We’ve looked at the high level realities the Blue Jays face as they enter this winter at the crossroads between making a push in 2018 and rebuilding.
Now for a more practical consideration, and yet perhaps the most critical question: what is the likelihood that they can legitimately contend in 2018? This means making a realistic, clear-headed assessment of where the roster currently stands, and where it’s possible to get to by the Spring.
That involved an incredible amount of uncertainty, but I’m going to take a crack at it, at least a good first pass.
Let’s start with my 2018 lookahead from earlier this month. At most positions the 2018 roster is pretty settled, given the eight players under contract, another seven through arbitration that will be tendered, and some other contracts renewals who figure to be on the roster. Here’s what my 2018 roster from internal resources looked like, with no roster movement since.
For this purpose, let’s non tender Koehler and Goins, replacing them with whomever from the column at the right at minimum salary. That roster would cost upwards of $140-million.
Now to estimate their production. The common approach is to make a point estimate for each player (say 6 WAR for Donaldson), add it up, and figure out what it means for wins. But this doesn’t account for uncertainty, which, especially for a lot of Blue Jays like Aaron Sanchez, Devon Travis and Troy Tulowitzki, is significant.
To bring in uncertainty for each of the 14 players in the forecasted lineup and starting rotation, I estimated five possibilities for playing time (PA/IP), and five possibilities for their rate of production. Basically, a median forecast, and then good/really good/bad/really bad outcomes. This essentially produces 25 possibilities for each player’s production, and while it’s still overly simplistic, it passes the 80/20 rule.
At the bottom, I’ve included a table showing my assumptions for each player, which were basically on their individual histories and trajectories. Playing time for the bench was the residual of what the starters didn’t eat, same with starting pitchers, and then I assumed that starters would average 5.2 innings/game (including long relief type outings) and the bullpen 3.1 innings/game.
I then used random numbers to run 100 simulations for the 2018 Blue Jays roster in terms of WAR (31 random variables per simulation). Here’s what it looks like.
For context, I’ll note that (by definition), the average team WAR is 33.3, which means a .500 team should have around 33 WAR. But I’m not going to spend too much time on this chart, but it still omits quite a bit.
The biggest thing is free agent additions, which they certainly will do if they’re contending but is next to impossible to project. Again, I used some assumptions. With the payroll around $140-million as noted above, I assumed FA spending of $15 to 30-million, again chosen randomly. How much bang for their buck was also random, and the parameters were set so they added between 1 WAR and 7 WAR, with an average of just over 2 WAR, which I think is realistic given the market and likely spending.
Finally, production doesn’t directly translate into wins. There’s variation in how production (WAR) translates to runs, and then runs to wins. Again, I added a couple random variables to account for this. In extreme cases, it can add or subtract upwards of 10 wins (as happens from time to time), but is usually much smaller.
Accounting for all that, and running 100 simulations, this is range of projected outcomes I get for 2018 wins:
The blue bars are the likelihood of a specific number of wins, the red line the cumulative probability function. The Blue Jays project as a decent team, with a cluster of wins in the mid-80s, with tails basically extending down to 70 wins and up to 100 wins.
So what about contention? Winning the AL East usually starts at about 93 wins. I only get 9 outcomes of 93 wins or more, so I’d put the odds of winning the division in 2018 at 5-10% (it could and will likely take more than 93).
The wild card is more of a moving target. This year it took only 85 wins for the second wild card, and almost 40% of my scenarios have the Jays winning 85+ games. But again, that’s the lowest ever, and it will probably not be that low next year. If the wild card threshold is 89 wins, there’s only about 20% of scenarios where they get there.
So that’s a first pass, but I think reasonable look at the contention possibilities in 2018. That’s only part of the story, since those odds have to be balanced against the opportunity cost of doing something else. That’s what I’ll explore in my last piece.
Appendix: Individual player inputs
Note that “WAR” is short for WAR/100 PA, and “RP-” is run prevention indexed (basically true talent ERA- estimate)