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Last week Beyond the Box Score took a look at how good the Padres would be if all players hit their 90% PECOTA projection. The outcome was the Padres would be quite good and just clear the Dodgers 50% run differential for best in MLB with a +189.
The Rays have substantial advantage over the lowly Padres as they are projected at 84-78 record and +32 run differential compared to Padres projected 69-93 record and -118 run differential.
There isn’t a serious expectation where all players well overperform, but it gives you an idea of what kind of reasonable upside there is for players, and perhaps helps shed light on the high degree of fluctuation one finds within the course of a season.
What would the Rays look like if the whole team hit their 90% projection?
Rays Starting Position Players 90th Percentile Projection
Player | Pos | PA | BB | K | HR | SB | RBI | R | AVE | OBP | SLG | Tav | VORP | FRAA | WARP |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Player | Pos | PA | BB | K | HR | SB | RBI | R | AVE | OBP | SLG | Tav | VORP | FRAA | WARP |
Kevin Kiermaier | CF | 684 | 7.9% | 18.0% | 19 | 28 | 76 | 97 | 0.288 | 0.348 | 0.470 | 0.295 | 46.8 | 26 | 8.0 |
Evan Longoria | 3B | 684 | 9.1% | 20.9% | 29 | 3 | 101 | 87 | 0.285 | 0.353 | 0.495 | 0.303 | 45.4 | 4 | 5.4 |
Matt Duffy | SS | 633 | 7.3% | 17.1% | 15 | 14 | 75 | 74 | 0.303 | 0.357 | 0.446 | 0.293 | 45.4 | 1 | 5.0 |
Brad Miller | 1B | 635 | 9.8% | 20.6% | 24 | 12 | 87 | 82 | 0.278 | 0.350 | 0.478 | 0.297 | 31.9 | 7 | 4.2 |
Corey Dickerson | DH | 593 | 7.4% | 22.4% | 26 | 4 | 89 | 75 | 0.292 | 0.345 | 0.520 | 0.307 | 36.8 | 0 | 4.0 |
Steven Souza Jr. | RF | 549 | 10.7% | 29.3% | 23 | 16 | 73 | 79 | 0.272 | 0.357 | 0.470 | 0.298 | 33.4 | -1 | 3.5 |
Colby Rasmus | LF | 572 | 9.8% | 28.7% | 26 | 4 | 79 | 74 | 0.252 | 0.327 | 0.459 | 0.281 | 27.2 | -3 | 2.8 |
Nick Franklin | 2B | 591 | 11.2% | 24.0% | 19 | 15 | 67 | 83 | 0.262 | 0.346 | 0.436 | 0.281 | 29.5 | -5 | 2.7 |
Luke Maile | C | 383 | 8.4% | 21.7% | 9 | 0 | 41 | 40 | 0.260 | 0.328 | 0.398 | 0.266 | 15.6 | 6 | 2.4 |
The players get small increases in BB% and K% and extra base hits. The biggest increase in offensive production comes from BABIP and inflation of singles. The gains are pretty modest all around, but add up to pretty big gains.
Baseball Prospectus has Logan Morrison as a bench bat with Brad Miller as the starting first baseman and Nick Franklin picking up the majority of the playing time at second base.
Defensively the only real difference in projection comes from added playing time for key players. In single season samples this will have a massive effect: if Kevin Kiermaier puts up that offensive line and combines it with his 2015 defensive rate he would put up roughly +37.7 runs and add another win and a half to that projection.
TAv scales the league average offense to .260 and includes park factors. Last year Evan Longoria led the regulars with a .292 TAv to give some perspective.
These numbers aren’t accounting for any significant breakout, but they would require running hot as Longoria is the only one who has put up a season close to any of their projections. It wouldn’t take a career year from Longoria, but would from every other position player. Corey Dickerson came close with a .303 TAv in 2014.
The good news is everybody besides Longoria and Colby Rasmus is on the right side of 30 and could put up the best year of their career.
Rays Bench/AAA Position Players 90th Percentile Projections
Player | Pos | PA | BB | K | HR | SB | RBI | R | AVE | OBP | SLG | Tav | VORP | FRAA | WARP |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Player | Pos | PA | BB | K | HR | SB | RBI | R | AVE | OBP | SLG | Tav | VORP | FRAA | WARP |
Tim Beckham | 2B/SS/3B | 349 | 7.7% | 25.5% | 8 | 6 | 38 | 40 | 0.274 | 0.334 | 0.432 | 0.278 | 15.4 | -2 | 1.2 |
Mallex Smith | OF | 294 | 10.2% | 21.4% | 5 | 27 | 29 | 43 | 0.300 | 0.372 | 0.443 | 0.297 | 20.7 | -2 | 1.8 |
Curt Casali | C | 247 | 13.4% | 26.3% | 9 | 0 | 32 | 32 | 0.254 | 0.362 | 0.442 | 0.293 | 16.4 | -1 | 1.7 |
Wilson Ramos | C | 227 | 7.0% | 17.2% | 10 | 0 | 34 | 28 | 0.297 | 0.346 | 0.491 | 0.301 | 15.4 | 1 | 1.8 |
Logan Morrison | 1B | 229 | 10.9% | 17.0% | 9 | 3 | 31 | 30 | 0.277 | 0.363 | 0.469 | 0.299 | 11.6 | -1 | 1.1 |
Patrick Leonard | 1B/RF | 197 | 8.6% | 29.4% | 6 | 2 | 25 | 23 | 0.262 | 0.338 | 0.434 | 0.280 | 7.3 | -1 | 0.7 |
Daniel Robertson | 2B | 128 | 10.9% | 20.3% | 3 | 0 | 14 | 15 | 0.281 | 0.373 | 0.428 | 0.295 | 8.3 | 0 | 1.0 |
The biggest takeaway is the offensive upside of the catchers. Maile’s 90th percentile projection is just above average offensive at .266 TAv, but Curt Casali’s .293 TAv and Wilson Ramos’s .303 TAv would give the Rays a real offensive threat behind the plate.
The playing time projection for Ramos is one spot you could say is a place that the 90th percentile projection is light. Their playing time projection has Ramos receiving 15% of the starts at catcher, roughly 25 games, and 10% of the starts at designated hitter, roughly 16 games. If his health is there he’s going to catch much more. I personally have the under/over around 50 games behind the plate. If Ramos has his way and produces with the bat like his projection he would be in the line up for almost 100 games if he’s able to return in May or June.
Logan Morrison’s .299 TAv projection would earn him the starting 1B job over Nick Franklin’s .281 TAv projection unless Miller’s defense at 2B is significantly worse than the -5 projected for Franklin.
Casey Gillaspie (319 PA, .279/.379/.509 .310 TAv, 2.3 WARP), Willy Adames (315 PA, .268/.355/.443, .287 TAv, 2.2 WARP), and Jake Bauers (315 PA, .284/.364/.464, .293 TAv, 1.9 WARP) don’t receive playing time in the depth chart. Casey Gillaspie’s line would make him the best offensive player on the team.
Rays Starting Pitchers 90th Percentile Projections
Player | Pos | G | GS | IP | HR | K | BB | BABIP | WHIP | ERA | DRA | VORP | WARP |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Player | Pos | G | GS | IP | HR | K | BB | BABIP | WHIP | ERA | DRA | VORP | WARP |
Chris Archer | SP | 30 | 30 | 206 | 21 | 28.0% | 10.2% | 0.262 | 1.03 | 2.52 | 2.91 | 47.1 | 5.1 |
Jake Odorizzi | SP | 31 | 31 | 204 | 24 | 22.9% | 8.4% | 0.251 | 1.06 | 3.05 | 3.49 | 35.0 | 3.8 |
Matt Andriese | SP | 28 | 28 | 178.4 | 18 | 20.8% | 7.3% | 0.268 | 1.09 | 2.93 | 3.36 | 32.2 | 3.5 |
Blake Snell | SP | 23 | 23 | 140.4 | 12 | 25.3% | 13.0% | 0.270 | 1.18 | 2.87 | 3.29 | 25.5 | 2.8 |
Alex Cobb | SP | 23 | 23 | 143 | 13 | 20.6% | 8.9% | 0.260 | 1.10 | 3.00 | 3.38 | 24.3 | 2.6 |
Chase Whitley | SP | 20 | 5 | 57.7 | 6 | 19.6% | 7.9% | 0.247 | 1.07 | 3.17 | 3.56 | 6.7 | 0.7 |
Jacob Faria | SP | 38 | 8 | 88 | 9 | 20.6% | 11.5% | 0.243 | 1.14 | 3.40 | 3.75 | 10.2 | 1.1 |
Taylor Guerrieri | SP | 5 | 5 | 40 | 4 | 17.3% | 11.4% | 0.246 | 1.19 | 3.96 | 4.45 | 2.2 | 0.2 |
Jose De Leon | SP | 13 | 3 | 42.4 | 3 | 36.4% | 16.5% | 0.244 | 0.99 | 2.45 | 2.89 | 6.0 | 0.7 |
Jaime Schultz | SP | 3 | 3 | 28.4 | 3 | 24.7% | 14.8% | 0.264 | 1.24 | 3.24 | 3.67 | 2.5 | 0.3 |
The first thing that sticks out on the 90th percentile projections for pitchers are the inflated walk rates. The numbers look much better in bb/9 terms. Chris Archer’s 90% projection has him walking 64 in 206 innings or 2.8 bb/9 and his 50% projection has him walking 68 in 189 innings or 3.2 bb/9. The better projection comes from the BABIP dropping from .290 to .262 which greatly reduces the WHIP and batters faced per inning. Archer’s 10.2% would be far the worst he’s put up since his 29.1 inning cameo in 2012. The four years as a starter with over 100 innings he’s walked 7.2%, 8.8%, 7.6%, and 7.9% of batters faced.
There is still some health upside as they only expect Archer to make 30 starts and Jake Odorizzi to make 31. It’s wise to expect fewer starts, but when players stay healthy they’ll get more playing time which will inflate these numbers.
This rotation is quite good. In their 50% projection PECOTA already thinks they are quite good as they have five average or better starters with good depth. If everyone remains healthy, I would be surprised if anybody outside of Chase Whitley gets more starts than Jose De Leon, however. I expect De Leon to be added to the rotation as the first man up after the Rays get the extra year of control sometime in mid May.
Many of the prospects end up with significant time in the bullpen even if they throw more innings as a starter with this playing time split. Jaime Schultz only receives three starts, but is not projected for relief work. I expect he’s the most likely of the group to throw significant innings out of the bullpen.
Rays Bullpen 90th Percentile Projection
Player | Pos | G | GS | IP | HR | K | BB | BABIP | WHIP | ERA | DRA | VORP | WARP |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Player | Pos | G | GS | IP | HR | K | BB | BABIP | WHIP | ERA | DRA | VORP | WARP |
Alex Colome | RP | 55 | 0 | 75.4 | 6 | 25.3% | 9.4% | 0.249 | 0.99 | 2.29 | 2.73 | 13.2 | 1.4 |
Xavier Cedeno | RP | 55 | 0 | 77.2 | 5 | 24.5% | 9.6% | 0.250 | 1.00 | 2.33 | 2.78 | 12.9 | 1.4 |
Brad Boxberger | RP | 50 | 0 | 70.8 | 9 | 26.1% | 11.3% | 0.258 | 1.11 | 3.12 | 3.43 | 8.1 | 0.9 |
Tommy Hunter | RP | 25 | 0 | 42.3 | 4 | 16.0% | 7.3% | 0.250 | 1.09 | 3.58 | 3.52 | 3.8 | 0.4 |
Danny Farquhar | RP | 50 | 0 | 70.4 | 7 | 22.6% | 9.3% | 0.256 | 1.09 | 2.96 | 3.32 | 8.7 | 0.9 |
Shawn Tolleson | RP | 45 | 0 | 65.5 | 9 | 22.4% | 8.1% | 0.249 | 1.05 | 3.44 | 3.72 | 5.8 | 0.6 |
Ryne Stanek | RP | 25 | 0 | 42.8 | 4 | 20.0% | 11.4% | 0.242 | 1.14 | 3.36 | 3.62 | 3.5 | 0.4 |
Ryan Garton | RP | 25 | 0 | 43.2 | 4 | 19.6% | 9.2% | 0.252 | 1.13 | 3.38 | 3.67 | 3.4 | 0.4 |
Kevin Gadea | RP | 55 | 0 | 81 | 7 | 20.4% | 10.7% | 0.246 | 1.13 | 3.37 | 3.72 | 7.1 | 0.8 |
Austin Pruitt | RP | 10 | 0 | 22.8 | 2 | 20.2% | 8.0% | 0.254 | 1.03 | 2.70 | 3.13 | 1.9 | 0.2 |
Erasmo Ramirez | RP | 53 | 3 | 84.7 | 8 | 20.7% | 8.1% | 0.246 | 1.03 | 3.01 | 3.41 | 11.1 | 1.2 |
The bullpen is the spot where volume is key due to the expected volatility in performance. Every year a group will significantly under perform and some will over perform. The pitchers they’ve assembled have talent with many of them having very successful seasons in the recent past.
The key to success will be to avoid needing to use those who continually underperform, as we saw from Steve Geltz and Dana Eveland last season.
Normalized Projections
With these projections the Rays would receive 6,995 plate appearances and 1804.4 innings pitched. The league average last year was 6,153 plate appearances and 1,443 innings pitched.
Rays Normalized Position Player 90th Percentile Projection
PA | BB | K | HR | SB | RBI | R | AVE | OBP | SLG | Tav | VORP | FRAA | WARP |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
PA | BB | K | HR | SB | RBI | R | AVE | OBP | SLG | Tav | VORP | FRAA | WARP |
6153 | 9.2% | 22.4% | 211 | 118 | 784 | 793 | 0.278 | 0.348 | 0.463 | 0.292 | 358.1 | 26 | 41.6 |
Rays Normalized Pitchers 90th Percentile Projection
G | GS | IP | HR | K | BB | BABIP | WHIP | ERA | DRA | VORP | WARP |
---|---|---|---|---|---|---|---|---|---|---|---|
G | GS | IP | HR | K | BB | BABIP | WHIP | ERA | DRA | VORP | WARP |
529 | 162 | 1443 | 142 | 22.9% | 8.9% | 0.255 | 1.07 | 2.97 | 3.36 | 216.9 | 23.5 |
These projections normalize the total playing time, so you’re taking about 12% of the playing time equally from all the position players whether it’s Kevin Kiermaier or Tim Beckham. Health is a significantly factor as the playing time of the top guys would give even more upside.
This hypothetical dream scenario would project the team to score 793 runs, averaging 4.90 runs per game, while allowing 477 runs, or 2.94 runs per game. This would lead to an absurd +316 run differential. The Cubs put up +252 last year and the Dodgers are projected to have the largest run differential at +163.
The pythagorean win percentage of the team would be .734. That would translate to 119 wins with neutral luck.
The takeaway: even a team that looks like it doesn’t have the talent to compete could have the talent to compete if everything were to go right. Luckily the Rays don’t need everything to go right to be competitive.
Few teams are good enough if they only perform at their 50% projection. All teams rely on reasonably good health, a few key overperformances and a minimal number underperformances.