Once again, the non-waiver trading deadline came and went, and the Rays left many fans wanting more.
While Toronto and Baltimore—teams essentially equal to the Rays in the standings—both geared up to make a wildcard push, the Rays sold two relatively minor but still useful pieces in Kevin Jepsen and David DeJesus for pitching prospects who may or may not help them in years to come.
Matt Silverman did nothing to improve the team right now, but he also didn't go into full-fire-sale mode, leaving most of the team to play out the rest of the season.
To deal with that question, we have to think about game theory. There are three types of strategies that are theoretically applicable to the Rays situation: optimal strategies; David strategies, and Goliath strategies.
Optimal strategies are very simple, and they're what teams should focus on most of the time. They boil down to one directive: "play better," or in the case of a front office, "run your team better."
Because statistical analysis in sports was introduced to so many people by the book and movie "Moneyball," there's a lot of confusion over it's application, with many thinking that sabermetrics is the tool of a small-market team. That's not true at all.
The inherent disadvantages baseball presents to small market teams prodded them—most famously the Oakland Athletics, but closely followed by others, including the Andrew Friedman Rays—to invest more heavily in statistical research. But the results of that research was not simply strategies for the underdog. What baseball teams learned was how to better identify good players, and in some cases, how to better help players improve themselves.
Figuring out which players help their teams win so that you can hire them, and getting the most out of the players you have, isn't some wacky niche. It's what everyone—both the Yankees and the Rays—should be trying to do all the time.
What's the effect of employing a better strategy? A higher probability of winning. Think of any given team as having a certain range of possible outcomes. This can be represented by a curve. The peak of the curve is their most likely outcome, and as they move off the peak to the right, that represents the chances of them playing better, while off the curve to the left represents the chances of playing worse.
This curve can be used to represent the probably outcomes of a single pitch, one game, a season, or a decade of seasons. The scope and the units on the X axis do not change the basic model.
Devising and implementing a new optimal strategy makes the team better, and it does so not by changing the distribution of probabilities on the curve, but by shifting the entire curve in the right direction.
This is essentially what Jonah Keri talks about the Rays front office trying to find in his book, The Extra 2%. When the distribution of probabilities cannot be changed, it's the Rays impetus to find small advantages in every facet of running the franchise so as to shift their curve as far to the right as possible.
The blue curve below shows the original curve of probable outcomes for a team, while the orange curve shows the probable outcomes after they have successfully implemented a new, better strategy.
David and Goliath Strategies
But while optimal strategies increase a team's chances of overall success and should be used by all teams in all situations, there are other strategies that might be attractive either to good teams or to bad teams, but that are only appropriate in certain situations. These are called "David strategies" (for underdogs) and "Goliath strategies" (for topdogs)
A Goliath strategy is one that, while it may limit the total potential of a team, decreases the variance of the possible outcomes, squeezing the probability curve. This is attractive to topdog teams, who have a higher level of expected performance than their opponents, meaning their curve is already farther to the right. The team may find itself in a situation where the most likely possibilities on the curve grant them success, and where failure comes from them having an uncharacteristically bad performance. The Goliath strategy helps the team lower the chances of that bad performance by clustering odds around their current characteristics of performance. .
On the other side of the spectrum is the David strategy, which may decrease a team's overall potential, but increases the variance of possible outcomes. A team currently break-even (.500) in the standings that employs a David strategy may turn themselves into a .400 team over the long term, but over the short term may increase their likelihood of playing like a .600 team. For a team positioned farther back along the X-axis, this strategy is advantageous if they're about to enter an elimination series against a true-talent .600 team.
Below are three different curves. The blue curve is an average team playing a normal strategy. The orange curve is an above-average team playing a Goliath strategy. The grey curve is a below-average team playing a David strategy.
The X axis is quality of outcomes and that the Y axis is probability of those outcomes. So if all three teams achieve only an average outcome, the Goliath will finish comfortably in front of the crowd, but if all three perform to a higher or lower extreme, the David will actually come away victorious over both of the 'better' teams.
Who is David? Who is Goliath?
Well, the theory is easy, but it takes a lot more work to adapt it to real-life game situations, and even this most basic of questions is difficult to answer. In the long term, the Rays, the Athletics, and the other relatively-poor small-market teams in the league are all David, while the Yankees, the Red Sox, the Dodgers, and all of the other large-market teams are Goliath. But over the short term it's not that simple.
For example, the Philadelphia Phillies have more resources at their disposal than do the Rays, but since their meeting in the 2008 World Series, the Phillies have made a string of poor management decisions that have maneuvered them to the bottom of baseball. It's fair to say that with the qualities of front office that each team currently has, the Rays are Goliath to the Phillies David.
And when the scope is limited to the span of a single season, strength of front office should get tossed out of the window, and a golden generation of players all maturing at once can turn a perennial minnow into the strongest of Goliaths.
The best way to think of this question is that whoever is able to use their resources most effectively by implementing the best, most optimal strategies becomes Goliath for as long as they're able to maintain their advantage. There was a time when the Friedman-Era Rays were the smartest guys in the room. For the span of a few years, they were Goliath, and it's a real shame they didn't win the World Series when they had their best chance.
I think it's fair to say that those days are over. We'll find out over the next five years exactly how much that's changed.
I Thought This Was About the Trading Deadline
To apply analysis to trades, it's helpful to convert all of the possible trade pieces into a like currency: money. The way this is done is by calculating the surplus value for players. Player salaries are paid in money of course, but their contributions on the field can be represented as how much money they earn their team—more wins means more local popularity, more ticket sales, more jersey sales, higher TV ratings, more lucrative TV contracts, etc. The amount of money per each additional win is governed by the separate economics of each individual team, and by their position on the win curve.
The thing that makes deadline trades special is that by deadline time, teams have a pretty good idea about their current position on the win curve, so they can make much more accurate evaluations of how much a certain player is worth to them than they can in the off-season, or even earlier in the year.
At the start of the season, a player making $7 million and winning his team one more game than a replacement player would might appear to have a marginal value of $0. That is to say he's payed exactly what he'll likely produce, on average. But at the trade deadline, context is important. A team that knows that his one extra win might push them into the playoffs might actually value his contributions at $15 million, while a team that knows that his one extra win will push get them to 75 wins could value that at only $1 million.
In this situation, the two teams should be able to work out a deal, trading him from the team that views him as having a declining surplus value to the team that views him as having a surplus value much higher than his salary. Trades like that are optimal strategies. Both teams are made better by the trade, and every team in baseball should (and mostly does) participate in this trading market.
But while the optimal strategy is to always choose the trade package that brings the highest overall marginal value, when teams start to have preferences for the composition of what return package they want when they trade major leaguers at the deadline, they're getting into David and Goliath strategies.
Prospects, by their very nature of being unfinished, carry wider variances than major league players. This spectrum is open for debate (especially the high-minors hitters/low-minors pitchers part), but here's my hypothesis, listed from lowest variance to highest variance:
MLB hitters - MLB pitchers - high-minors hitters - high-minors pitchers - low-minors hitters - low minors pitchers
If a team views themselves as a Goliath, they may tend toward preferring to trade for the players at the left side of the spectrum, while if they view themselves as a David, they may instead prefer to acquire players at the right side of the spectrum, hoping for higher value with a more drastic variability.
Photo credit: Andy Marlin-USA TODAY Sports
Let's Get to the Rays
During the latter portion of Andrew Friedman's time, I think it's fair to say that the Rays acted like a Goliath in their trades. Friedman succeeded in building a good core that was capable of competing for the playoffs every single year, and made it a priority not just to acquire prospects, but to acquire some players (either prospects or major leaguers just starting out their careers) who were would be able to help the team immediately.* Following this plan, Friedman acquired players like Wil Myers and Drew Smyly -- young, controlled salaries, ready to contribute.
Even more clear, Friedman signed and then extended Goliath players like James Loney and Yunel Escobar. Both of those players were aging major leaguers with limited upsides, but who were a good bet to be competent as starters. Rather than pursuing players who might become stars or who might tank, those two helped to mitigate risk and lower the overall variance of the Rays.
*We should note that Friedman's trades often did well in surplus value analyses, so it's probably reductive to say he was just pursuing Goliath strategies.
It's too early to tell whether Matt Silverman is playing things differently (signing Asdrubal Cabrera for a market value contract was something of a Goliath move). But it is interesting to note that the three players he acquired by trading David DeJesus and Kevin Jepsen were all low-minors pitchers. We don't know if anything else was offered, but if something of similar value was that included other types of players, Silverman chose the David strategy.
On the other hand, there were three other players with limited surplus value** on short-term contracts that Silverman did not trade: Cabrera, James Loney, or John Jaso. If he was fully embracing the David role, he would have traded those players as well, likely for something young and high-variance.
The fact that he didn't move these trade candidates either means that he didn't receive any offers that he thought matched the production the Rays would receive from those players as they finished the season in Tampa Bay, or he wasn't willing to make trades in search of variance alone.
**It should be noted that if the Rays do not make the playoffs, that doesn't make the games they win in August and September worthless, it merely means they were worth less than wins that propelled a team to the playoffs.
The Nathan Karns Trade that Didn't Happen
There were rumors before the deadline that the Rays were listening to offers for starting pitcher Nathan Karns. This was exciting for several reasons. First off, there was no obvious reason to trade Karns. He's a pretty good pitcher with five years of team control left. If he were to be traded, that would likely mean that the Rays were getting something extremely valuable back in return. If it had happened, it would probably have been an optimal strategy trade, with someone offering just too much, because there really wouldn't be any other reason to pull the trigger.
If, however, Karns had been traded for prospects (even very good ones) who were not 100% major-leauge ready, that would have signaled a radical shift toward David strategies. Giving up a known and producing commodity with years of affordable team control for a relatively unknown one has not been the Rays Way in recent times.
Photo credit: Nick Turchiaro-USA TODAY Sports
Goliath in Toronto and Baltimore?
They're only a short distance ahead of the Rays in the standings, but both the Blue Jays and the Orioles behaved very different than the Rays at the trading deadline.
The Jays traded their top pitching prospect for two months of David Price and also acquired Ben Revere (giving up prospects), while the Orioles gave up their eighth-rated prospect to acquire Gerardo Parra.
In doing so, each team hasn't just traded future wins (via prospect) for current wins (via veteran), but they've also traded a greater number of risky wins (prospects are volatile) for a lesser number of more certain wins (veteran performance is less volatile).
One or even both of them may receive the hoped-for windfall of making the playoffs, which will make up some or all of the difference, but if they do not, they will have both narrowed their performance curve in the short term, and shifted to the left their performance curve in the long term. That could be a benefit to the Rays and their more reserved approach.
Flip back up to the graphs, and note how the Goliath curve leaves itself open to be beaten by an excellent effort by an underdog, and then imagine how quickly that probability grows if the underdog is able to employ additional optimal strategies to shift their entire curve to the right. Where you place the Rays and their David-like graph along the X-axis is then the determining factor.
Of course, it's worth noting that the Yankees—the true Goliaths in the division—also held steady at the deadline. They were allegedly pursuing Craig Kimbrel, but when the asking price was too high, the refused to step into a long-term Goliath strategy and held on to their prospects. They, too will be in a better position to defeat the Jays and the Orioles in the future.
There's really not a lot of information to draw from yet, though the early moves of Matt Silverman's career suggest a slight shift away from the Friedman-Era mindset.
Andrew Friedman built a team that operated very efficiently and turned itself into a contender despite its small budget. Part of the Rays system was refusing to behave like traditional Davids and focusing on the optimal. But, especially towards the end of his time in Tampa Bay, the Friedman Rays actually began to make Goliath-type moves in targeting young, MLB-ready players (Smyly, Myers).
That's a practice that, at this trading deadline at least, Matt Silverman has not continued.