tag:blogger.com,1999:blog-23241716.post6544376398656204072..comments2007-11-13T18:57:33.679-05:00Justinhttp://www.blogger.com/profile/07697776280178146413noreply@blogger.comBlogger11125tag:blogger.com,1999:blog-23241716.post-76759550112700160162007-11-13T18:57:00.000-05:002007-11-13T18:57:00.000-05:00Thanks Dave, glad you enjoyed it and found it useful!<BR/><BR/>Thanks also for the typo catch. I'm terrible about typos and missing words, despite my proofreading passes. And that one in particular gets me all the time. :) -jJustinhttp://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-83028706240318071312007-11-13T18:47:00.000-05:002007-11-13T18:47:00.000-05:00Justin-<BR/><BR/>This is just awesome. I've never really taken the time to read a comprehensive breakdown of this stuff, and I find it fascinating. Your writing is clear and concise, and easy to follow. Can't wait to read the other ones you have posted!<BR/><BR/>One quick typo I noticed, which, considering the effort you put into this, I thought you might want to know about:<BR/><BR/>"is more accurate and flexible that Runs Created" should read "flexible than Runs Created" methinks.<BR/><BR/>Thanks!<BR/><BR/>-DaveAnonymousnoreply@blogger.comtag:blogger.com,1999:blog-23241716.post-15195362107504288512007-11-06T14:53:00.000-05:002007-11-06T14:53:00.000-05:00<I>So if you're looking to compare how good a player he is in a team-neutral way, the league-average linear weights is actually probably the way to go. But if you want to estimate how many runs he created for his team, I think you'd need team-specific weights.</I><BR/><BR/>I completely agree with your summary. Well said.<BR/><BR/><I>Naturally. You could also add the question as to whether it's even fair to a player to evaluate his performance in the context of his team, which he has little control or influence over.</I><BR/><BR/>That makes a lot of sense to me too, and it's something I talked about with Skyking a few weeks back. I've never been completely sure which direction I wanted to go with it either. If I'm just interested in comparing players within the Reds, for example, it's definitely best to use the custom team linear weights. But for comparing hitters across teams, I do lean toward using league-wide linear weights. Probably. Still not sure on that one though.<BR/>-jJustinhttp://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-4434142904707087342007-11-06T14:31:00.000-05:002007-11-06T14:31:00.000-05:00I think we can summarize it this way:<BR/><BR/>For an individual player...<BR/><BR/>- Base Runs estimates how many runs would be created per player by a team of players with the same statistics.<BR/><BR/>- Linear Weights estimates how many runs the player would have created for a league-average team.<BR/><BR/>- Linear Weights with team-specific weights estimates how many runs the player likely created for his own actual team.<BR/><BR/>So if you're looking to compare how good a player he is in a team-neutral way, the league-average linear weights is actually probably the way to go. But if you want to estimate how many runs he created for his team, I think you'd need team-specific weights.<BR/><BR/><BR/><B>part of my goal here (written or not) was to figure out how to accurately assess player value from easily-accessible data.</B><BR/><BR/>Naturally. You could also add the question as to whether it's even fair to a player to evaluate his performance in the context of his team, which he has little control or influence over.iblemetricianhttp://www.blogger.com/profile/13247503051718359682noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-66233367759455010962007-11-06T09:15:00.000-05:002007-11-06T09:15:00.000-05:00Hi there,<BR/><BR/>I disagree that linear weights is just the other side of the coin from base runs. Base runs are clearly inappropriate to use on players because players cannot interact with themselves. This is well-established and can lead to massive overvaluations for players with high OBP and SLG.<BR/><BR/>However, your criticism about linear weights is correct. It's not just the opposite bias, but it is a problem. Custom linear weights for teams are ultimately the way to go. Practically, it doesn't make a huge difference compared to using custom weights for a particular league (which is what I've posted here)...maybe 5 or 6 runs difference when you "move" an extremely productive hitter from a good offensive team to a poor offensive team in MLB. Nevertheless, that's something I'm planning to talk about in the last part in this series, along with park factors. One step at a time...<BR/><BR/>As for the situation specific values, my tendency is to not go that route. Past performance in those situations has very little predictive value compared to overall performance, and yet those adjustments can massively influence the values we attribute to those events. It's a give and take, but I'd rather avoid that kind of thing for the time being. Besides, it makes this stuff impossible to do from a single row of player data, and part of my goal here (written or not) was to figure out how to accurately assess player value from easily-accessible data.<BR/>-jJustinhttp://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-69046427369056368892007-11-06T03:38:00.000-05:002007-11-06T03:38:00.000-05:00Justin,<BR/><BR/>It's not clear to me precisely what you're looking to measure here.<BR/><BR/>Clearly, nonlinear models such as Runs Created and Base Runs fail to model individual run scoring, since they have the individual's on-base ability interact with his own runner advancement ability.<BR/><BR/>But Linear Weights makes the opposite mistake. It assigns a fixed run value to each offensive event based on the league average or (in your case) marginal value. Thus, it fails to take into account the actual team the player is on. The more your teammates get on base, the more valuable your double or home run potentially is, and vice versa. Run values of offensive events do depend on what your teammates will do with them.<BR/><BR/>So it would seem we should assign run weights to offensive events on a per-team basis.<BR/><BR/>But if we're really trying to assess a player's offensive contribution, shouldn't we take into account the fact that all singles, or all home runs, are not created equal? A single with two outs, no men on base and the pitcher on deck is worth less than a single with bases loaded.<BR/><BR/>Shouldn't we distinguish between hits with men on base and hits without, or between hits in high-leverage situations and those without, or by the number of outs, or by the on-base percentage of the batters on deck? But then, of course, the mathematics gets increasingly complex.<BR/><BR/>Ultimately, as I said to begin with, it depends on what you're really trying to measure. If you want to "estimate the number of runs a player contributes to a team in a given season," I'm not sure Linear Weights is more accurate than Base Runs. It's just differently biased.iblemetricianhttp://www.blogger.com/profile/13247503051718359682noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-26674870015287210612007-10-30T15:25:00.000-04:002007-10-30T15:25:00.000-04:00Retrosheet has the ROE everywhere.Tangotigerhttp://www.blogger.com/profile/11864323151591103655noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-47360162881688408662007-10-22T13:49:00.000-04:002007-10-22T13:49:00.000-04:00Joel, thanks for the tip on RBOE's at B-ref! I checked it (and everywhere else I could think of) to see if those numbers were present, but only on the main page, and not the splits page. <BR/><BR/>I may take you up on getting those data at some point, but for now, don't worry about it--I doubt I'm all that far off without them. -jJustinhttp://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-3224254778515215922007-10-22T10:52:00.000-04:002007-10-22T10:52:00.000-04:00Just getting around to reading this. Interesting stuff. I've just been getting interested in BaseRuns recently, and I've used Linear Weights off and on for the last couple of years. Usually, if I quote a run estimator for a player though, it's the RC from Baseball Reference, but that's only because of convenience. So, once you calculate everything and post it, I'll just refer to you, okay? cool. :)<BR/><BR/>Anyway, if you are interested in including ROE in your run estimators, BRef has them in the splits for both individuals and teams. I don't remember what is behind the subscription wall and what isn't, but if you need help getting to them, let me know and I'll get you a sample of them.Joelnoreply@blogger.comtag:blogger.com,1999:blog-23241716.post-32983772384919213842007-10-18T14:09:00.000-04:002007-10-18T14:09:00.000-04:00Hi,<BR/><BR/>It's a fair critique. Errors, in particular, are available for team stats, and if you look at Tango's version of base runs, they are included. That's one of the advantages of baseruns--it's flexible enough that you can add and remove terms as needed based on what you have to work with. In this way, there really isn't one The Base Runs Formula, but they're all inter-related...and some are better than others.<BR/><BR/>I didn't include them because my primary goal in developing the above base runs equation was to use it to deliver accurate linear weights that could be used on hitters. Therefore, I only included statistics that are typically available for hitters...while I'd love to have reached base on error and advanced on error terms in my base runs model, I can't get that without parsing retrosheet data, and I haven't gotten that to work yet.. <BR/><BR/>If my goal was instead to just predict team runs, I would definitely include the error term. This, in fact, is what was done in that post I linked to about the Israeli Baseball League, and it made a huge difference because of the rather absurd error rates in that league.<BR/><BR/>Tango had a recent post on the runs value of an error (look at the '07 fielding data post that I made...I think it links to it) in which he noted that a missed play--be it an error, or a ball a player didn't get to but another defender would, is worth ~.8 runs. You can trace this to the marginal value of a single (~0.48) plus the marginal value of an out (-0.27 runs). <BR/><BR/>Or you can do something like what you did: go back and compare all games where hits were the same but teams differed by one error, average 'em up, and you'll find that the team with the error gave up ~.8 runs more than the other teams (so says Tango anyway...haven't done it myself).<BR/><BR/>Note, because the linear weights I report in this post uses an absolute scale, it doesn't have the same out value as Tango's marginal linear weights. But since we usually measure fielding on a marginal scale (i.e. vs. average), those are the numbers to use.<BR/>-jJustinhttp://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-8609788222608587942007-10-18T13:34:00.000-04:002007-10-18T13:34:00.000-04:00Why aren't things like errors and wild pitches considered when trying to estimate how many runs a team has scored? I know they have value and they contribute to the scoring of runs, but they are simply dismissed in the base runs formula (unless I am missing something). I read on the Baseball Fever that errors have about the same run-value as singles and should be considered as such. This was posted by TangoTiger. (I saw in another article that errors were worth .49 runs) The average NL team made right at 100 errors in 2007. The average NL team made 50 wild pitches in 2007. If you add 100 singles to the team stats (for the errors) and then change 50 singles to doubles (for the wild pitches - and often-times wild pitches occur with more than one runner on base) and run the Base Runs formula you will find that it is off by approximately 75 runs. IOW it estimates that teams should score about 75 more runs than if you run run the Base Runs formula without regard to errors and wild pitches. This would indicate to me that either some of the positive coefficients are too high or some of the negative coefficients are too low. I guess my question is this: how does the Base Runs formula account for errors and wild pitches? Thanks for any light you could shed on this for me.<BR/>Here is a quick anecdote. I once went through five seasons worth of box scores for the Reds (2000-2004) and summed up the statistics for games in which the opponents made an error, and games in which they didn't. I have long since lost that data, but in games in which the other team made an error the Reds scored roughly 10% more runs than Runs Created would suggest. And they scored about the same 10% less than expected in error-free games. If you summed the two it was a very close estimate. It would seem that errors and wild pitches would not be that hard to track.<BR/><BR/>PS Yes EdE had a fine second half. =)texasdavehttp://www.blogger.com/profile/17215541522980498371noreply@blogger.com