St Claire vs McCatty - Some Data

So, on 2 June 2009 Randy St Claire was fired and replaced by Steve McCatty. There's been some favourable comment about the new regime — allegedly pitching has improved. The trouble with making direct comparisons of 'St Claire 2009' with 'McCatty in the Big Leagues' is that McCatty is working with significantly different personnel over a shorter period of time. So, before it's too late, I decided to take a look while the names they both had to deal with were much the same.

From 2nd June to today is about the same length of time as from 20th May to 1st June. (In fact, McCatty has had an extra game in that time.) By 20th May, Daniel Cabrera had been removed from the rotation, and Scott Olsen was on the disabled list. The youngsters Stammen and Detwiler entered the rotation and have remained since. The bullpen hasn't change dramatically, with Kip Wells going on the disabled list. So 20th May to 13th June involves much the same personnel.

First, let's use the old Big Bad Baseball Annual Quality Matrix (QMAX) to analyse the starters. (I like QMAX, because it actually uses individual starts, as opposed to lumping everything together, and offers a more nuanced picture than the Quality Start.)

Coach       Success (Elite 
            Square   Square)   Hit Hard      --- 
St Claire      3       0           5          2
McCatty        6       2           1          2

The Elite Square is a subset of the Success Square, so don't add those together. In this case, it's a solid win for McCatty. This makes sense, after a fashion, because St Claire built his reputation working with veteran pitchers, and suddenly there weren't any in the Nationals' rotation. McCatty's more 'instinctual' approach might work better than St Claire's 'technical' methods with younger pitchers still learning the broad principles of pitching.

For relief, I took two elements. The Win Expectancy (WE) situation when the relief pitcher entered the game, and the net plus/minus after comparing the ideal result (no change to the leader's advantage in runs if the change occurs at the start of an inning; or, if the change is made mid-inning, all batters faced make outs) with the actual result.

Coach      Average WE             WE       WE+
           at entry              effect
St Claire      .254             -1.378     -1.79     
McCatty        .330             -3.230     -2.49

The WE+ is an attempt to translate the win expectancy effect to a common standard. The problem with the raw numbers is that the better performance of the starters under McCatty mean there is more win expectancy to lose than there was under St Claire. (Think of it as a reliever having an 8 per cent better chance of entering a close game under McCatty; there's just more win expectancy to lose to begin with.)

Basically, the bullpen under McCatty is having an even more difficult time than it was under St Claire. Some of that may be down to the fielding. If you take away the 12th June game, lost in part by Nick Johnson misplaying a foul pop-up, the WE+ number comes down to -1.88. Maybe the difference isn't so big.

On balance, from this evidence, the improvement in the rotation probably justifies the switch from St Claire to McCatty. I'd go so far as to say that a pitching coach really must stand or fall on how effective the rotation is.

STOP PRESS - Acta Rumours

Oleanders and Morning Glories tells of a Ken Rosenthal (RoboThal to the Baseball Primer cognoscenti) report that the Sword of Damocles has dropped lower over Manny Acta's head.

The Washington Times' blog has this quote from Kasten: "And yet, we have a record of 16-43, which is, to me, inexplicable."

Really? What would be explicable with this roster, with its inadequate bullpen and atrocious outfield defence? 30-24? 22-37? 17-42?

I really hate it when top-level management shove the middle-level management under the wheels of a passing bus. We all know Bowden was at the root of the problem, the Bowden that was kept on far too long by ownership. Mr Kasten, maybe you didn't want him, but your associates ensured that he stayed to cause even more damage. Don't blame Mr Acta for failings at your level of the operation.

Nationals' Bullpen Hero of the Day #1

I like to be fair, and given the recent performance of the bullpen, it's about time I started highlighting their successes as well as their failures. The first award is made for the 11th June game against the Reds.

Reliever            Effect on 
                    Win Expectancy
Beimel                   0.175
Tavárez                  0.121

I considered awarding a Goat for yesterday's game, but I decided that the real failing lay with Nick Johnson's foul pop-up error. Sorry, Nick; Ron Villone will be heaving a sigh of relief — there's a pun to end the entry with.

Nationals' Bullpen Goat of the Day #14

I had this post all ready to go yesterday, but then the bullpen came through in yesterday's game I put it on hold. Being the sort of fellow who likes to accentuate the positive, I was going to hide Goat#14 (for the game of 10 June) within a post celebrating yesterday's heroes of the bullpen, but I haven't got a moment to do the analysis just now.

Reliever            Effect on 
                    Win Expectancy
Bergmann                -0.643
Villone                 -0.508
Hanrahan                 0.034
Beimel                   0.021
MacDougal                0.343

I really thought Villone was going to get it.

Defensive Breakthroughs?

It really started here. But that was a blogpost about this. And it was soon followed by something we perhaps didn't know we needed.

While there are many fine new fielding metrics around using PBP (play-by-play data), to me the really important breakthrough is going to come when we get a reliable metric for fielding in the pre-PBP days. That's going to involve some kind of assumption about a piece of information we'll never have for most of baseball history - how many hits was a fielder responsible for.

I suspect it's quite important to start from the team level when calculating the value of fielding. (See Clay Davenport's article in the 2002 Baseball Prospectus for an example.) You then have a choice - either you can calculate the total of opportunities from the assumption that all balls will fall for hits, and thus the caught balls represent runs saved. Or you can look at fielding in terms of runs allowed, by thinking in terms of the number of mistakes. I suspect for a decent 'all of baseball history' metric, we need to think more along the lines of the latter. We need to establish 'expected runs' baseline against which to measure fielding.

I also came to a key realization after reading all this. Looking at the statistics when I was developing my Defensive Winning Percentage, I was surprised at how narrow the band is of fielding effectiveness. This is, I think, a reflection that there's both a floor and a ceiling to the effectiveness of fielders. Some of the credit is all down to the pitcher. All home runs except those inside-the-park, for example, are the pitcher's fault. Only some of the runs scored by those who walk, however, are the pitcher's fault. So there's some fielding input on that. But a walk and home run equals all the pitcher's fault.

Probably, the Fielding Experts will say I'm not being very original here. But I hadn't thought of it that way before.

Draft Day & Unfinished Business

Today is the amateur baseball draft. In the olden days, one didn't know much about it until the next day's papers. Then, mlb.com started offering the audio of the conference call. I loved that. Great soundtrack for a June afternoon. Now it's one big party. Can't we go back to the olden days?

I also owe this blog some links to very interesting work related to defensive statistics that appeared on the Web recently. It's made me look back over my Defensive Winning Percentage method. I'll get round to it, I promise.

Nationals' Bullpen Goats of the Day #s 10, 11, 12, 13

I've been a bit remiss this week, not awarding Goats of the Day. In part this is because the bullpen has generally improved, and it seems unfair to fault them for problems elsewhere on the team. However, here's the roundup for the eight games prior to Sunday's.

29 May - No award, batting failure.

30 May vs Phillies

Reliever            Effect on 
                    Win Expectancy
Villone                 -0.349
MacDougal               -0.062
Tavárez                 -0.009
Colome                   0.008
Wells                    0.012
Bergmann                 0.024

31 May vs Phillies

Reliever            Effect on 
                    Win Expectancy
Beimel                  -0.191
Hanrahan                 0.017
Bergmann                 0.034

2 June - Nats Win!

4 June vs Giants (game 1)

Reliever            Effect on 
                    Win Expectancy
Hanrahan                 -0.187
Beimel                   -0.022
MacDougal                 0.059
Villone                   0.062

4 June vs Giants (game 2) - rain stopped play in 6th. No bullpen usage.

5 June vs Mets

Reliever            Effect on 
                    Win Expectancy
Hanrahan                 -0.794
Villone                  -0.114
Bergmann                 -0.078
Beimel                    0.114
MacDougal                 0.153

6 June - Nats Win!

So four more names in the book. Time I ran some standings, maybe.