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SABR 201: Linear Weights by the 24 base/out states, 1999-2002 (June 10, 2003)

Posted 9:06 a.m., June 11, 2003 (#2) - Andrew Edwards
  Fascinating stuff. I could spend all day reading through and finding explanations for all the times when the empirical values deviate from theoretical values.

I think it's those deviations that tell us the most about the game.

Great stuff, Tango.

SABR 201: Linear Weights by the 24 base/out states, 1999-2002 (June 10, 2003)

Posted 9:11 a.m., June 11, 2003 (#3) - Andrew Edwards
  For instance, with the bases empty, a walk is worth just a shade more than a single.

My explanation is that this is because pitchers who give up walks are just slightly more likely to be scored on than pitchers who give up hits. Perhaps also that batters who take walks are slightly more likely to be higher in the order, and therefore followed by better hitters.

Like I said, I could do this all day.

It would be interesting, by the way, to control for lineup slot of hitter. Might help reduce some of the noise, especially around the relative value of IBB. I'm not sure if the sample size is there, though.

SABR 201: Linear Weights by the 24 base/out states, 1999-2002 (June 10, 2003)

Posted 3:10 p.m., June 11, 2003 (#6) - Andrew Edwards
  Sample size, I expected, would be a restriction. I hadn't thought of the selective sampling issue (I hadn't thought much about it at all).

I guess you're probably right about sifting through nine tables like that. I'd love it though. I'd especially love it if I could make a 3-dimensional pivot table in SPSS out of the nine. *drool* ...pivot tables... *drool*

Jim:

Tango's done Win Expectancy tables too, if you search around this site. The general consensus, in strategy terms, is that you play to maximize total runs in the early parts of the game, since the situation is more variable then. As the possible number of situations diminishes in the later innings, then it becomes more manageable and more sensible to play simply for the win.

SABR 201: Linear Weights by the 24 base/out states, 1999-2002 (June 10, 2003)

Posted 3:11 p.m., June 11, 2003 (#7) - Andrew Edwards
  Tango, just to clarify, I'm not actually asking you to do it. Far be it for me to assign you hours of work. You're already doing way too much.

Ballpark Effects - By Type of Player (June 26, 2003)

Posted 7:21 a.m., June 26, 2003 (#1) - Andrew Edwards
  I liked this too - it seems to make sense that different parks have stronger effects on different kinds of hitters. I wonder whether runs created is the right measure, though....

More generally, I'd expect, for instance, huge domes with fast turf to help speedy groundball hitters (Ichiro!) and hurt the Mo Vaughns of the world, for instance.

And we've already been talking about types of hitters who flourish in Coors.

The best part is that this data is obviously and immediately applicable to understanding how teams should be built. Wanna bet Keith Law already knows the answers for SkyDome?

Cycles (June 27, 2003)

Posted 12:38 p.m., June 27, 2003 (#2) - Andrew Edwards
  Another explanation for why the actual rate of cycles exceeds the expected rate is that players might start performing to the cycle.

That is, if you're just missing a double, maybe you try to stretch that single. If you're just missing a home run, maybe you swing a little more for the fences. If you're just missing a single (and we've all seen this), maybe you pull up a bit on a borderline double.

If I was better at manipulating play-by-play data, I think I could check this. I should learn ASS sometime.

Overall, I'd say this is probably just part of why they beat expectations. I think 'bad pitchers' are the best explanation. I'm more likely to double off a guy who's already allowed me a single, triple, and homer than I am off a guy who I haven't hit all day.

Ruane - Cost of outs, and speed (July 9, 2003)

Posted 5:07 p.m., July 9, 2003 (#1) - Andrew Edwards
  Awesome.

Aaron's Baseball Blog - David Wells (July 10, 2003)

Posted 5:57 p.m., July 11, 2003 (#1) - Andrew Edwards
  What's amazing is that Aaron does this for free, in his spare time. I can't imagine why he hasn't been hired somewhere.

Free Aaron Gleeman!

DIPS year-to-year correlations, 1972-1992 (August 5, 2003)

Posted 4:23 p.m., August 5, 2003 (#9) - Andrew Edwards
  Hmmm...

Allow me that singles tend to be given up by ground ball pitchers, XBH by flyball pitchers. Does this suggest that GB pitchers have more control over BABIP? Or that infield defence is more stable than outfield defence?

Just tossing hypotheses.

DIPS year-to-year correlations, 1972-1992 (August 5, 2003)

Posted 4:27 p.m., August 5, 2003 (#10) - Andrew Edwards
  Post #9 was written before I read posts 5-8.

Stadium could account for some of this, but I suspect that there's also a degree to which outfielder defensive performance tends to decay more abruptly than infielder performance.

Alternately, this could mean that outfielder defence has more influence than infielder defence, which is couterintuitive, at least to me.

Psychological Impact of Losing an Easy Game (August 9, 2003)

Posted 2:25 a.m., August 10, 2003 (#1) - Andrew Edwards
  Why not test it? Look at all the games in which a team has blown an 'easy' lead, and look at the percentage of the time they win the next game, as compared to the expected percentage. Expected percentage could just be that year's winning percentage, or something.

Solving DIPS (August 20, 2003)

Posted 4:29 p.m., August 20, 2003 (#5) - Andrew Edwards
  I belong to the class of person Jim R. described, and I too find these unbelieveably useful.

Is there a way someone like us could help?

Road Warriors (September 4, 2003)

Posted 3:08 p.m., September 4, 2003 (#2) - Andrew Edwards
  The near total absence of year-to-year consistency in Bob's numbers suggests to me that there are serious sample size concerns.

That's not to say that the insight isn't relevant - some teams could have a serious playoff problem driven by a poor road record - but we'd need to aggregate over a few years I think before we started to be able to really make any strong statements.

By The Numbers - Sept 7 (September 8, 2003)

Posted 10:09 a.m., September 9, 2003 (#4) - Andrew Edwards
  Heh. I expected the skin-tone thing to pretty completely rebut Dusty.

With that sample size, it neither rebuts nor confirms Dusty's hypothesis. But if I was going to present evidence that suggested any sort of difference between "races", I'd be damn sure my methodology was airtight. Doing otherwise borders on the irresponsible.

Incidentally, if the effect seen there is real, I'd say it was much more likely attributable to players who were raised in hot climates performing better in hot conditions than to anything about genetic traits.

Fanhome's Dackle: World Series Odds (September 18, 2003)

Posted 10:51 a.m., September 18, 2003 (#4) - Andrew Edwards
  Umm, I think there's a mistake here.

It says the Red Sox and the Cubs both have non-zero chances of winning the World Series.

Shouldn't insane mystical curses be folded in here somehow?

TheStar.com - Analyze this: NBA '04 (September 19, 2003)

Posted 10:42 a.m., September 19, 2003 (#2) - Andrew Edwards
  Some has got to do this for hockey too. I'm not enough of a fan to do it myself, but it's so obvious to me that goaltenders are seriously misevaluated that I go crazy everytime I hear golaie stats discussed.

Most pitches / game in a season (September 22, 2003)

Posted 4:52 p.m., September 22, 2003 (#2) - Andrew Edwards
  Same list, sorted by pitches (hope this formatting works).

ryanno01 1977 142
gibsobo01 1969 137
gibsobo01 1970 136
ryanno01 1974 135
ryanno01 1973 133
ryanno01 1978 133
wittbo01 1988 133
niggejo01 1944 132
vanceda01 1924 131
vanceda01 1925 131
fellebo01 1941 130
vandejo01 1943 130
perryga01 1973 130
newsobo01 1938 129
whiteea01 1935 128
gibsobo01 1968 128
langsma01 1987 128
kenneve01 1936 127
lyonste01 1938 127
fellebo01 1938 127
blackew01 1947 127
mcdowsa01 1970 127
lolicmi01 1971 127
perryga01 1974 127
ryanno01 1976 127
richajr01 1978 127
coopewi01 1921 126
grimebu01 1923 126
grovele01 1937 126
carltst01 1972 126
singebi01 1973 126
tananfr01 1976 126
blylebe01 1976 126
niekrph01 1977 126
norrimi01 1980 126
pfeffje01 1919 125
grimebu01 1924 125
uhlege01 1926 125
gomezle01 1937 125
leonadu02 1940 125
leeth01 1941 125
whiteea01 1931 124
chandsp01 1942 124
marchph01 1947 124
raschvi01 1950 124
hudsosi01 1950 124
piercbi02 1956 124
malonji01 1965 124
stonebi01 1971 124
gibsobo01 1972 124
perryga01 1975 124
sotoma01 1983 124
valenfe01 1984 124
valenfe01 1987 124
ruffire01 1936 123
ferrewe01 1937 123
fellebo01 1939 123
chaseke01 1940 123
fellebo01 1946 123
marreco01 1952 123
pascuca02 1963 123
gibsobo01 1965 123
perryga01 1969 123
ryanno01 1975 123
carltst01 1980 123
carltst01 1981 123
carltst01 1983 123
valenfe01 1986 123
johnsra05 1994 123
johnsra05 1999 123
ruethdu01 1923 122
bridgto01 1935 122
whitejo02 1935 122
ruffire01 1937 122
ruffire01 1938 122
grovele01 1939 122
ruffire01 1939 122
rignejo01 1941 122
newhoha01 1946 122
turlebo01 1954 122
maricju01 1968 122
lolicmi01 1969 122
carltst01 1974 122
mccatst01 1981 122
morrija02 1987 122
clemero02 1987 122
ryanno01 1989 122
grimebu01 1921 121
ringji01 1923 121
lyonste01 1941 121
sheasp01 1952 121
carltst01 1970 121
seaveto01 1970 121
gibsobo01 1971 121
jenkife01 1971 121
ryanno01 1972 121
blylebe01 1973 121
tiantlu01 1974 121
palmeji01 1977 121
richajr01 1979 121
carltst01 1982 121
morrija02 1983 121
langsma01 1988 121
johnsra05 1992 121
coneda01 1995 121
allenjo02 1933 120
lyonste01 1935 120
ferrewe01 1936 120
whiteea01 1936 120
lyonste01 1940 120
waltebu01 1940 120
smithed04 1941 120
waltebu01 1941 120
lyonste01 1942 120
lopated01 1947 120
chesnbo01 1948 120
colemjo04 1949 120
spahnwa01 1951 120
shantbo01 1952 120
scorehe01 1955 120
schwado01 1961 120
maricju01 1964 120
carltst01 1969 120
bluevi01 1971 120
perryga01 1972 120
blylebe01 1975 120
richajr01 1976 120
hunteca01 1976 120
langfri01 1981 120
vuckope01 1982 120
valenfe01 1985 120
martipe02 1997 120
clemero02 1997 120
schilcu01 1998 120

Pyschological Impact of a Devastating Outcome (September 27, 2003)

Posted 11:59 p.m., September 30, 2003 (#5) - Andrew Edwards
  Possible scenarios (just thinking through what would make me frustrated):

- Walks in a run
- Makes an error himself
- Has an error made behind him
- Walks a batter after an 0-2 count
- Is warned by an ump for brushback, etc.
- Balks
- Gives up a tying run
- Throws a wild pitch
- Has a passed ball

Of course, you've already thought of this, but just to remind you - these scenarios have biases themselves. For instance, a balk requires a runner on, so a poor pitcher will have more chances to balk than a good pitcher. Ideally, comparisons would be made within a pitcher: i.e. How does David Wells normslly do with a runner on 2nd versus how does he do wit ha runner he's balked to 2nd, versus a runner who's gone to 2nd on a passed ball, etc.

Sample size issues abound, of course, but if we do that within pitcher comparison across a few hundred or a few thousand pitchers, we should be able to get something useful.

Injury-prone players (October 14, 2003)

Posted 12:47 p.m., October 17, 2003 (#21) - Andrew Edwards
  Just a thought on sample design. There are two questions bundled together:

1) Is past DL time a predictor of future DL time?

Steve's study does a good job of addressing that, and some of the discussion since could refine it further. Overall, this is an important insight - there are plenty of teams who seem to behave as though DL time were random, and they've obviously got something to learn.

2) Are past injuries a predictor of future injuries?

I think it's important to distinguish this from the first question.

Two times on the DL could both be caused by the same injury. For instance, from what I understand of Ken Griffey, what's really going on with his legs is that his hamstrings are pretty much permanently shredded. They get worse and better through time, according to all kinds of variables, and this leads to time on and off the DL. But it's really just a single injury that leads to multiple times on the DL.

So if Griffey's legs act up in 2004, and he goes on the DL, and then again in 2005, and he goes on the DL, it's not that he was injured in both seasons. It's that a single injury never healed (and never will), and the pain just got to be too much for a while in both years.

He also, though, had a second injury this year when he dislocated his shoulder. This suggests that above and beyond having a chronic injury that makes him DL-prone, he also may have some strange attribute that makes him injury-prone. I'd like to see that investigated too.

Ideally, we'd also control for team, although we're a few years away from that.

Cities with best players (October 23, 2003)

Posted 1:34 p.m., October 23, 2003 (#5) - Andrew Edwards
  Montreal has Pedro and half the greatest hockey players ever, but no football or basketball legends to mention.

Mooser has Toronto, but forgot Vince Carter.

Pittsburgh would be Clemente, Lemieux, and, well, now we find out how little I know about pro football. But surely the Steelers have had some great players.

Cities with best players (October 23, 2003)

Posted 1:35 p.m., October 23, 2003 (#6) - Andrew Edwards
  Of course, Pittsbugh had Honus Wagner too, who would have been a much better baseball player to include in that initial post.

Gleeman - Vlad (November 4, 2003)

Posted 2:36 p.m., November 5, 2003 (#6) - Andrew Edwards
  At the same time, there's something to be said for overpaying for extreme talent.

It's certainly a better strategy than what I like to call GordAshonomcis, which is paying $5-6 million for a whole mess of decent-but-not-great players and fielding a $70 million decent-but-not-great team year in and year out.

What's a Ball Player Worth? (November 6, 2003)

Posted 10:50 p.m., November 6, 2003 (#4) - Andrew Edwards
  Interesting work. As tango said, not novel, but good validation work.

Agree that pitchers are overrated, they almost certainly underrepresented fielding if Halalday and Delgado are their top 2 AL players.

Cool that they came up with $2 million per win too.

Futility Infielder - 2003 DIPS (January 27, 2004)

Posted 11:56 a.m., January 27, 2004 (#7) - Andrew Edwards
  Wow, three Jay hurlers with dERA significantly lower than actual ERA. All three no longer with the club. Doesn't that indicate there's a good probability for improvement?

And they signed Pat Hentgen, who was one of the most 'lucky' by DIPS. Does Keith Law not believe in DIPS anymore? Or did he get overruled?

Also, what the hell is wrong with Glendon Rusch? Is he just the least lucky pitcher in human history, or what?

Futility Infielder - 2003 DIPS (January 27, 2004)

Posted 1:57 p.m., January 27, 2004 (#12) - Andrew Edwards
  tj:

I actually agree, I think Hentgen will be fine this year. But combined with the other Jays moves, it adds up to an ostensibly anti-DIPS strategy, which is strange from this group.

Futility Infielder - 2003 DIPS (January 27, 2004)

Posted 2:41 p.m., January 27, 2004 (#14) - Andrew Edwards
  tj:

It's not even a criticism, really. It's just an observation that they let go of some guys who DIPS says should be a bargain, and signed a guy who DIPS says is overvalued. Each individual deal was fine, but when you step back and look at the aggregate, it looks inconsistent with a lot of Jays philosophy.

So I'm wondering if they've got something going on that I can't pick up - did Keith Law re-assess DIPS in some way we don't know about? Or were these just several tactical deals, into which I shouldn't read anythign about strategy?