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BtB Power Rankings: Week 24 -- Two weeks left!

By JinAZ

Toprank-091610_medium

Allrank-091610_medium

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

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

Under the Hood

The tables are all sortable when you click in the header.

Converting Runs to Wins

Team G RS eRS RA eRA W% pW% cW% SoS cW%s xtW LgQ TPI
ARI 146 615 614 729 695 0.397 0.420 0.442 0.527 0.469 65 0.482 0.451
ATL 147 692 685 576 572 0.565 0.584 0.583 0.505 0.588 92 0.482 0.570
BAL 146 557 592 725 736 0.397 0.379 0.400 0.508 0.408 64 0.518 0.425
BOS 146 716 723 646 658 0.562 0.549 0.545 0.496 0.541 91 0.518 0.558
CHW 145 663 646 607 628 0.545 0.541 0.513 0.476 0.490 88 0.518 0.508
CHC 146 607 613 689 657 0.445 0.441 0.468 0.491 0.459 72 0.482 0.441
CIN 146 691 699 605 628 0.568 0.562 0.550 0.483 0.533 92 0.482 0.515
CLE 145 577 593 698 699 0.407 0.412 0.424 0.495 0.420 66 0.518 0.437
COL 146 650 665 585 582 0.548 0.548 0.561 0.510 0.571 89 0.482 0.553
DET 146 659 681 666 659 0.493 0.495 0.515 0.485 0.500 80 0.518 0.518
FLA 145 671 665 649 644 0.503 0.515 0.515 0.519 0.534 82 0.482 0.516
HOU 146 561 550 654 633 0.479 0.430 0.436 0.507 0.443 77 0.482 0.425
KCR 145 583 600 742 755 0.414 0.389 0.393 0.499 0.392 67 0.518 0.409
LAD 146 627 621 631 613 0.493 0.497 0.506 0.514 0.520 80 0.482 0.502
LAA 145 629 598 655 684 0.490 0.482 0.438 0.489 0.427 78 0.518 0.445
MIL 145 678 712 755 702 0.462 0.448 0.506 0.494 0.501 76 0.482 0.483
MIN 145 710 690 574 586 0.600 0.598 0.576 0.482 0.559 97 0.518 0.576
NYY 146 782 758 607 644 0.603 0.618 0.577 0.489 0.566 97 0.518 0.584
NYM 146 608 612 598 635 0.500 0.508 0.483 0.515 0.498 81 0.482 0.480
OAK 145 597 601 576 586 0.497 0.517 0.511 0.483 0.494 81 0.518 0.512
PHI 147 673 656 580 615 0.585 0.569 0.530 0.515 0.545 94 0.482 0.527
PIT 145 505 534 791 743 0.331 0.301 0.349 0.510 0.359 54 0.482 0.342
SDP 145 678 647 568 561 0.566 0.581 0.566 0.506 0.572 92 0.482 0.555
SEA 146 477 498 640 640 0.377 0.371 0.389 0.494 0.384 61 0.518 0.401
SFG 146 628 623 545 596 0.562 0.564 0.520 0.514 0.534 90 0.482 0.516
STL 144 667 659 595 599 0.514 0.553 0.545 0.495 0.540 84 0.482 0.522
TBR 145 743 701 593 610 0.607 0.605 0.566 0.501 0.567 98 0.518 0.584
TEX 145 702 687 610 647 0.566 0.566 0.528 0.482 0.511 91 0.518 0.529
TOR 146 674 688 665 625 0.500 0.506 0.545 0.503 0.549 82 0.518 0.566
WSN 146 599 602 661 636 0.425 0.454 0.474 0.511 0.485 70 0.482 0.467

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 615 614 0.318 0.327 0.417 622 -8 729 695 4.89 4.67 4.54 704 9 0.308
ATL 692 685 0.332 0.341 0.404 685 -1 576 572 3.60 3.65 3.84 581 9 0.297
BAL 557 592 0.313 0.317 0.389 592 0 725 736 4.69 4.42 4.69 696 -40 0.308
BOS 716 723 0.340 0.338 0.452 730 -6 646 658 4.18 4.18 4.30 658 0 0.300
CHW 663 646 0.325 0.332 0.426 649 -3 607 628 4.06 3.67 4.13 600 -28 0.312
CHC 607 613 0.318 0.321 0.411 617 -4 689 657 4.38 4.07 4.23 636 -21 0.316
CIN 691 699 0.335 0.338 0.435 698 1 605 628 4.09 4.08 4.37 656 28 0.296
CLE 577 593 0.314 0.319 0.373 593 0 698 699 4.32 4.60 4.66 703 4 0.300
COL 650 665 0.328 0.340 0.432 660 6 585 582 4.07 3.61 3.95 584 1 0.308
DET 659 681 0.332 0.338 0.414 679 1 666 659 4.33 4.17 4.55 671 12 0.302
FLA 671 665 0.329 0.323 0.411 656 9 649 644 4.07 3.83 4.22 615 -29 0.311
HOU 561 550 0.304 0.304 0.363 546 4 654 633 4.02 3.74 4.11 606 -27 0.313
KCR 583 600 0.315 0.332 0.397 608 -8 742 755 5.01 4.91 4.62 722 -33 0.314
LAD 627 621 0.319 0.323 0.380 619 2 631 613 3.93 3.74 4.06 601 -12 0.297
LAA 629 598 0.314 0.314 0.395 611 -13 655 684 4.20 4.22 4.44 660 -23 0.304
MIL 678 712 0.338 0.333 0.427 710 1 755 702 4.75 4.23 4.31 650 -52 0.321
MIN 710 690 0.334 0.345 0.426 693 -3 574 586 3.77 3.84 4.08 610 25 0.304
NYY 782 758 0.347 0.350 0.438 757 1 607 644 3.91 4.11 4.28 644 0 0.284
NYM 608 612 0.317 0.315 0.379 602 9 598 635 3.78 3.98 4.29 640 5 0.307
OAK 597 601 0.315 0.322 0.372 589 12 576 586 3.60 4.25 4.24 642 56 0.280
PHI 673 656 0.327 0.330 0.411 656 0 580 615 3.78 4.06 3.93 625 11 0.299
PIT 505 534 0.300 0.300 0.367 542 -8 791 743 5.08 4.63 4.59 688 -55 0.320
SDP 678 647 0.325 0.320 0.377 643 4 568 561 3.38 3.94 3.76 596 35 0.292
SEA 477 498 0.293 0.298 0.338 503 -5 640 640 3.91 4.16 4.40 657 17 0.289
SFG 628 623 0.320 0.321 0.403 625 -2 545 596 3.50 3.84 4.21 629 33 0.293
STL 667 659 0.327 0.330 0.407 662 -3 595 599 3.62 4.08 4.01 619 20 0.300
TBR 743 701 0.336 0.336 0.408 687 14 593 610 3.84 4.05 4.21 636 27 0.286
TEX 702 687 0.333 0.340 0.423 681 6 610 647 3.96 4.27 4.39 667 20 0.291
TOR 674 688 0.333 0.311 0.453 691 -3 665 625 4.28 3.99 4.22 630 5 0.304
WSN 599 602 0.315 0.321 0.397 606 -4 661 636 4.13 4.06 4.31 639 3 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.

FAQ

Q. What are the power rankings?
A. The power rankings are an attempt to rank all teams in major league baseball based on their component statistics (hitting, baserunning, pitching, and fielding), after adjustments for park and strength of schedule (including league difficulty). Unlike most power rankings, these are not based on team wins or actual team runs allowed scored and allowed. It's an alternative way of creating power rankings than you will see in most places.

Q. This seems so complicated it might as well be a black box!
A. It's really not that hard to understand. We estimate runs scored based on hitting and baserunning stats. We estimate runs allowed based on fielding-independent pitching stats, and then add in a fielding stat. Then we adjust for park, plug it into the Pythagorean equation, and apply the strength of schedule adjustments. That gives us an estimate (an estimated winning percentage) of how well a team has performed this year, and that number is what we use to rank the teams. There are a lot of details (I try to break everything down in the descriptions below the tables), but really that's really all we're doing here.

Q. You've obviously got a broken model here because it's not ranking team X like I think they should be ranked.
A. There are errors around each estimate of team performance, and so it is entirely possible for the model to miss on a few teams while still being a meaningful way of ranking them teams. That said, we are always happy to hear specific suggestions as to how to improve them model overall: most of the improvements made over the past year are due to user feedback. ... of course, it's also possible that your perceptions are incorrect and the model is ranking a team in a fair and reasonable fashion.

Q. Shouldn't we just be looking at wins? Isn't that all the matters in the end?
A. It just depends what question you're trying to answer. If you just want to know who will make the playoffs, this isn't the ranking for you (though the extrapolated wins we calculate might be of interest). If you want a look at which teams have performed the best, regardless of whether those performances have resulted in wins and/or runs, you might find this ranking of interest. Also, even if you reject the overall rankings, you may find these rankings useful as a way to check out rankings of team offenses, pitching, fielding, and strength of schedule.

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