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How good would the Rays be if they hit their 90th percentile PECOTA projection?

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Very good! (But that is true of every team).

Tampa Bay Rays v Toronto Blue Jays Photo by Tom Szczerbowski/Getty Images

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.