BtB Power Rankings: Week 21 -- Entering the stretch run

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"On Paper" Playoff Rankings:

American League: E=Rays, C=Twins, W=Rangers, WC=Yankees
National League: E=Braves, C=Cardinals, W=Padres, WC=Rockies*

This Week's Breakdown: The Cincinnati Reds

Sorry for the late update this week.  With the first week of classes, I'm suddenly behind on everything.

As a Reds fan, I want to point out that there is exactly one team at the top of their division in the real standings, with 90+ extrapolated wins, but ranked in the bottom half of these rankings.  That's my team, the Reds.  I love that I've been accused have having "some sort of weird bias," and yet my rankings consistently seem to beat up on my team as much as any other! :)

From the standpoint of hitting, the Reds expected runs scored are in almost exact agreement with actual runs scored.  This is good to see: to the surprise of everyone, the Reds' offense has been a real strength of the team.  They rank second in the NL in park-adjusted runs scored (to the Padres) and second in estimated runs scored and wOBA (to the Brewers).  This was a below-average offensive squad last year, so it's taken some pretty remarkable performances to get this kind of offense out of the team this year.  Votto has obviously been outstanding and is in the MVP discussion.  But we've also seen better than projected seasons from Rolen, Phillips, and the catcher tandem of Hernandez and Hanigan.  The bench has also been huge: Miguel Cairo and Chris Heisey, in particular, have hit far better than expected in their roles as super-subs.  The result has been a very capable offensive squad.  Given that almost everyone is playing over projection, you have to wonder if they can keep it up...but so far, across most of the season, they have.

Fielding-wise, this is also a very good team.  With the exceptions of Jonny Gomes and possibly Orlando Cabrera, everyone on this team can "go get it."  There's pretty good agreement across the board, too, among UZR (+37 runs), DRS (+22 runs), and a stat based on base runs and FIP (+34 runs).  Even the catching has been very good (+5 runs).  The result is what we're estimating as the second-best fielding team in the National League, behind only the Padres.

So, if there's an Achilles' heal to this team, it's the pitching staff.  Park-adjusted FIP (4.18) ranks only the Brewers, Pirates, and Diamondbacks as having poorer pitching performances thus far.  xFIP (4.44) ranks the Reds as also behind the Brewers, 3rd to last in the National League.  As a fan, this is surprising to me: we have 7 guys who seem like legitimately major league starters available for the rotation: Arroyo, Bailey, Cueto, Harang, Leake, Volquez, and Wood.  I can't remember a time where such depth existed in the rotation.  The truth is, though, that several of those pitchers seem to have pitched a bit over their heads so far this year.  Arroyo always seems to beat his peripherals every year, but his xFIP is currently a full run higher than his ERA.  Cueto is similar: 3.49 ERA vs 4.35 xFIP.  Leake's stat line also looked similar, until his shelling over the past two weeks led to a DL stint.  It is these kinds of disparities that are the reason that the model predicts that the Reds should have allowed 22 more runs than they actually have.

The good news for the Reds is that, while I think the pitching has gotten a bit lucky thus far, there is talent coming back that an can help.  Edinson Volquez has been wild as all heck in his first batch of starts, but if he can get his control issues ironed out during this (hopefully brief) stint in the bullpen, he can still become a top-flight starter for the playoff push.  Aaron Harang is also due back soon.  While Harang isn't the pitcher he used to be, he is someone who seemingly has gotten pretty unlucky: 5.02 ERA this season vs. a 4.51 FIP and a 4.33 xFIP.  This is a staff that may lack excellence at the top, but it is a deep rotation: I think almost everyone, #1 through #5, can be counted on to post somewhere around a 4.30 ERA over the rest of the season.  

The Reds already have a lot of wins in the bank; if the offense can keep it up, and the pitching doesn't completely implode, we very well could see Cincinnati baseball in October.  Last time I could say that, I was in high school.  And once you're in...who knows what will happen?

Under the Hood

Converting Runs to Wins

Team G RS eRS RA eRA W% pW% cW% SoS cW%s xtW LgQ TPI
ARI 129 548 545 658 619 0.395 0.414 0.440 0.524 0.464 66 0.482 0.446
ATL 128 602 597 495 496 0.570 0.590 0.584 0.503 0.587 93 0.482 0.570
BAL 129 476 512 666 668 0.357 0.348 0.378 0.511 0.388 59 0.518 0.405
BOS 129 634 648 568 583 0.574 0.552 0.551 0.502 0.552 92 0.518 0.570
CHW 128 588 566 517 541 0.547 0.560 0.521 0.479 0.500 87 0.518 0.518
CHC 129 527 540 614 583 0.419 0.429 0.464 0.490 0.454 69 0.482 0.436
CIN 128 616 615 534 556 0.578 0.567 0.548 0.479 0.527 92 0.482 0.509
CLE 128 527 533 635 618 0.406 0.413 0.430 0.503 0.433 67 0.518 0.451
COL 127 546 556 515 513 0.520 0.527 0.537 0.506 0.543 85 0.482 0.525
DET 129 569 591 587 589 0.496 0.486 0.501 0.492 0.493 80 0.518 0.510
FLA 127 581 571 545 547 0.512 0.529 0.520 0.513 0.533 83 0.482 0.515
HOU 128 489 479 598 567 0.453 0.408 0.423 0.505 0.427 72 0.482 0.410
KCR 128 508 518 660 670 0.422 0.379 0.381 0.503 0.384 67 0.518 0.401
LAD 129 580 570 564 544 0.519 0.513 0.521 0.509 0.530 84 0.482 0.512
LAA 129 580 545 602 613 0.488 0.482 0.445 0.501 0.446 78 0.518 0.463
MIL 128 610 637 687 634 0.469 0.443 0.502 0.492 0.495 77 0.482 0.477
MIN 129 627 628 526 526 0.574 0.582 0.582 0.488 0.570 93 0.518 0.587
NYY 128 690 661 529 565 0.609 0.624 0.575 0.492 0.567 97 0.518 0.584
NYM 128 528 538 512 555 0.500 0.513 0.486 0.514 0.500 81 0.482 0.482
OAK 127 520 522 497 510 0.496 0.521 0.511 0.489 0.500 81 0.518 0.517
PHI 128 572 561 510 535 0.555 0.553 0.522 0.511 0.533 89 0.482 0.515
PIT 128 434 462 688 662 0.336 0.298 0.338 0.506 0.343 55 0.482 0.327
SDP 127 623 583 484 487 0.598 0.616 0.584 0.498 0.582 96 0.482 0.564
SEA 128 430 447 568 561 0.391 0.376 0.399 0.501 0.400 64 0.518 0.417
SFG 129 573 570 501 542 0.550 0.561 0.523 0.508 0.531 88 0.482 0.513
STL 126 604 598 495 520 0.548 0.592 0.565 0.489 0.554 89 0.482 0.536
TBR 128 644 615 501 520 0.609 0.616 0.578 0.502 0.580 98 0.518 0.597
TEX 128 616 604 523 558 0.570 0.576 0.537 0.482 0.519 91 0.518 0.537
TOR 128 595 609 558 534 0.523 0.530 0.561 0.504 0.565 86 0.518 0.583
WSN 129 508 520 595 570 0.419 0.427 0.458 0.508 0.465 69 0.482 0.448

G=Games
RS = Actual Runs Scored, after a park adjustment
eRS = Estimated Runs Scored, after park adjustment (see table below)
RA = Actual Runs Allowed, after a park adjustment
eRA = Estimated Runs Allowed, after park adjustments (see table below)
W% = Actual Winning Percentage
pW% = PythagenPat Winning Percentage, based on actual runs scored and run allowed totals
cW% = Component Winning Percentage, using estimated runs scored and estimated runs allowed totals.  If you don't like the league adjustments or strength of schedule adjustments, click in the header and sort by this column to get an "unsullied" ranking.
SoS = Strength of Schedule.  This is an iterative weighted average of the component-based winning percentages of a team's opponents.  Described in this post.
cW%s = Schedule-adjusted Component Winning Percentage.  Calculated by applying SoS to cW% with the log5 method, as described in this post.
xTW = Extrapolated wins.  Based on current real wins to date, and extrapolated wins over the rest of the season.  Extrapolations are based on an average of cW% and cW%s, as justified in this post.
LgQ = League Quality.  The AL has superior talent to the NL (justification here and here, and modified most recently here.  A good introduction to the topic is this post).  The number shown is an estimated true talent level (in winning percentage) of the two leagues were they to be able to play one other for a large number of games.  It's based on the last two years of interleague, with a small adjustment toward 0.500 to account for the fact that the leagues do play one another and thus have already had a small effect on one another's performance.
TPI = Team Performance Index, a hypothetical winning % based on cW%s, after adjustment for league quality. Think of this as the W% we'd expect teams to have if they were all in one big league and were allowed to play 10,000 games vs. every team.

Team Offenses and Defenses

Team RS eRS wOBA OBP SLG HitRns EqBRR RA eRA ERA FIP* xFIP PitRns Field BABIP
ARI 548 545 0.320 0.327 0.419 553 -8 658 619 5.03 4.73 4.55 606 7 0.310
ATL 602 597 0.332 0.340 0.404 596 0 495 496 3.54 3.71 3.92 514 17 0.295
BAL 476 512 0.312 0.314 0.389 518 -6 666 668 4.89 4.49 4.76 631 -46 0.313
BOS 634 648 0.343 0.341 0.456 651 -3 568 583 4.15 4.23 4.35 587 7 0.297
CHW 588 566 0.324 0.332 0.428 569 -3 517 541 3.95 3.66 4.12 545 -14 0.305
CHC 527 540 0.318 0.322 0.410 544 -4 614 583 4.45 4.11 4.26 564 -18 0.316
CIN 616 615 0.336 0.337 0.436 614 1 534 556 4.13 4.18 4.44 593 30 0.295
CLE 527 533 0.317 0.322 0.380 532 1 635 618 4.51 4.67 4.73 617 3 0.305
COL 546 556 0.322 0.335 0.421 551 6 515 513 4.10 3.64 4.01 524 0 0.306
DET 569 591 0.330 0.339 0.415 590 0 587 589 4.35 4.23 4.57 608 5 0.302
FLA 581 571 0.326 0.322 0.405 562 9 545 547 3.92 3.77 4.16 544 -17 0.308
HOU 489 479 0.303 0.302 0.361 474 4 598 567 4.18 3.76 4.14 546 -33 0.319
KCR 508 518 0.313 0.329 0.394 526 -8 660 670 5.09 4.90 4.65 614 -33 0.316
LAD 580 570 0.325 0.329 0.388 568 2 564 544 3.95 3.70 4.05 539 -16 0.300
LAA 580 545 0.319 0.318 0.402 557 -13 602 613 4.36 4.33 4.47 590 -22 0.306
MIL 610 637 0.341 0.336 0.431 635 1 687 634 4.91 4.25 4.33 571 -58 0.328
MIN 627 628 0.339 0.348 0.433 631 -3 526 526 3.94 3.90 4.11 547 18 0.306
NYY 690 661 0.346 0.349 0.439 661 1 529 565 3.90 4.11 4.30 565 -2 0.286
NYM 528 538 0.318 0.314 0.379 526 12 512 555 3.69 3.93 4.26 567 2 0.307
OAK 520 522 0.314 0.320 0.373 513 9 497 510 3.53 4.14 4.18 544 42 0.281
PHI 572 561 0.323 0.326 0.407 561 0 510 535 3.84 4.04 3.95 527 10 0.299
PIT 434 462 0.299 0.301 0.364 467 -5 688 662 5.07 4.72 4.62 597 -50 0.317
SDP 623 583 0.328 0.324 0.379 579 4 484 487 3.30 3.94 3.82 507 40 0.289
SEA 430 447 0.296 0.302 0.343 451 -4 568 561 3.95 4.13 4.38 577 10 0.294
SFG 573 570 0.325 0.327 0.409 570 -1 501 542 3.64 3.93 4.29 579 25 0.299
STL 604 598 0.332 0.336 0.414 601 -3 495 520 3.42 4.07 4.02 528 23 0.296
TBR 644 615 0.336 0.337 0.402 601 14 501 520 3.66 3.95 4.15 552 30 0.285
TEX 616 604 0.333 0.339 0.423 598 6 523 558 3.88 4.25 4.35 580 26 0.289
TOR 595 609 0.335 0.314 0.453 611 -2 558 534 4.12 3.96 4.18 551 13 0.299
WSN 508 520 0.314 0.320 0.394 528 -8 595 570 4.18 4.11 4.37 577 1 0.309

RS = Actual Runs Scored
eRS = Estimated Runs Scored: HitRns + EqBRR
wOBA The Book's statistic, but park adjusted, and using data from both HitRns and EqBRR
OBP = On Base Percentage (Times on Base / Plate Appearances)
SLG = Slugging Percentage (Total Bases / At Bats)
HitRns = Base Runs-estimated runs scored, ignoring all base running, using the equation in this post.
EqBRR = Dan Fox's composite baserunning statistics from Baseball Prospectus, minus stolen bases since they are included in wRC.

RA = Actual Runs Allowed, after park adjustment
eRA = Estimated Runs Allowed: PitRns - Field
ERA = Straight-up Earned Run Average
FIP* = Fielding-Independent Runs, based strictly on K-, BB-, and HR-rates.  HR/FB rates are park adjusted using these park factors.
xFIP = Expected Fielding-Independent Runs from FanGraphs.  Like FIP, but with HR/Outfield Fly Ball rates regressed completely to league average.  xFIP is as predictive as any other DIPS-like stat.
PitRns = Pitching Runs Allowed, the expected runs allowed based on the average of FIP and xFIP.  Described in this post.
Field = Described in this post.  It is essentially an average of team UZR, DRS (minus rSB since I calculate catcher fielding separately), and BsRFld.  BsRFld is just difference between FIP-based runs allowed and park-adjusted Base Runs, and is a less direct approach of measuring fielding.  The fielding number also includes a catcher fielding statistic, based on SB's, CS's, WP's, PB's, E's, and this year catcher interference.  The catching methods are essentially those described here.  But I'm using B-Ref data this year, and so there are slight tweaks to the methodology, generally in ways that should lead to greater accuracy.  If you want to know, feel free to ask!
BABIP = Batting Average on Balls In Play.  Fluctuates at the team level with fielding, although park effects and chance events can have effects as well.

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