Sunday, February 27, 2005

Comparing the Projections by Component

At Minor League Ball today, John Sickels started publishing some of his projections from a system he calls JSPS-2. He didn't mention any of the specifics, and I thought it would be fun to compare his numbers with ZiPS, Marcel, and PECOTA (I'm not the only one- Rob already has a comparison up at 6-4-2).

For this comparison, I wanted to look at the differences by component, rather than by counting totals, to see where the systems differ on each player's skillset.

Here's Dallas McPherson:
Dallas lwts/600 $BB $K $HR $H $XB $3B
JSPS-2 0.3 0.075 0.258 0.067 0.312 0.302 0.172
ZiPS 9.2 0.086 0.305 0.078 0.346 0.288 0.188
PECOTA 7.4 0.1 0.302 0.071 0.343 0.292 0.095
Marcel -3.9 0.087 0.216 0.051 0.304 0.244 0.091

Including Marcel isn't done to find the best projection; it's more of a baseline, since it uses very little data for players with as little major league playing time as McPherson and the reliability rating it assigns to its McPherson projection is among the lowest for any player.

ZiPS and PECOTA both project very high $H's for McPherson. Although it's certainly a skill McPherson has excelled at coming up, I'm not sure if that's a reasonable expectation. This is the same concern I voiced about Delwyn Young a week ago. Sickels' system also expects McPherson to put the ball into play more than the others do, projecting lower K and BB rates than ZiPS or PECOTA. PECOTA really likes McPherson's ability to draw walks while ZiPS bets high on both home runs and triples.

To take a look at how hard each system projects McPherson to hit the ball, I calculated the average run value of McPherson's batted balls for each projection and then multiplied by 400 to approximate a season's worth of batted balls (we'll call this measure r400b for short, okay?). ZiPS is highest at +47 runs, PECOTA says +42, and JSPS-2 says +30.

Here's Jeremy Reed:
Reed lwts/600 $BB $K $HR $H $XB $3B
JSPS-2 -3.9 0.09 0.125 0.018 0.314 0.243 0.212
ZiPS -2.3 0.099 0.104 0.023 0.302 0.209 0.172
PECOTA -3.3 0.086 0.109 0.026 0.303 0.228 0.095
Marcel 11.3 0.096 0.155 0.034 0.339 0.228 0.077

Again, Marcel is only for color- it assigns a very low reliability to its Reed projection. ZiPS and PECOTA are very similar, with the only substantial difference coming from walk rate. JSPS-2 slots in between the two in walk rate but projects a good deal more strikeouts. JSPS-2 also projects high $H and $XB rates, somewhat compensated for by a lower HR rate. Using the same r400b measure from above, there's virtually no spread here: ZiPS -3, Pecota -1, JSPS-2 +0.

Reed's hype rollercoaster has been a lot of fun to watch, as his amount of hype is directly proportional to his batting average on balls in play:

NCAA, 2002: .342
Low-A, 2002: .339
High-A, 2003: .341
AA, 2003: .413
AAA, 2004 (Charlotte): .281
AAA, 2004 (Tacoma): .313
MLB, 2004: .426

My unstudied thought is that the .302-.314 $H range in these Reed projections is probably about right. I'd like to see what the spread in $H under JSPS-2 is, as the similarity between it's $H projections for McPherson and Reed is equal parts encouraging and disconcerting. I'm not really sold that the Mariners would be better off with Reed playing in the majors this season; I don't know that it's better for his development, and I don't see how it benefits Seattle enough to offset the impact of starting his service clock earlier.

In any event, I'm waiting with baited breath to learn more about how John Sickels is doing his projections and what the rationale behind them is.

Comments:
Is it baited breath? Or [a]bated breath? I don't remember, and have seen it both ways.
 
Should have looked it up. I used to know this:

Usage Note: The word baited is sometimes incorrectly substituted for the etymologically correct but unfamiliar word bated (“abated; suspended”) in the expression bated breath. (http://dictionary.reference.com/search?q=baited)
 
Just to clarify... "$H" is batting average on balls in play, right? something like: (H-HR)/(PA-BB-SO-HR)? Rather than hits per plate appearance...
 
Correct.

$HBP = HBP/PA
$BB = BB/(PA - BB)
$K = K/(PA - HBP - BB)
$HR = HR/(PA - HBP - BB - K)
$H = (H - HR)/(PA - HBP - BB - K - HR)
$XB = (2B + 3B)/(H - HR(
$3B = 3B/(2B + 3B)

Oh, and it's typical to take SH and IBB out, but I think I forgot to for the Marcels here (the other projections don't include them anyway).
 
OK,
So each one of these stats tries to isolate a particular skill or give us some idea of how flukey the player's overall performance was. Who uses these stats? The Hardball Times dudes? I haven't yet been able to get into the articles I've seen on their site (except for your debut and Dodger Stadium articles, of course).
Can you recommend a good explanation of the merits of these stats?
thanks
 
These are stats that various people use for various reasons. Tangotiger is probably their most prominent supporter. Voros McCracken's DIPS work, IIRC, coined "$H."

The reason to use them is to measure a skill in the context of its occurrence. If a player has a .300 BA one season and a .270 BA the next, it's useful to see how often he's striking out, how often his fly balls are clearing the fence, and how often his balls in play go for hits. It could turn out that those 30 points come from a big drop off in one area or from smaller drop offs in all areas, so gauging a player's abilities is much easier this way.

Come to think of it, it's probably not used too widely (with the exception of BABIP)... maybe I'll write a THT article on this shortly.
 
These are some neat stats... its interesting to see how they isolate different segments of the players skill set. And I can see how it would be totally rad to look at the various batted ball types with this same sort of approach (like HR/airballs).

To get a sense of the shape of a batter's skill set I've been looking at the raw rates per PA of each of the basic offensive events (BB/PA, 1B/PA, 2B/PA, etc) plus OBP, isolated slugging, and BABIP. I'll start looking at some of the stats you've used and we'll see what I learn. Thanks.
 
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