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Reliever Usage Pattern, 1999-2002 (June 24, 2003)

Posted 6:14 p.m., June 24, 2003 (#9) - Jim
  Can you give an example of how you determined what the LI is for a particular situation? Also, how did you determine the cutoff points?

Competitive Balance (July 25, 2003)

Posted 11:53 a.m., July 29, 2003 (#6) - Jim
  Looking at the bottom 10, we see three WS winners in the last 10 years (Toronto, Florida, Arizona). Wonder how well this correlates to actual wins over a period of years? Yet this still doesn't answer questions of causation.

What I'd like to see is some breakdown showing what % of revenue is due to "inherent" factors and what % is due to factors within the team's control. We know that winning generates revenue, which certainly accounts for a significant portion of the Yankees' success. Smart management, good marketing, ticket sales would all be ways a team
could increase revenue short of moving to a better market.

Competitive Balance (July 25, 2003)

Posted 4:23 p.m., July 29, 2003 (#9) - Jim
  "The only way to increase revenues (long-term anyway) is to put a product on the field that performs better than the competition."

I don't disagree with that at all. However, there may be some business strategies a team could use to generate some cash that would enable them to invest in some key players to help the on-field performance. For example, building additional luxury boxes.

Ultimately, consistent winning is the way to generate long-term revenues. But like any business, you may have to build up winning and revenues slowly over a period of years.

Tippett and DIPS (August 1, 2003)

Posted 10:04 p.m., August 1, 2003 (#26) - Jim
  Regarding Ben's comments in #7, I'd like to see how pitchers fare in 2B+3B rate, the theory being that doubles and triples generally represent harder hit balls than singles. But I'd bet that pitchers don't really have much control over doubles vs. triples, i.e. triples likely differ from doubles only in terms of baserunning speed and defense/park effects. So slugging (or isolated power) probably adds too much noise by weighing triples too heavily. If Tippett is correct, I'd expect a higher correlation of year-to-year pitcher 2B+3B rates than 1B rates or BABIP (IPAvg).

Tippett and DIPS (August 1, 2003)

Posted 11:20 p.m., August 1, 2003 (#29) - Jim
  I'm not surprised that 2B/3B rates by park correlate well from year-to-year. I wonder if they correlate as highly as HRs? I'm not at all suggesting that we ignore park-effects. But intuitively, it seems to me the whole DIPS debate is about whether bad pitchers get hit "harder" than good pitchers, even on balls put in play. One way to test this would be by looking at play-by-play data, although that introduces the subjective element of line drive vs. fly ball. My suggestion is simply to look at 2B+3B rates, adjusted for park effects. If pitchers can indeed affect balls in play, perhaps they'd do so in such a manner that reduces extra base hits.

Of course, it might turn out that pitchers with low 2B+3B rates turn out to be groundball pitchers with slightly higher BABIP, while those with high 2B+3B rates are flyball pitchers with a lower BABIP.

Tippett and DIPS (August 1, 2003)

Posted 10:08 p.m., August 2, 2003 (#42) - Jim
  Tango, maybe I'm also misreading your numbers, but those correlations also appear quite different than what Tippett reported:

Tango: MinPA 500, Years 1969-2002, sample size 2814
Tippett: MinPA 400, Years 1913-2002, sample size 7486

Tango: HR corr. 0.20, BABIP corr. 0.22, K corr. 0.61, BB corr. 0.45
Tippett: HR corr. 0.29, BABIP corr. 0.09, K corr. 0.73, BB corr. 0.66

Am I missing something in the way these numbers were computed, or did pitchers in 1969 suddenly learn how to control in-play balls while losing their ability to control strikeouts and walks?

Tippett and DIPS (August 1, 2003)

Posted 10:10 p.m., August 2, 2003 (#43) - Jim
  Tango, just saw your latest post. Can't wait to see more research in this area!

Tippett and DIPS (August 1, 2003)

Posted 12:29 a.m., August 5, 2003 (#69) - Jim
  Ben (#61), I meant isolated power on balls in play. I'm not saying HRs are soley due to park effects and defense, I'm theorizing that a pitcher almost certainly doesn't have any control over a 2B vs. a 3B. If a good pitcher has the ability to prevent a ball in play from being hit "hard", it might show up as 2B+3B per ball in play, moreso than it shows up as total bases per ball in play or hits per ball in play.

In the other recent DIPS thread, it was discussed whether hitting triples is a skill beyond what can be measured by other power hitting stats. Probably yes, accounting for baserunning speed.

My question is whether preventing triples by a pitcher is a skill beyond what can be measured by other pitching stats. My guess is probably not.

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

Posted 5:14 p.m., August 5, 2003 (#18) - Jim
  Great stuff Tango! As I mentioned in another thread, one might expect XBH to represent "harder" hit balls than singles. Now it's not so clear there is a difference in pitcher ability. Probably it's because a lot of singles are hard-hit balls and a lot of doubles and triples are swung under by the batter but happen to fall in the gap or down the line. Yet HRs are probably always partly the fault of the pitcher. There aren't really a lot of flukey HRs.

I think the groundball/flyball distinction is an important one, and it would be interesting to see this breakdown with respect to BABIP and related stats.

What research has been done on GB/FB pitchers? Do they correlate with other pitcher characteristics (power, control, sinkerballers, knucklers, age)? Any (even anecdotal) evidence that pitchers can reliably induce grounders or flies by using certain types of pitches or locations in the strike zone?

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

Posted 5:09 p.m., September 22, 2003 (#6) - Jim
  As for football books, try The Hidden Game of Football by Carroll and Palmer, Pro Football Prospectus by Lahman and Greanier, and for a couple oldie but goodies at your used book store, The New Thinking Man's Guide to Pro Football by Paul Zimmerman and Football by the Numbers by Allen Barra and George Ignatin.

There's also some interesting stuff going on at footballoutsiders.com.
They seem to have patterned themselves after Baseball Primer.

Injury-prone players (October 14, 2003)

Posted 11:07 p.m., October 14, 2003 (#17) - Jim
  A related issue I'd love to see studied is whether there are any injury patterns on the team level. Do some teams have consistently more injuries than others, at least more than would be expected by chance?

This might tell us whether some teams are able to avoid injuries either by avoiding injury-prone players or by encouraging superior training/conditioning techniques. I think the average fan places little to no blame on a team that is hit hard by injuries, but rather attributes it almost entirely to bad luck. Yet this study implies individual injuries can be predicted to some resonable degree of accuracy, and so therefore a team should be able to at the very least make personnel decisions that are likely to reduce team injuries.

Relevancy of the Post-season (October 16, 2003)

Posted 2:31 a.m., October 20, 2003 (#14) - Jim
  Since it's very difficult (perhaps impossible) to consistently beat the actual Vegas betting line, I would guess the most efficient way to choose the "best" team is to see which team is the favorite to win the World Series at the end of the regular season. I'd guess the Vegas favorite wins the World Series more often than any other prediction system (or subjective individual analysis picks), and it seems unlikely that it would matter what the exact format of the postseason is.

Results of the Forecast Experiment, Part 2 (October 27, 2003)

Posted 12:19 p.m., October 28, 2003 (#51) - Jim
  Where are each of the systematic forecasters numbers published? I guess Shandler is Baseball Forecaster, Silver is PECOTA/Baseball Prospectus, Szymborski is ZiPS/Baseball Primer, Tippett is Dimond Mind Baseball.

What about Palmer and Warren?

Results of the Forecast Experiment, Part 2 (October 27, 2003)

Posted 5:16 p.m., October 28, 2003 (#57) - Jim
  Tango, I assume Palmer is Pete Palmer of Hidden Game. Who is Warren?

Also, in your pre-season writeup you said you were trying to get forecast data from STATS, Inc. Did you ever get these? I think these would be interesting since in the study Voros did a couple years ago, he found that STATS was among the most accurate in hitter projections.

ALCS Game 7 - MGL on Pedro and Little (November 5, 2003)

Posted 10:52 a.m., November 7, 2003 (#23) - Jim
  The good days/bad days question sound a lot like the hot hand (or cold hand) in basketball. Or streak hitting. Lot of research done on shooters and hitters as far as the predictive value of streaks, but very little on pitchers. You'd probably have to consider the in-game fatigue factor (high pitch counts). Might there something different about the mechanics of pitching (perhaps injury-related) that makes it more worthwhile to consider how a pitcher is performing that day in deciding how long to leave him in?

Tendu (November 24, 2003)

Posted 5:05 p.m., November 24, 2003 (#1) - Jim
  I would think it's awfully subjective to judge pitch type, location, and speed just from watching games on TV. Camera angles are different, the radar speeds shown on the screen graphic are unreliable, and there would be a lot of biases among the individual reviewers.

On the other hand, this seems like a great application for Questec.

Tendu (November 24, 2003)

Posted 12:36 a.m., November 25, 2003 (#3) - Jim(e-mail)
  Ron, I agree that the system still has value despite the subjective element. But it just seems like the manual process your data collectors use would be very tedious and error-prone, in addition to the biases mentioned above.

I'm curious, has your company made any attempts to work with Questec, perhaps to use data obtained from their SuperVision PitchTrax at least for a few games for quality-control purposes? Tendu sounds like the sort of system that would be much more accurate if the data collection process were automated.

Tendu (November 24, 2003)

Posted 12:43 a.m., November 25, 2003 (#4) - Jim
  I just realized that Questec already claims to have many MLB teams as clients and that they also apparently offer tools for statistical analysis. Perhaps Tendu views Questec as a direct competitor.

Tendu (November 24, 2003)

Posted 4:47 p.m., November 25, 2003 (#8) - Jim
  "Every player must prove to me his knowledge of pitch movement, pitch grips, pitch follow through, pitching mechanics and prove it via tests before they are hired."

OK, but what makes Ron qualified to be the judge? I would expect even the most experienced experts on the subject to have significant differences of opinion on matters that are fairly subjective.

Tendu (November 24, 2003)

Posted 12:03 a.m., November 26, 2003 (#10) - Jim
  I think part of the issue is inherent to the difficulty of judging exactly where a baseball traveling 90 mph passes with respect to an invisible floating 3-dimensional object. MLB umpires have far more experience and the best view of the pitch. Yet they are still notorious for having many different interpretations of the strike zone. I would think Tendu's data collectors, despite having the ability to use replay technology, would still be limited by not being there live and not having the proper camera angle (or even a consistent one from park to park). This is likely a significant hinderance to the accuracy of the system.

Tendu (November 24, 2003)

Posted 10:27 a.m., November 26, 2003 (#12) - Jim
  My guess is that Questec is significantly more expensive than Tendu. Questec is probably more accurate, but I'm guessing they don't yet have the capability for 100% coverage of all MLB games. Aside from each company's marketing claims, does anyone have any inside knowledge of how the client teams are using each technology? Getting back to my original point, it seems like a combination of the two systems would be best, and it would give you some quality control and some idea of the strengths and weaknesses of each system. In fact, it wouldn't surprise me if the Athletics are already doing this.

It's probably a lot like scouting vs. sabermetrics. Knowing how to use both in concert would give you a nice advantage.

FOOTBALL research (December 9, 2003)

Posted 4:30 p.m., December 10, 2003 (#1) - Jim (homepage)
  More on this work is at the above link, though it's a couple years old.

Professor who developed one of computer models for BCS speaks (December 11, 2003)

Posted 11:26 a.m., December 12, 2003 (#21) - Jim (homepage)
  I'm a BCS novice, but I noticed from David Wilson's page (linked above) that the BCS includes both predictive and retrodictive ratings systems. Can anyone here explain why?

Also, one thing that bothers me about the strength of schedule component is that it keeps adjusting itself throughout the season beyond what seems relevant. For example, USC lost points when Syracuse beat Notre Dame because USC played Notre Dame two months ago. But did USC really get perceptively weaker when SU beat ND? Or to put it another way, if USC and LSU were scheduled to play each other, and then SU beat ND, would the betting line on USC/LSU change as the result of this seemingly unrelated game? I seriously doubt it.

Professor who developed one of computer models for BCS speaks (December 11, 2003)

Posted 12:07 p.m., December 12, 2003 (#24) - Jim
  Tom, I understand the concept behind strength of schedule, but I just think they're splitting hairs by talking about a team that you played two months ago. Perhaps ND simply isn't as strong as it was then, maybe due to injuries or whatever.

I still go back to the Vegas hypothetical. If the ND/SU game wouldn't affect a USC game betting line by even 0.5 points, then you're not talking about anything of significance. You might as well flip a coin.

Professor who developed one of computer models for BCS speaks (December 11, 2003)

Posted 2:25 p.m., December 12, 2003 (#29) - Jim
  OK, if the BCS is not intended to be predictive, that makes the strength-of-schedule issue make more sense. So USC's strength-of-schedule factor would be no different if they had beat ND last week (as opposed to two months ago).

On the other hand, perhaps a predictive system would weigh recent games more heavily, including the strength-of-schedule component, to account for teams improving or declining during the season.

Batting average on balls in play, ground balls and other such beasts (December 24, 2003)

Posted 11:51 a.m., December 30, 2003 (#5) - JIm
  I'd think speed is really only a determining factor on GBs hit to the infield; even the slowest runner can reach first base on a GB that gets through the infield. So what % of GB hits are infield hits? This would seem to be very defense-dependent.

I'd like to see a breakdown of FB into line drives and "true" FB, subjective as it may be. Then true FB in play would almost be always outs, LD in play almost always hits, and GB somewhere in between.

SuperLWTS Aging Curve (January 26, 2004)

Posted 7:51 a.m., January 28, 2004 (#17) - Jim
  Older players don't only get playing time because they are still good, but often times they are still sitting on large salaries which make teams feel like they NEED to play those players. Can't have 'huge salaries on the bench'.

FANTASY CENTRAL (February 21, 2004)

Posted 2:57 p.m., March 19, 2004 (#140) - Jim
  I must say I'm impressed with the statistical knowledge and zeal for the fantasy baseball topic of the contributors here. I'm playing a points league for the first time. It is both AL and NL - 5 players to be kept for next season - new league - scoring as follows:

Hitting - 1 pt for singles, RBIs, runs, walks
2 pt for doubles, SBs
3 pt for triples
4 pt for HR
-1 pt for Ks and Caught Stealing

Pitching - 10 pts for Wins
-6 pts for Losses
5 pts for Saves
7 pts for Complete Game
-2 pts per Earned Run Allowed
-1 pts per Walk Allowed, Hit Allowed

I have to fill a basic roster of C,1B,2B,3B,SS,CI,MI,OF,OF,OF,UTIL,SP,SP,RP,RP,RP,P,P.

Am I right in concluding that the scoring system is weighted strongly in favor of hitters? It also seems that relief pitchers are much more desirable than starting pitchers. I kind of think that I should have 5 closer types and only a couple of starters. Do the math experts agree? Thanks.

FANTASY CENTRAL (February 21, 2004)

Posted 3:03 p.m., March 19, 2004 (#141) - Jim
  Re: #140

Pitchers also get 1 point per K.

FANTASY CENTRAL (February 21, 2004)

Posted 3:38 p.m., March 19, 2004 (#145) - Jim
  Thanks for the comments.

EconPapers: Steven Levitt (February 24, 2004)

Posted 12:05 p.m., March 1, 2004 (#12) - Jim
  As I recall, the bookies don't actually set the initial lines themselves, they subscribe to a service that does this for them. Las Vegas Sports Consultants does this service for the majority of books. Sports Illustrated did a fascinating story on this company a few months ago. The individual books then move their lines depending on the action they get.

I'd guess that the guys at LVSC are better handicappers than 99.9% of gamblers. They have to be--it's their profession. And likewise, it's nearly impossible to beat the sports books on a consistent, long-term basis.

MGL - Questec and the Strike Zone (March 20, 2004)

Posted 7:53 p.m., March 20, 2004 (#5) - Jim
  Does UZR account for shifts like the one used against Giambi? If he pushes a ball down the line, towards the normal position for a third baseman and soft enough where the play was made 90% of the time, does this count against the third baseman who is positioned at short?