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BtB Power Rankings: Week 22 -- We're into September

Toprank-090410_medium

Look! A National League team in the top 5!

Allrank-090410_medium

"On Paper" Playoff Leaders (*=new this week)

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

Under the Hood

Converting Runs to Wins

Click in the header to sort the tables

Team G RS eRS RA eRA W% pW% cW% SoS cW%s xtW LgQ TPI
ARI 135 587 579 680 645 0.415 0.430 0.449 0.524 0.473 68 0.482 0.456
ATL 135 646 637 520 526 0.578 0.600 0.588 0.505 0.593 94 0.482 0.575
BAL 135 498 534 687 692 0.363 0.354 0.381 0.510 0.390 59 0.518 0.407
BOS 134 655 670 590 601 0.567 0.549 0.552 0.499 0.550 91 0.518 0.568
CHW 133 617 599 543 569 0.549 0.560 0.524 0.477 0.501 88 0.518 0.519
CHC 135 566 574 647 614 0.430 0.438 0.468 0.490 0.458 71 0.482 0.440
CIN 134 645 648 553 581 0.582 0.572 0.551 0.481 0.532 93 0.482 0.514
CLE 135 552 561 668 661 0.400 0.411 0.423 0.500 0.423 65 0.518 0.441
COL 134 579 594 544 541 0.522 0.529 0.543 0.507 0.550 85 0.482 0.532
DET 135 606 628 616 611 0.496 0.492 0.513 0.491 0.504 81 0.518 0.522
FLA 133 616 603 585 583 0.511 0.525 0.516 0.516 0.532 83 0.482 0.514
HOU 134 508 500 610 585 0.463 0.417 0.428 0.505 0.433 74 0.482 0.416
KCR 134 534 547 690 706 0.418 0.381 0.381 0.501 0.382 67 0.518 0.399
LAD 135 601 596 595 570 0.511 0.505 0.521 0.511 0.532 83 0.482 0.514
LAA 135 590 559 624 636 0.481 0.473 0.440 0.496 0.436 77 0.518 0.454
MIL 134 635 661 718 664 0.463 0.441 0.498 0.492 0.490 76 0.482 0.472
MIN 135 648 644 545 549 0.578 0.580 0.574 0.486 0.560 93 0.518 0.578
NYY 135 740 712 554 596 0.630 0.636 0.584 0.491 0.575 101 0.518 0.593
NYM 135 550 567 549 585 0.489 0.501 0.486 0.517 0.503 79 0.482 0.486
OAK 134 553 554 529 536 0.493 0.521 0.515 0.488 0.502 80 0.518 0.520
PHI 135 605 587 529 561 0.570 0.561 0.521 0.514 0.535 91 0.482 0.517
PIT 134 473 497 735 695 0.336 0.304 0.348 0.505 0.353 55 0.482 0.337
SDP 133 636 601 518 512 0.571 0.595 0.574 0.500 0.574 93 0.482 0.557
SEA 135 444 459 587 586 0.393 0.378 0.392 0.498 0.390 64 0.518 0.408
SFG 135 595 586 528 574 0.548 0.555 0.510 0.511 0.521 88 0.482 0.503
STL 132 616 611 527 549 0.530 0.573 0.550 0.490 0.540 86 0.482 0.522
TBR 134 670 637 523 548 0.619 0.614 0.570 0.503 0.573 99 0.518 0.590
TEX 134 636 628 552 591 0.560 0.566 0.528 0.480 0.508 90 0.518 0.526
TOR 134 623 637 592 557 0.515 0.524 0.563 0.504 0.567 85 0.518 0.585
WSN 135 550 559 630 593 0.422 0.437 0.473 0.509 0.482 70 0.482 0.464

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 587 579 0.321 0.329 0.422 587 -8 680 645 4.96 4.66 4.54 651 5 0.311
ATL 646 637 0.334 0.342 0.408 636 0 520 526 3.54 3.66 3.90 537 11 0.295
BAL 498 534 0.311 0.313 0.387 538 -4 687 692 4.80 4.45 4.74 648 -44 0.312
BOS 655 670 0.341 0.339 0.453 673 -3 590 601 4.15 4.21 4.30 607 6 0.298
CHW 617 599 0.326 0.334 0.431 602 -3 543 569 3.98 3.69 4.12 551 -18 0.307
CHC 566 574 0.320 0.323 0.415 579 -5 647 614 4.45 4.11 4.25 591 -23 0.318
CIN 645 648 0.336 0.339 0.438 647 1 553 581 4.08 4.14 4.42 609 29 0.294
CLE 552 561 0.317 0.321 0.378 560 1 668 661 4.51 4.70 4.74 661 0 0.305
COL 579 594 0.324 0.335 0.425 589 6 544 541 4.11 3.66 4.01 542 1 0.306
DET 606 628 0.332 0.340 0.417 629 -1 616 611 4.32 4.18 4.55 621 10 0.302
FLA 616 603 0.326 0.323 0.407 594 9 585 583 3.98 3.81 4.17 559 -24 0.309
HOU 508 500 0.303 0.303 0.360 496 4 610 585 4.08 3.74 4.15 558 -28 0.316
KCR 534 547 0.314 0.329 0.394 555 -8 690 706 5.06 4.90 4.63 669 -38 0.317
LAD 601 596 0.325 0.329 0.387 592 4 595 570 3.99 3.76 4.08 559 -10 0.298
LAA 590 559 0.316 0.316 0.398 572 -13 624 636 4.34 4.28 4.45 613 -23 0.307
MIL 635 661 0.339 0.335 0.428 660 1 718 664 4.91 4.31 4.34 608 -56 0.326
MIN 648 644 0.335 0.345 0.427 647 -3 545 549 3.85 3.90 4.11 573 24 0.304
NYY 740 712 0.350 0.352 0.446 711 1 554 596 3.87 4.11 4.29 594 -1 0.285
NYM 550 567 0.318 0.313 0.378 554 14 549 585 3.73 3.95 4.26 587 2 0.309
OAK 553 554 0.315 0.322 0.374 545 9 529 536 3.55 4.19 4.20 586 50 0.280
PHI 605 587 0.323 0.325 0.406 587 0 529 561 3.76 4.03 3.96 574 14 0.298
PIT 473 497 0.302 0.303 0.370 504 -6 735 695 5.19 4.69 4.58 637 -58 0.321
SDP 636 601 0.326 0.322 0.378 599 2 518 512 3.37 3.98 3.81 553 41 0.288
SEA 444 459 0.293 0.300 0.340 467 -8 587 586 3.88 4.14 4.38 604 18 0.290
SFG 595 586 0.323 0.325 0.404 585 0 528 574 3.66 3.94 4.30 594 21 0.298
STL 616 611 0.328 0.333 0.409 614 -3 527 549 3.50 4.09 4.05 571 22 0.297
TBR 670 637 0.334 0.336 0.402 625 12 523 548 3.66 3.94 4.16 577 29 0.284
TEX 636 628 0.332 0.337 0.421 622 6 552 591 3.89 4.25 4.36 612 21 0.290
TOR 623 637 0.334 0.313 0.453 639 -2 592 557 4.15 3.95 4.16 571 14 0.300
WSN 550 559 0.316 0.322 0.399 563 -4 630 593 4.26 4.12 4.35 597 4 0.310

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.