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

"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

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

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.