tag:blogger.com,1999:blog-23241716.post2719216967425321508..comments2023-07-09T11:23:36.355-04:00Comments on On Baseball & The Reds: Markov: Dusty Baker's lineups aren't half badjinazhttp://www.blogger.com/profile/07697776280178146413noreply@blogger.comBlogger31125tag:blogger.com,1999:blog-23241716.post-37368706095827826082008-04-16T07:08:00.000-04:002008-04-16T07:08:00.000-04:00Hmmm... looks like the post was lost. Using the P...Hmmm... looks like the post was lost. <BR/><BR/>Using the PECOTA forecasts noted in the main blog entry, and ignoring batting handedness, speed, and GIDP (all things I would not normally ignore), with wOBA in parens:<BR/><BR/>1. Hatty (.358)<BR/>2. Dunn (.401)<BR/>3. Junior (.360)<BR/>4. Encarnacion (.367)<BR/>5. Keppinger (.348)<BR/>6. Phillips (.334)<BR/>7. Valentin (.333)<BR/>8. Pitcher (.160)<BR/>9. Patterson (.311)<BR/><BR/>I don’t see how it’s possible to have such a big disagreement here. Other than Dunn and Patterson, the PECOTA forecasts are very tight for the rest of the players.<BR/><BR/>Here’s a reasonable lineup (5 best players remain in the top 5, don’t touch the pitcher), but in the worst possible combination:<BR/>1. Encarnacion (.367)<BR/>2. Junior (.360)<BR/>3. Dunn (.401)<BR/>4. Keppinger (.348)<BR/>5. Hatty (.358)<BR/><BR/>6. Patterson (.311)<BR/>7. Phillips (.334)<BR/>8. Pitcher (.160)<BR/>9. Valentin (.333)<BR/><BR/>And that’s just 3 runs worse than the optimal one that my Linear Weights model would suggest.<BR/><BR/>Basically, it’s pretty difficult to create a bad lineup (notwithstanding the exceptions I noted at the start of this post).Tangotigerhttps://www.blogger.com/profile/11864323151591103655noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-48944713389740471452008-04-15T19:19:00.000-04:002008-04-15T19:19:00.000-04:00Xeifrank, the more the merrier! Tango is also goi...Xeifrank, the more the merrier! Tango is also going to run MGL's projections on these lineups and see what his simple markov comes up with.<BR/><BR/>As for the data, you should be able to calculate all of that from MGL's posted projections. But I can also look them up for you when I get a sec. -jjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-68061910536464021602008-04-15T18:30:00.000-04:002008-04-15T18:30:00.000-04:00Justin,That's amazing that the two systems are inv...Justin,<BR/>That's amazing that the two systems are inverted on the top and bottom lineups. Perhaps, i should try running the two on my simulator and see which one my simulator trends towards. If you'd like me to try that, I could but I format my hitters input data a little differently. I would need to know OBP, AB, 1B, 2B, 3B, HR, BB, K for the hitters.<BR/>vr, XeifrankAnonymousnoreply@blogger.comtag:blogger.com,1999:blog-23241716.post-90280108026177563012008-04-15T15:41:00.000-04:002008-04-15T15:41:00.000-04:00Fun stuff, Justin. I thought you were accounting ...Fun stuff, Justin. I thought you were accounting for platoon splits, for some reason - hence my two lineups for everything. <BR/><BR/>The "bottleneck" theory is a very interesting one. Baker is sailing into the wind here, but some of the typical nonsense moves we might expect (Juan Castro batting second; Phillips' crappy OBP in the cleanup spot) may actually be beneficial.Chris at Redleg Nationhttps://www.blogger.com/profile/03474147423587094139noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-42059275733711160122008-04-15T13:40:00.000-04:002008-04-15T13:40:00.000-04:00Ok, I've run MGL's splits through the model. And ...Ok, I've run MGL's splits through the model. And I'm sure I'm now using the model correctly. <BR/><BR/>Those projections are much worse than the PECOTAs! But the rank order from this model has Baker actually coming out on top. Here are the results, listed in the same order you listed them:<BR/><BR/>Baker OD: 4.41 r/g, 715 r/sea<BR/><BR/>Old Top 3:<BR/>Bluzer OD: 4.32 r/g, 700 r/sea, -16 above Baker<BR/>Chris-OD2: 4.34 r/g, 703 r/sea, -12 above baker<BR/>Pickoff-OD: 4.36 r/g, 706 r/sea, -9 above Baker<BR/><BR/>Old Bottom 3 (bottom first):<BR/>redmanrick-OD: 4.26 r/g, 691 r/sea, -24 above Baker<BR/>Brad-OD2: 4.30 r/g, 697 r/sea, -18 above baker<BR/>fareast-OD: 4.33 r/g, 701 r/sea, -14 above baker<BR/><BR/>Mine:<BR/>jinaz-OD: 4.39 r/g, 711 r/sea, -4 above Baker<BR/>jinaz-OD-exploit: 4.33 r/g, 701 r/sea, -14 above baker<BR/><BR/>I'm using 2007 #9-slot hitting totals now, which come to a 0.170/0.216/0.250 hitting line. Before I was using pitchers only, but this helps account for the late-inning pinch hitters.<BR/><BR/>So...Still disagreements between the two systems. These come out much lower than yours (using the same projections, mostly), and with a different rank order. And the range is a bit higher as well, with ~24 runs between the worst and best in the Markov and ~11 runs between the best and worst in your sim.<BR/><BR/>The rank order differences are just bizarre though. Baker's lineup comes out on top in this Markov, but is doing <I>terribly</I> in your sim. In fact, the worst lineup according to this Markov is the best in your sim...it's almost like they're inverted!<BR/><BR/>????<BR/>-Justinjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-76710661750967770612008-04-15T04:19:00.000-04:002008-04-15T04:19:00.000-04:00Important Note!!John Beamer discovered an error in...Important Note!!<BR/><BR/>John Beamer discovered an error in my use of his model tonight. I'll re-do all of the lineups using this modification, but I ran out of time to do it tonight. Initially, it looks like the major findings remain the same, and that Baker continues to do well...better, in fact.<BR/><BR/>MGL, I haven't given your projections a try yet, but will tomorrow night (hopefully). <BR/><BR/>@Anthony, my instructions to you weren't quite right. Forget the Hlookup. What you should do is just copy the entire row in your new row 32 up to row 30. Row 30 does not know anything about the lineup order that you manipulate in row 29. In other words, whatever is in C30 is always associated with the leadoff hitter.<BR/><BR/>John recommends doing this a few times, pushing the SBA button in between, until the values converge. I'm finding that just creating a direct link to row 32 works fine--no apparent problem with infinite loops, etc.<BR/>-jjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-55776905354532077272008-04-14T15:14:00.000-04:002008-04-14T15:14:00.000-04:00Justin The iteration step is straightforward. The ...Justin <BR/><BR/>The iteration step is straightforward. The PA per line up spot should "converge" all you need to do is copy the computed PA into the PA per position 2-3 times, update the SBA (push the button) and the rpg shouldn't change.<BR/><BR/>If you do get different results perhaps you can send me the exact input data you use and I will look into the Markov logic and try to piece if anything is falling down. I'm pretty sure everything is working as it should but as with all these things you never know. Then I can also adjust for other stuff like handedness etc. All those variables you can adjust for manually in the code but it is harder to automate in a mathematical model as you have to make assumptions that don't hold up to reality<BR/><BR/>-beamerUnknownhttps://www.blogger.com/profile/03526796566602278577noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-66664521520628968122008-04-14T14:47:00.000-04:002008-04-14T14:47:00.000-04:00Justin, that's great that John put this tool toget...Justin, that's great that John put this tool together. Like he said you and MGL need to use the same input data. Keep up the great blog, your site is an every day must read. vr, XeiXeifrankhttps://www.blogger.com/profile/15904090174534262598noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-92066794924336021442008-04-14T14:13:00.000-04:002008-04-14T14:13:00.000-04:00Xeifrank, the above results are not based on David...Xeifrank, the above results are not based on David Pinto's lineup tool. they use Markov chains, which is definitely a better tool for this purpose. The sim might be better, but I honestly wouldn't expect them to be *that* different given how much info the Markov uses. -jjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-60107779331279888262008-04-14T13:04:00.000-04:002008-04-14T13:04:00.000-04:00Ok, my questions were answered in reading the comm...Ok, my questions were answered in reading the comments. I was thinking along the same lines as MGL, that a simulator would do a better job than a Markov Chain. I have a simulator too, but he beat me to it. :) Good work everyone.<BR/>vr, XeifrankXeifrankhttps://www.blogger.com/profile/15904090174534262598noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-80506184652347476352008-04-14T12:57:00.000-04:002008-04-14T12:57:00.000-04:00Justin, this is a nice excercise. Great job. I h...Justin, this is a nice excercise. Great job. I have a question, and I must admit that I haven't yet read the whole study (I will, I will). The Pinto tool for projecting runs per season, did you make any adjustments for "splits", ie - LHB vs LHP, LHB vs RHP? Does the Pinto model take into account speed/baserunning? If not, do you think it's important that you take into consideration more factors than OBP and SLG? Perhaps you'd see at the very minimum some adjustments to the run totals. Thanks!<BR/>vr, XeifrankXeifrankhttps://www.blogger.com/profile/15904090174534262598noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-5282863744412403772008-04-14T10:57:00.000-04:002008-04-14T10:57:00.000-04:00MGL, thanks for those projections. I'll try to gi...MGL, thanks for those projections. I'll try to give them a run tonight in the Markov and see what happens. I may try Beamer's additional step of iterating the PA based on lineup spot as well if I can figure that out.<BR/><BR/>I really would think that these two approaches would result in fairly similar results, at least in a gross sense. If nothing else, they both should be vastly superior to the regression-based analyses we've seen. -jjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-73448372038728855752008-04-14T03:39:00.000-04:002008-04-14T03:39:00.000-04:00Oh, and I was mixing up Phillips with someone else...Oh, and I was mixing up Phillips with someone else in my mind. He was +5 in 07 UZR and I have him with an average defensive projection overall.<BR/><BR/>The Reds still have one of the worst projected team defenses (-33 per 150), though, owing mostly to Griffey and Dunn, who are a combined 35 runs or so below average per 150 in projected UZR (-15 for Dunn and -20 for Griff).<BR/><BR/>I have Hatty with an average defensive (UZR) projection and below average (-2) in "scooping bad throws."<BR/><BR/>MGLAnonymousnoreply@blogger.comtag:blogger.com,1999:blog-23241716.post-22717425052593496092008-04-14T03:31:00.000-04:002008-04-14T03:31:00.000-04:00I don’t know how much difference it makes, but the...I don’t know how much difference it makes, but the sim uses all kinds of other variables, such as each player’s projected sb/cs rate, foul out rate, infield singles rate, roe rate, bunt rate (attempts and results), sacrifice rate (attempts and results), IBB rates, etc. Shouldn’t really make much difference in terms of batting order, I wouldn’t think.<BR/><BR/>Here are the projections it is using for each player, more or less. Singles are regular, infield, and bunt (sac and regular bunts) attempts combined. All are per 510 PA, where a PA is not including an IBB. These are park neutral and scaled to average NL offensive rates for 05-07, where the average wOBA for a non-pitcher is .340.<BR/><BR/>Dunn<BR/>S 51 d 22 t .9 hr 29 bb+hp 83 so 127 sb 4 cs 1 wOBA .382<BR/><BR/>Encarnacion<BR/>S 79 d 29 t 1.7 hr 17 bb+hp 50 so 75 sb 7 cs 2 wOBA .360<BR/><BR/>Keppinger<BR/>S 107 d 24 t 3.0 hr 6 bb+hp 38 so 33 sb 4 cs 2 wOBA .342<BR/><BR/>Griffey<BR/>S 68 d 22 t .7 hr 20 bb+hp 52 so 87 sb 4 cs 1 wOBA .335<BR/><BR/>Hatteberg<BR/>S 81 d 24 t .9 hr 8 bb+hp 61 so 46 sb 1 cs 1 wOBA .329<BR/><BR/>Phillips<BR/>S 82 d 22 t 3.2 hr 15 bb+hp 35 so 76 sb 14 cs 5 wOBA .324<BR/><BR/>Valentine<BR/>S 79 d 26 t .8 hr 12 bb+hp 37 so 68 sb 1 cs 1 wOBA .311<BR/><BR/>Patterson<BR/>S 84 d 25 t 4.1 hr 15 bb+hp 26 so 98 sb 25 cs 8 wOBA .311<BR/><BR/>As you can see, my projections are not very flattering - only 3 players are above average hitters and the entire lineup averages .337 in wOBA, 3 points below the NL average, which amounts to 15 runs worse than average per year. And that is with their best lineups (not including Votto and Bruce, I guess).<BR/><BR/>I don't have much optimism for the Reds, BTW. Pre-season I had them at 77 wins. As of yesterday, I had them at 78 wins. After today, it is 77.5, with a 1% chance of winning the pennant and 0% (rounded off to the nearest percent) chance of winning the WS. I do have them with a 7% chance of making the post-season. I have them as the 6th worst team in the NL (could be worse I guess) in front of only PIT, WAS, HOU, FLO, and SF. My season projections include some significant playing time for good players like Bailey, Votto, and Bruce. I actually like their pitching (3 wins over average). I have their staff as the 5th best in the NL, behind only ARI, LA, Mets, and SD, with MIL right behind them.<BR/><BR/>MGLAnonymousnoreply@blogger.comtag:blogger.com,1999:blog-23241716.post-77287590954911946162008-04-14T01:34:00.000-04:002008-04-14T01:34:00.000-04:00Justin -- no you do it manually. Let me have a loo...Justin -- no you do it manually. Let me have a look when I have 5 mins today and drop you a line with detailed instructions. <BR/><BR/>By the way to compare this with MGL's sim we should absolutely use identical forecasts ...Unknownhttps://www.blogger.com/profile/03526796566602278577noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-14308939730825405372008-04-14T00:58:00.000-04:002008-04-14T00:58:00.000-04:00ps to do the lineup analysis correctly you have to...<I>ps to do the lineup analysis correctly you have to iterate the PA per position. For similar line-ups this shouldn't make a difference but can be a source in instability ... you do this by copying and pasting the computed PA per position into the relevant part of the line-up spreadsheet.</I><BR/><BR/>This sounds like it could potentially make a difference, so I'd like to try it. <BR/><BR/>I'm having a hard time figuring out how to do this, though. I snooped around the common calculations page, but I'm not seeing it. Do I need the source code version to find the calculated PA? I'm also unclear about where I'd paste them.<BR/><BR/>Thanks,<BR/>Justinjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-53613144461851631902008-04-14T00:46:00.000-04:002008-04-14T00:46:00.000-04:00MGLThe model includes baserunning and GDPs. It als...MGL<BR/><BR/>The model includes baserunning and GDPs. It also includes the the difference between a strike out and a batted ball out.<BR/><BR/>The GDP variable is calculated for each player individually based (principally) on the number of singles they have. <BR/><BR/>There is an implict, debatable assumptions here: that the ratio of GB/1B is roughly constant (no idea if this is true).<BR/><BR/>One thing I don't adjust for is left handed vs right handed batters. As you point out I probably should. <BR/><BR/>I tested the line-up part of the Markov extensively against real world data (especialy the PA per batting position) so I think it works fairly well (within the constraints of the Markov approach). Of course a fully fledged sim allows you take into account more variables but doesn't model the essence of the game, which is what the Markov does (not that that matters).<BR/><BR/>Justin -- if there is additional work you want me to do drop me a line. Also I am more than happy to make the Markov "source code" available to anyone who has bought the THT annual -- the only reason I didn't is because it is pretty complicated.<BR/><BR/>-Beamer<BR/><BR/>ps to do the lineup analysis correctly you have to iterate the PA per position. For similar line-ups this shouldn't make a difference but can be a source in instability ... you do this by copying and pasting the computed PA per position into the relevant part of the line-up spreadsheet.Unknownhttps://www.blogger.com/profile/03526796566602278577noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-76729863572595350372008-04-14T00:42:00.000-04:002008-04-14T00:42:00.000-04:00@Anonymous,I get 4.87 R/g, 788.5 runs/season, -0.6...@Anonymous,<BR/><BR/>I get 4.87 R/g, 788.5 runs/season, -0.6 runs above Baker per season.<BR/><BR/>-jjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-76872053881154124952008-04-13T23:56:00.000-04:002008-04-13T23:56:00.000-04:00Hi MGL,Thanks for the quick work!It is a bit unner...Hi MGL,<BR/><BR/>Thanks for the quick work!<BR/><BR/>It is a bit unnerving to see how different your results are. You absolutely could be right about the importance of the handedness and baserunning details that your simulator takes into account. I do wonder how much your final point about the differences between your projections and the PECOTAs I used might also be coming into play though. Looks like the big differences were on Keppinger, Hatteberg, and especially Patterson. As you say, the Reds' lineup is fairly balanced, so differences like that could result in big differences in the rank order of lineups. Of course, the Patterson difference should just help Dusty's case, and he clearly got creamed in your sim.<BR/><BR/>As for your other points, I generally agree (though I still think that UZR must be missing low with Phillips given how he does with the Fans, PMR, and RZR...but we've had that conversation already!). A point I've made a few times is that if the Reds are going to contend, they're going to need surprises from both their offense and defense. And the only way they'll get surprises from their offense is if they play high-upside players like Jay Bruce and Joey Votto over known quantities like Patterson and Hatteberg. <BR/><BR/>FWIW, Votto does have pretty good speed for a first-baseman (perhaps average overall?), though reviews of his glove have been a bit mixed. I'm just assuming that he's an average defender for now. Hatteberg's been all over the place from year to year defensively, but I think he's at least not terrible.<BR/>-jjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-27272747539525131712008-04-13T23:50:00.000-04:002008-04-13T23:50:00.000-04:00Try from opening day players:1)Dunn2)Keppinger3)Gr...Try from opening day players:<BR/>1)Dunn<BR/>2)Keppinger<BR/>3)Griffey<BR/>4)Encarnacion<BR/>5)Hatterberg<BR/>6)Phillips<BR/>7)Patterson<BR/>8)Valentin<BR/>9)PitcherAnonymousnoreply@blogger.comtag:blogger.com,1999:blog-23241716.post-4389682763269800912008-04-13T23:20:00.000-04:002008-04-13T23:20:00.000-04:00Using my sim, I ran each lineup 100,000 times at h...Using my sim, I ran each lineup 100,000 times at home (neutral stats adjusted for home field advantage) in a neutral park against a neutral, league-average (neither RH nor LH) pitcher, using my projections for each player. My sim includes baserunning, GIDP, etc., so it is pretty much all encompassing. The standard deviation of runs per game for one team in 100,000 games is .009. So these numbers are plus or minus .018 runs at 2 sigma (with a 95% confidence interval). <BR/><BR/>Baker: 4.560<BR/>Baker with Votto rather than Hatteberg: 4.646 rpg +13.9<BR/>Your #1: 4.604 +7.1<BR/>Your #2: 4.618 +9.4<BR/>Your #3: 4.615 +8.9<BR/>Your worst: 4.626 +10.7<BR/>Your 3rd worst: 4.620 +9.7<BR/>Your 4th worst: 4.549 +1.8 <BR/>Jinaz-OD: 4.588 +4.5<BR/>Jinaz-OD-exploit: 4.579 +3.1<BR/><BR/>I re-ran each lineup at home at GABP, rather than a neutral park:<BR/><BR/>Baker: 4.640 <BR/>Baker with Votto rather than Hatteberg: 4.763 +19.9<BR/>Your #1: 4.706 +10.7<BR/>Your #2: 4.736 +15.6<BR/>Your #3: 4.758 +19.1<BR/>Your worst: 4.729 +14.4<BR/>Your 3rd worst: 4.731 +14.7<BR/>Your 4th worst: 4.672 +5.18<BR/>Jonaz-OD: 4.679 +6.3<BR/>Jinaz-OD-exploit: 4.690 +8.1<BR/><BR/>Let me say a couple of things: One, Dusty’s lineup is one of the worst you can put out there, as you can see from the above, based on my projections and my sim. You really have to make an effort to do as badly as Dusty.<BR/><BR/>I have much more confidence in a comprehensive sim than a “dry Markov chain.” In fact, I think that using a Markov chain that does not include handedness, baserunning, etc., is a waste of time for evaluating lineups. <BR/><BR/>Two, the Reds have a roughly average first-string lineup, despite what you often hear about them having a very good one or even a great one. And of course, the defense is awful, as long as Griff, Dunn, and Phillips are out there.<BR/><BR/>Three, can we stop saying that Griffey is a “great hitter.” He is not anymore. Not even close. He is a below-average hitting corner outfielder. With his terrible defense and baserunning, he is near replacement level. One of the worst overall players in baseball. Possibly the worst full-time player. Has been for a few years.<BR/><BR/>Four, Baker’s (or whoever makes those decisions) biggest mistake is playing Hatteberg over Votto. I don’t know about their defense, but Votto is almost a win and a half better with the bat than Hatty. If Hatty is a better defender, it probably is not more than a win, unless Votto is a DH-like entity, awful with the glove. And of course Hatty cannot run the bases a lick. I don’t know about Votto.<BR/><BR/>Five, the Reds lineup is quite balanced, as compared to many or even most, so that it does not make that much difference who you put where, as you can see from the above. As long as Keppy, Griffey, Dunn and Encarnacion are near the top or middle of the lineup, you are fine. And no one is that bad that they can’t pretty much bat anywhere, although Valentine being the worst and the slowest should probably bat last in any lineup.<BR/><BR/>Six, just eyeballing the above Zips projections, my projections are quite a bit different. I have, in a neutral setting, something like, in wOBA, Dunn, .386, Encarnacion, .368, Keppinger, .353, Griffey, .348, Hatty, .338, Phillips, .338, Patterson, .338, Valentine, .323.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-23241716.post-24998060585816240162008-04-13T19:30:00.000-04:002008-04-13T19:30:00.000-04:00Brilliant! Thanks, Justin.Brilliant! Thanks, Justin.Anonymousnoreply@blogger.comtag:blogger.com,1999:blog-23241716.post-45193031243996878232008-04-13T18:17:00.000-04:002008-04-13T18:17:00.000-04:00@MGL,John Beamer's the better person to ask about ...@MGL,<BR/><BR/>John Beamer's the better person to ask about the inner workings of the model. I'm just plugging in numbers. But here's what I know:<BR/><BR/><I>I assume that the Markov model does not include baserunning?</I><BR/><BR/>The model does include situation-based baserunning. But aside from stolen bases I don't think it varies the probabilities of taking extra bases, pickoffs, etc, based on the given batter's skills. I *think* the best we can do in this model is make adjustments across all batters and see how that changes the results. I haven't messed with this at all.<BR/><BR/><I>Also, does the model include GDP's and the differences, for example, between a strike out and batted ball out (moving runners over, etc.)?</I><BR/><BR/>The model does request inputs of GDP's and strikeouts, so I'm pretty sure that it includes those in its calculations. And that it handles advancement on strikeouts differently than regular outs. Not positive about that, however.<BR/><BR/><I>Does it move runners over differently on a batted ball out, depending on the handedness of the batter?</I><BR/><BR/>There is a matrix that allows one to manipulate the frequency with which one takes a base on an out, and it does so for all base/out situations. However, the model knows absolutely nothing about the handedness of the batter.<BR/><BR/><I>Finally, if it uses GDP, does it use a GDP projection for each player or does it assume the same GIDP rate for all players? If the latter, it it based on BIP for that player, and does it distinguish between RH and LH batters (the former hit into DP's more than twice the rate as the latter)?</I><BR/><BR/>It does ask for input on GDP's, and the baserunning matrices have a specific category for what happens to baserunners during a double play. <BR/><BR/>However, because I'm using PECOTA projections, which do not include GDP projections, I estimated GDP's for all players based on 2007 averages. I did it based on BIP rates (i.e. GDP / [AB-K-HR]), not GDP/PA. I imagine that including information about speed would also be helpful, but I didn't do this.<BR/><BR/><I>I have a sim that incorporates everything. I can run it on several lineups if you want and report back.</I><BR/><BR/>If you'd like to run your sim on the Baker opening day lineup and the top 3 (or whatever) and bottom 3 opening day lineups according to this model, I think that'd be pretty interesting to compare to the results!<BR/><BR/>I also agree about the left vs. right lineups, and breaking up lefties to prevent late-inning left-handed relievers from neutralizing your lineup. However, this model doesn't have the capability of dealing with that yet (right John?). Still, the philosophy behind left & right lineups should be similar, no? It's just that you use different input data, i.e. data that recognizes left/right splits of players.<BR/><BR/>In other words, while this model might not allow us to identify The Best Real Life Lineup, it should help us understand what approach(es) to lineup construction are most successful given a set of input data.<BR/><BR/>Thanks for dropping by!<BR/>-jjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-32892594696542365112008-04-13T17:58:00.000-04:002008-04-13T17:58:00.000-04:00@Anthony, that's a modification that I had to do w...@Anthony, that's a modification that I had to do with Beamer's help. Here's how I'm doing it:<BR/><BR/>First, in row 31, I created some lineup lookup numbers. So, C31 is 1, D31 is 2, E31 is 3, etc.<BR/><BR/>Then, in row 32, columns C-K, I pull the actual innings led off from the model. The code in C32 is "='Line-up start'!L61" (without double quotes). D32 is L62, E32 is L63, and so on.<BR/><BR/>Finally, I then use an Hlookup function to pull the correct innings led off from row 32. The code for C30 is: "=HLOOKUP(C29,$C$31:$K$32,2,FALSE)". D30 is the same, except that the lookup cell is D29 instead of C29.<BR/><BR/>I uploaded a screenshot of how it looks <A HREF="http://jinaz.reds.googlepages.com/markovsheet.gif" REL="nofollow">here. </A> Let me know if this is unclear. -jjinazhttps://www.blogger.com/profile/07697776280178146413noreply@blogger.comtag:blogger.com,1999:blog-23241716.post-68350273002799637572008-04-13T16:48:00.000-04:002008-04-13T16:48:00.000-04:00Are you using the Team Batting tab? I'm using the ...Are you using the Team Batting tab? I'm using the THT Markov spreadsheet, but the "number of innings led off" row doesn't change on mine. I'm curious how you're getting the different leadoff numbers for different lineups.Anonymousnoreply@blogger.com