate major league front offices on how efficiently they were spending their payroll dollars, building on the work of Doug Pappas and Nate Silver. I called it MR3/ExpMR-which was horrible. So from now on, we’re going with Payroll Efficiency Rating, or PER. So there.
Anyway, I think we nailed the high end. Teams like the Rays and Red Sox dominated the top of the charts, while the previously overrated Marlins and underrated Yankees converged in the middle. But on the bottom end, there was still a major bugaboo, as I mentioned:
If there’s still a piece missing, it’s the value that comes with finishing last. The first pick in the draft is worth a lot more than the fifth or the tenth or the fifteenth, so a team that wins 59 games, as the Nationals did last year, should have that factored into its marginal revenue figures.
So there’s still some work to do, but the process is actually pretty straightforward: figure out which pick each team should expect to get, based on their third-order win total, and about how much that pick is normally worth, in terms of future value. (For this, I used Sky Andreychuk’s draft-pick value calculator, which holds up pretty well under heavy testing.)
Before we get to the numbers, let’s acknowledge the five-hundred pound elephant that’s about to walk into the room: this adjustment rewards teams for sucking. In fact, the worse a team is, below somewhere around 75-80 wins, the better they’ll come out in the final rankings. So maybe we’re rewarding incompetence, in some cases. But the reality is that teams are usually better off trying to win 60 games than 81-81 is a moral victory, while 60 could get you Justin Upton.
So with that said, here’s the bottom ten with the old system (but updated for current third-order winning percentage), followed by the new one. Also, a big hat tip to Eric Seidman, who ran simulations to find expected draft positions, based on teams’ win totals.
Bottom 10, Old Way Team PER Padres 0.90 Nationals 0.90 Cubs 0.89 Brewers 0.88 Orioles 0.84 Royals 0.80 Mets 0.76 Pirates 0.76 Astros 0.75 Reds 0.75 Bottom 10, New Way Team PER Orioles 0.96 Reds 0.96 Indians 0.95 White Sox 0.95 Mariners 0.94 Brewers 0.93 Tigers 0.84 Astros 0.82 Cubs 0.80 Mets 0.72
For the curious, here’s the full data. The Pirates (15th in the new rankings), Padres (17th), Nationals (19th), and Royals (20th) move out of the bottom ten, which shouldn’t be a big surprise, given their expected draft positions. Meanwhile, the Mets, Cubs, and Tigers all fall a few places, with the Mets now bringing up the rear. If you’re surprised to see the Tigers there, just check out their third-order winning percentage, which would have them winning 78 games. Also-and are you allowed to do two parentheticals in a row? Whatever-you’ll notice that the numbers are higher in the new version, but this is actually just a function of the top and bottom converging. The 30-team average is actually down, from about 1.17 to 1.09.)
At the top, the Rays keep the top spot, despite their troubles lately (the third-order standings still have them ahead of the Red Sox), while the Dodgers, Rockies, Red Sox, and Cardinals round out the top five. The top eight teams in terms of third-order winning percentage are all in the top half of the league, and all but the Phillies are ahead of the no-cost Marlins.
So integrating draft-pick values didn’t rock the boat at the top of the chart, which I think is a good thing. But there are a lot more questions we can now try to answer with this data. For example, where is that key cutoff point where your team is actually better off losing? We can take the expected pick value curve, add the totals to Nate Silver’s marginal revenue curve, and see where the dips are:
Some notes:
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This isn’t perfect. It probably overstates the value of winning 75-80 games, for example. But remember something: this doesn’t take into account the expense side. Using the 60 versus 81 example from above, the two are very close on the chart. But all other things being equal, an 81-win team should cost you more than a 60-win team. So while the “revenue” side might be similar, the ROI should be much higher for the 60-win team, and it’s obviously far less risky.
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There’s a steady drop between 60 and 70 wins, because a team’s chances at the number-one pick start going down very quickly in that range. In Eric’s simulations, teams that won around 60 games had about a fifty percent shot; teams that won 70 didn’t get it a single time, in over 65,000 tries.
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It’s still a lot better to win 100 games than 50.
If there’s another obvious practical application with this, it’s to show how much better it is for a small-market team to win than to simply fold up the tent and go for the number-one pick. Even with draft picks factored in, the Rays are still an easy number one, and the Pirates, Nationals, A’s, et al are in the middle of the pack. In terms of pure return on investment, a winning team always justifies a few more payroll dollars.
However, it’s also important to remember the constraints that these teams are working under. For example, if the Pirates were on pace to win 92 games instead of 62, we would expect them to bring in about $35 million more in revenue; that’s a decent chunk of money, but try improving your team by thirty wins in free agency-where a win usually goes for $3-5 million-with only $35 million. The only way that small-market teams can build economically viable contenders is through player development or trades; we already knew that, of course, but it’s an important reminder for Pirates fans who are about ready to hang themselves after watching the team go 3-22 over the past few weeks. (For what it’s worth, the Yankees’ expected revenue would go up by $140 million if the team went from 62 to 92, which makes their strategy actually seem somewhat reasonable.)
There are plenty of other potential applications of this, which I’m sure I’ll get to at some point. In the meantime, if anyone has ideas, fire away in the comments section.
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The difference this year for the Orioles is that, although they are losing, they have used the year productively to introduce significant new talent to the major leagues, including, Matt Wieters, Nolan Reimold, Chis Tillman, Brian Matusz, Brad Bergesen, Jason Berken, David Hernandez. They have also shown substantial improvement in several of their young players who were not rookies: Adam Jones, Felix Pie.
It's been a losing year, but a productive year.
If there's a smart way to do this, I'd up for adding it. But I actually like not having it factored in, b/c it gives teams credit for having depth.
Unless a GM SETS OUT to lose a bunch of games and get a good draft pick, I don't think it makes any sense to reward a GM whose team loses a bunch of games and gets a high draft pick.
If you want to include the draft in GM ratings, why not compare how a teams draft picks do relative to expectations for the spot, rather than just rewarding a GM for running a team that gets a high draft pick.
It seems to me that the purpose of the exercise is to identify the GMs who have contributed the greatest possible (quantifiable) value to their franchises. And while it is the case that a GM may or may not be intentionally setting out to finish in the bottom of the standings, it is nearly indisputable that a team that receives the number 1 draft pick has obtained greater added value than the team that receives the number 15 draft pick.
Including draft pick value goes along with a long-held principal among analysts that it is better to rebuild than to tread water.
"If there's still a piece missing, it's the value that comes with finishing last."
By that standard the GMs of the Tampa Bay DEVIL Rays must have been geniuses for 10 years.
Did they make some good draft picks? Yes. Did they build their brand with ten years of losing? Look at all the Yankee and Red Sox fans in their stands.
I think there was an excellent series of articles on the depreciating value of draft picks in the first round based on lifetime VORP. The article did point out, from a historical analysis, that the talent was front-loaded early in the draft.
But not only was the annual VORP number small (due to a large number of flunkies) but the teams on the cheap would only capture a fraction of the lifetime VORP (due to retaining the players for only six years on their careers).
Are you still using a linear model for expected wins? IIRC, last time I and a few other people suggested a logarithmic model, to account for the diminishing returns of dollars tacked onto larger payrolls. Any thoughts on that?
It's kind of like saying people who got ARM balloon mortgages, foreclosed, then got bailed out by the government so they could keep their house at a cheaply refinanced rate (because interest rates are so low currently) are better at managing their finances than blokes like me who got a fixed rate mortgage I can afford...