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SABR 301 - Talent Distributions (June 5, 2003)

Posted 6:40 p.m., July 7, 2003 (#26) - MAH
  Tango, great article, graphics and comments. Your last comment made me wonder whether it would be possible to build a sensible model to "discount" player performances from eras in which the major league talent pool was artificially constricted (by the color bar, for example) or expanded (by the siphoning off of talent from declining non-affiliated "minor" leagues, such as the PCL). Any thoughts?

Redefining Replacement Level (June 26, 2003)

Posted 12:50 p.m., June 27, 2003 (#12) - MAH
  Great stuff. Will want to revisit the article and threads. My immediate take-away is that Nate has developed an elegant model for estimating the likely, practical impact on a team of losing a particular player. The per-game impact is higher for the first few games, and declines with time, as more and better replacement alternatives become available.

I wonder how this model should inform our thinking about all-time player ratings. Should we give a player with a twenty-year career "credit" for his value *each year* above "emergency" replacement level? Something tells me that we should use the two- or three-year replacement level; i.e., 85% - 90% of average.

Redefining Replacement Level (June 26, 2003)

Posted 1:52 a.m., July 7, 2003 (#31) - MAH
  David, Patriot and Tango,

After re-reading your posts, the following ideas occurred to me. Sorry for the slightly disorganized (and heretical) thoughts--the hour is late and I may not be expressing myself too well.

In evaluating how valuable a player has been during his career for purposes of all-time rankings or Hall of Fame consideration, maybe we should compare his value *during the time he actually played* against the "90%" 3-year-player (or the 85% 1-year player), and then *penalize* him for his *absences* from the lineup based upon the *likely* replacement value player given the *type* of his absences*.

Here is where Nate's formula becomes so important. (David's Sosa example is the source of the idea.) Certain players have a *pattern* of *sporadic* absences--a few games here or there that add up over the course of a season. It is a "quality" (and I don't mean to make a "character" issue out of it) that has real impact on the success of their teams. Say, Bob Horner. Or Eric Davis. For each such absence, we could *assume* that the 75% "emergency" player is the replacement, who thereby brings down the *team's* *expected* performance by the difference between the 85%-90% "baseline" and the "75%" emergency level.

Contrast the Bob Horner player with a workhorse who plays every game that he can--but suffers a serious injury that takes him out mid-season. In theory, we would assume that the first few games would be played by a 75% replacment player, but that at some point an 85% player will be found and start to play. Again, this is not a "character" issue--but if a workhorse *does* get injured, his teams *are* likely to suffer.

Now let's say that there's a player who persists in playing for a few years at the end of his career when he's clearly below average. Say, Brooks Robinson or Pete Rose at the end of their careers. Those players implicate Tango's example of the employee who's really hurting you. Team management should *know* that the aging player is *expected* to be below-average; they should *foresee* the need for a replacement and *find* the 90% 3-year player. The Pete Roses should be deemed to have a *negative* value to the extent they can't perform better than the 90% 3-year player who is "readily available" with the benefit of a little planning.

The type of career rating system I'm proposing would give credit to durable "average" players, who do have substantial practical value. It takes as its point of departure a "typical" team--i.e., not the theoretical Year Zero expansion team of cast-offs--and asks the question of how much the player is likely helping or hurting such team given the fact that with a little bit of planning such team can usually obtain the services of a 85-90% player before a season begins.

Modeling this rating system would not be practical for all players, but it might be appropriate for making retrospective career evaluations for the type of players evaluated in The New Historical Baseball Abstract.

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

Posted 12:00 p.m., June 27, 2003 (#2) - MAH
  Important first step. I'm very much in agreement with Dave, Tango and MGL on the need to disaggregate park factors. With regard to Shea, I seem to recall reading something during the '80s about how Shea hurt averages, but not power. If there *has* been a "switch", it might be attributable to two causes.

1) The new ballparks built since the '80s by and large have favored homerun hitting, so Shea's *relative* impact on homeruns might have changed from being neutral or slightly favorable to negative.

2) Shea used to have possibly the largest foul territory in the majors. Recently (I don't know when), the Mets owners installed new box seats in front of the old field level boxes, which significantly shrunk the amount of foul territory to something closer to average.

In general, the track lighting and high humidity at Shea probably has harmed visibility, thus probably causing higher-than-normal strikeouts. The foul territory used to permit *many* more foul pop-ups to be caught. The low altitude and high humidity probably keeps the ball from carrying (sorta like an anti-Coors). Finally, there are no "short" fences: its almost 340' down the lines, 396' in the power alleys and 410' to straight center.

Bonderman and Age 20 (June 26, 2003)

Posted 12:19 p.m., June 27, 2003 (#2) - MAH
  Bob,

Thanks for the article. I think it would be very interesting to know what has happened to 20-year-old pitchers who pitched *more* than 225 innings. Dwight Gooden never had a really dominant (at least as measured by park-adjusted ERA) full-time season after he pitched 220, 275 and 250 innings at ages 19, 20 and 21. It's just a hunch, but there may in fact be a "threshold" number of innings or estimated pitches for *young* pitchers beyond which the chances of career-impairing damage goes way up.

Estimating Pitch Counts (July 2, 2003)

Posted 12:51 p.m., July 2, 2003 (#3) - MAH
  Tango,

Thanks for posting the article. I very much agree that you have to measure Pedro using BFP, *not* IP. Is per-pitcher BFP data available publicly? Going how far back? Or do people try to estimate BFP? Thanks.

UZR inter-positional linear correlations (July 6, 2003)

Posted 8:12 p.m., July 6, 2003 (#2) - MAH
  Scott,

Thanks for running the test. For what it's worth, a model I've developed that relies only on traditional, non-PBP/Zone data, shows that properly context-adjusted team-level performance at each position is basically uncorrelated with performance at the other positions--in the latest version of the model, no Pearson's r was greater than 0.2 or so--clearly below the 0.3 level that is commonly used as a good rule-of-thumb for "significant" correlation. That doesn't necessarily mean that it is *impossible* for player A to impact player B's fielding performance, but, in general, properly measured fielder performance is "independent".

Thanks again.

What value firemen? (July 6, 2003)

Posted 2:03 a.m., July 7, 2003 (#2) - MAH
  Neat analysis. It also suggests a solution to the "motivational" problem of relief specialists asking (demanding) to be used suboptimally in order to rack up "saves" that they can convert to cash in the free agent market: offer to pay them more on the express condition that they will be used in a way that maximizes their IP*LI, and not their "saves".

UZR, multiple positions (July 7, 2003)

Posted 6:25 p.m., July 7, 2003 (#2) - MAH
  Tango, very interesting. As a practical matter, the selective sampling issue might not be very important. No one would ever consider putting Frank Thomas at third or left, so the fact that his absence from the sample causes the first base rating to seem a little high is not important. What the study suggests is that among the subgroup of players that it would not be crazy to shift around, the likely impact of shifting them around should be what you found. In a sense, the "selective" sample is the relevant sample.

Competitive Balance (July 25, 2003)

Posted 10:30 a.m., July 26, 2003 (#3) - MAH
  Tango, great article, as always. As a Mets fan, I masochistically[sp?] enjoy measurements of how bad they are. Something I've been meaning to do is quantify my hunch that they are currently the most "balanced" bad team in baseball--bad in getting on base, bad in slugging, bad in baserunning, bad in fielding (DER), bad in starting pitching, bad in relief pitching. They're the complete five[six]-tool bad team. Roger Cedeno is the perfect example of what I'm talking about--he's bad at everything, plus he makes more mental mistakes than anybody in the game AND collects a huge salary.

Another study I've been meaning to do is of the horrific history of Met free-agent signings, going all the way back to the 1970s. It may very well be the case that no team in any sport during the last quarter century has wasted more financial resources / inherent financial advantages than the New York Mets.

Your suggestion of grouping the high-Base Revenues teams with each other in the same division is a variation on a Bill James idea, proposed in TNBJHBA, that small-market teams should just refuse to play big market teams unless and until the big market teams share a sensible portion of their cable revenue. I like the idea a lot. This kind of fundamental reform is likely to be delayed, however, so long as so many pesky small-market teams keep doing well, while so many large market teams do badly.

Aaron's Baseball Blog - Andruw Jones (September 9, 2003)

Posted 10:43 p.m., September 9, 2003 (#5) - MAH
  I wonder whether Andruw's late-season plunges in performance are related to his not taking days off--he plays nearly every game. I also wonder whether the heat and humidity in Atlanta increases fatigue.