Updating projection tables as free agents get signed.

Like the message says, I'll be updating the projection tables as free agents are signed.

This will also give us a good idea of projected dollars/win, which could be interesting as the offseason goes on.

UPDATE: 11/27/08
The Swindle signing moves the Brewers pitching to -1.97 WAA.
Bourgeois doesn't appear to be a player who will receive a roster spot (he's right around replacement level anyway) so he won't be put on my list unless he does make the roster.

CURRENT PROJECTION: Pitchers -1.97|Position Players +5.63|Total +3.66|ExpW-L 84.66 - 77.33

Wooooooooooooooooooooooooooo!

http://www.beyondtheboxscore.com/2008/11/25/670594/brewers-sign-r-j-swindle

Says everything I would say about this and more.

And better.

Pitching Projections

Here's part two of last week's post on projections.

This uses the 2009 Marcel's to project Brewers pitching, once again using only players the Brewers have currently locked down. It's possible that I may have missed somebody that would likely make the roster if the season started today, so please point that out if I missed it.

Notes: I required 1458 (162 g * 9 IP/g) as the total number of IP required overall.
I required 863.67 IP by starters (~5.33 IP/g) and 594.33 IP by relievers (~3.67 IP/g).

FIP = (13*HR + 3*BB - 2*K)/IP + 3.33 (difference between avg NL FIP and avg NL ERA)

Again, 10.5 R/Win.

AVG ERA = AVG FIP = 4.41

Starters = Gallardo, Capuano, McClung, Suppan, Bush
Relievers = Others

And without further ado, the numbers.

nameLast	IP	ERA	HR	K	BB	FIP	FIPRAA	ERARAA	FIPWAA	ERAWAA
Gallardo	79	3.65	7	70	28	3.77	5.59	6.67	0.53	0.64
Capuano	72	4.5	9	60	24	4.29	0.97	-0.72	0.09	-0.07
Stetter	38	4.03	4	33	18	4.38	0.12	1.6	0.01	0.15
Villanueva	96	4.03	13	82	34	4.44	-0.37	4.05	-0.04	0.39
Bush	169	4.31	23	118	45	4.5	-1.72	1.88	-0.16	0.18
McClung	89	4.35	9	70	44	4.55	-1.43	0.59	-0.14	0.06
DiFelice	35	4.37	5	28	12	4.62	-0.8	0.16	-0.08	0.02
Dillard	32	4.22	4	23	12	4.64	-0.83	0.68	-0.08	0.06
Coffey	43	4.81	6	33	16	4.73	-1.51	-1.91	-0.14	-0.18
Riske	53	4.25	7	39	23	4.88	-2.75	0.94	-0.26	0.09
Suppan	169	4.85	21	98	63	4.9	-9.28	-8.26	-0.88	-0.79
Replacement SP	285.33	5.5	-	-	-	5.5	-34.56	-34.56	-3.29	-3.29
Replacement RP	297.67	5	-	-	-	5	-19.51	-19.51	-1.86	-1.86
TOTALS	1458	-	-	-	-	-	-66.07	-48.39	-6.29	-4.61
Gallardo/Capuano 160 IP each	-	-	-	-	-	-	-	-	-	-
Gallardo	160	3.65	14.18	141.77	56.71	3.77	11.32	13.51	1.08	1.29
Capuano	160	4.5	18.23	121.52	48.61	4.29	1.97	-1.46	0.19	-0.14
Replacement SP	116.33	5.5				5.5	-14.09	-14.09	-1.34	-1.34
Replacement RP	297.67	5	-	-	-	5	-19.51	-19.51	-1.86	-1.86
TOTALS	1458	-	-	-	-	-	-38.87	-21.82	-3.7	-2.08
+McClung 160 IP
McClung	160	4.35	16.18	125.84	79.1	4.55	-2.57	1.07	-0.25	0.1
Replacement SP	45.33	5.5	-	-	-	5.5	-5.49	-5.49	-0.52	-0.52
Replacement RP	297.67	5	-	-	-	5	-19.51	-19.51	-1.86	-1.86
TOTALS	1458	-	-	-	-	-	-31.42	-12.74	-2.99	-1.21
+FREE AGENT SIGNINGS											$ (millions)	M$/FIPWAR
Swindle (Projections from CAIRO)	49	2.79	4	45	8	3.02	7.57	8.82	0.72	0.84	0.4	.147
Replacement SP	45.33	5.5	-	-	-	5.5	-5.49	-5.49	-0.52	-0.52
Replacement RP	248.67	5	-	-	-	5	-16.3	-16.3	-1.55	-0.15
TOTALS	1458	-	-	-	-	-	-20.63	-0.72	-1.97	1.34	0.4	0.147

Well, this doesn't look very good for Brewers fans. Using the pure mIP numbers from the Marcel's, the Brewers staff looks about 6.2 wins below average using FIP numbers (which I prefer, because I already ran fielding projections, and because FIP is more talent-based) and 4.5 below average using ERA. However, let's be optimistic and assume we can get starter-type innings out of Capuano, McClung, and Gallardo. With a minimal assumption of 160 innings for each of those pitchers, we're looking a little better, at -3 wins and -1 wins for FIP and ERA respectively.

Clearly, Melvin needs to go out there and get pitching, both in the bullpen and in the rotation. Anything to get experienced, non-replacement innings will greatly help this team. If the offense performs up to par, another 5 wins out of the pitching (which comes out to about 25 million on the free agent market, less than that if you can find bargains) would put this team at +7.5 WAA, or an 89 win team. If the team is willing to spend 40 or 50 million, we could be looking at a +12.5 WAA, or 93+ win team.

With the team we have right now, I'm not optimistic. But if the front office can find a few diamonds in the rough in the FA pool and minor leagues, as well as make a splash in the big name free agent market, the Brewers could very well be a contender again.

A Bare Bones Projection Of Brewers Hitters In 2009

The 2009 Marcel's are out, and I coupled them with Sean Smith's 2009 defensive projections to make a bare bones projection of Brewers hitters for the 09 season.

This assumes no signings of anybody at all, so obviously this is only to be seen as a starting point, and also to see where the Brewers holes are.

Important notes: I required each position to receive 700 plate appearances between all players and replacements.

Thus, 700/162 = 4.33 = PA/G, which is how I found expected games.

Rel = Reliability, which is based on the number of plate appearances Marcel had to work with. That's why it's low for players like Gamel and Gwynn and high for players like Cameron and Hart.

xG = Expected games.

The m before some columns represents the fact that they're from the Marcel projections.

Obviously this isn't perfect but like I said, this is a very simple projection.

EDIT: I had a formatting error in my spreadsheet, which rounded down all the wOBA values, which lowered both each player's wOBA AND the average wOBA. This results in a slightly lower WAA, but not a whole lot of difference overall.

PLAYER	POS	REL.	mPA	wOBA	RAA	WAA	WAR	xG	G/POS	DefRAA	PosAdj	DefWAA	TotalWAA
Gwynn, Tony	OF	0.46	238	0.306	-4.14	-0.39	0.24	55.09	39 CF 13 RF	-2.95	0.8	-0.2	-0.6
Gamel, Mat	3B	0.01	201	0.344	3.15	0.3	0.84	46.53	46 3B	0	0	0	0.3
Nelson ,Brad	1B	0.03	204	0.338	2.13	0.2	0.75	47.22	20 1B 27 PH	0	-2.22	-0.21	-0.01
Rivera ,Mike	C	0.42	236	0.329	0.62	0.06	0.69	54.63	36 C 18 PH	0	1.67	0.16	0.22
Hall, Bill	3B	0.84	474	0.325	-0.41	-0.04	1.22	109.72	110 3B	-0.68	0	-0.06	-0.1
Cameron, Mike	CF	0.85	519	0.333	3.16	0.3	1.68	120.14	120 CF	2.24	3.46	0.54	0.84
Weeks, Rickie	2B	0.83	531	0.343	7.85	0.75	2.16	122.92	122 2B	-6.84	0	-0.65	0.1
Kendall, Jason	C	0.85	545	0.295	-14.69	-1.4	0.05	126.16	126 C	10	7.25	1.64	0.24
Hardy, J.J.	SS	0.84	578	0.344	9.05	0.86	2.4	133.8	134 SS	0.83	3.86	0.45	1.31
Fielder, Prince	1B	0.87	615	0.382	29.95	2.85	4.49	142.36	142 1B	-7.09	-8.21	-1.46	1.39
Braun, Ryan	LF	0.81	581	0.384	29.3	2.79	4.34	134.49	134 LF	1.67	-3.86	-0.21	2.58
Hart, Corey	RF	0.84	585	0.345	9.67	0.92	2.48	135.42	135 RF	1.68	-3.89	-0.21	0.71
Replacement	C	-	0	-	-	0	0	-	0 C	0	0	0	0
Replacement	1B	-	0	-	-	0	0	-	0 C	0	0	0	0
Replacement	2B	-	169	-	-	-0.45	0	-	40 2B	0	0	0	-0.45
Replacement	3B	-	25	-	-	-0.07	0	-	6 3B	0	0	0	-0.07
Replacement	SS	-	122	-	-	-0.33	0	-	28 SS	0	0.86	0.08	-0.24
Replacement	LF	-	119	-	-	-0.32	0	-	28 LF	0	-0.86	-0.08	-0.4
Replacement	CF	-	0	-	-	0	0	-	0 CF	0	0	0	0
Replacement	RF	-	58	-	-	-0.15	0	-	14 RF	0	-0.43	-0.04	-0.2
Totals	-	-	-	-	-	5.89	21.35	-	162 ALL	-1.14	-1.57	-0.26	5.63
												'

No giant surprises here. The Brewer position players project as between 5 and 6 wins above average, with this being a conservative estimate due to Marcel's conservative estimates of playing time. The Brewer offense is basically back in full force, although clearly a backup outfielder or 2 would be useful over the off-season (Gwynn really doesn't seem to be worth much outside of a pinch-runner, as his outfield defense is far below average in center and average in the corners). Pitching projections will come in the next few days, and that's where it should get interesting.

What have the Brewers lost in Salomon Torres?

At the surface, it seems like the Brewers have lost quite a bit. Torres saved 28 games for the Brewers with a 3.49 ERA and gave at least a little bit of stabilization to the later innings (although not a whole lot, as any Brewer fan can attest to) after the failure of the Eric Gagne Project. Torres retired last week, and this leaves the Brewer bullpen slightly naked at the back end. But really, did Torres have that great of a season? How many runs did he really save for the Brewers?

NOTE: Torres retired last week, but the Brewers picked up his '09 option, so if Torres decides to come back, he will remain a Brewer.



Let's take a look at a stat called tRA, from Statcorner.com (check their glossary for this and more great stats) . tRA is a stat that is based on purely things that pitchers can control (walks, strikeouts, home run rates, etc., things that the defense doesn't effect) that is then normalized to the ERA scale.

Torres pitched 77.3 innings with a 4.63 tRA this year. Torres' controllable skills show that he was quite lucky to post such a high ERA. Much of this can be attributed to the Brewers defense, which was very good and by some metrics the best in the NL.

Let's convert this tRA and IP score into a number of runs saved above a replacement reliever (basically, any scrub from AAA, like, say Tim Dillard, who had a 5.99 tRA in his 14 IP with the Brewers this season). The formula for finding total runs saved above replacement is as follows:

EDIT: Turns out I was using the wrong value here. Should be 5.00 because we're looking at relievers.

(5.00 - (tRA))*IP/9.

Torres saved 3.22 runs above replacement (RAR) He definitely helped the bullpen. But let's compare him to some other relievers. Some other Brewers, some FAs, and some closers from around the league.

A couple Brewers:
Brian Shouse: 3.99 RAR
Carlos Villanueva (only as a RP): 11.53
(just for laughs)
Eric Gagne: -9.65 (and somehow, this guy is a type B free agent)

A few FA closers:
Francisco Rodriguez: 10.45
Brian Fuentes: 21.11
Kerry Wood: 20.97

And some other FAs, that some might classify as "F.A.T"
This doesn't mean Prince Fielder fat, but Freely Available Talent. Some of this depends on "Freely," because some of these guys are type B free agents, but either way, you might be able to get similar production to top-tier guys like K-Rod for far, far less money.

Jeremy Affeldt: 11.44 (previous contract 3M/yr)
Will Ohman: 8.94 (previous contract: 1.8M/yr)

And this guy is still the best reliever in baseball, even though everybody seems to have forgotten:

Mariano Rivera: 30.26

However, a big part of relieving has been ignored in this analysis. Closers, such as K-Rod and Wood and Fuentes pitch in more important situations, on average, than 6th or 7th inning guys like Villanueva and Ohman. So let's take that into account. Fangraphs keeps track of pLI, or the average leverage index for each reliever. Let's multiply the runs saved above average by pLI in order to take a look at a little truer number of runs saved. Also, let's look at their runs saved multiplied by 1.93, the average closer pLI (with closer defined as any reliever with 20+ saves in 2008).

For some reason, I can't seem to get rid of all these spaces so you'll have to scroll down a bit for the table.

EDIT: Fixed it!

PITCHER	tRA	IP	RSAR	pLI	RSAR*pLI	RSAR*1.93	WAR (normal)	WAR (pLI)	WAR (1.93)
Torres	4.63	78.3	3.22	2	6.44	6.21	0.32	0.64	0.62
Shouse	4.3	51.3	3.99	1.08	4.31	7.7	0.4	0.43	0.77
Villanueva	3.25	59.3	11.53	1.09	12.57	22.25	1.15	1.26	2.23
Gagne	6.9	45.7	-9.65	1.72	-16.59	-18.62	-0.96	-1.66	-1.86
Rodriguez	3.59	66.7	10.45	2.54	26.54	20.17	1.04	2.65	2.02
Fuentes	1.97	62.7	21.11	2.01	42.43	40.74	2.11	4.24	4.07
Wood	2.11	65.3	20.97	1.99	41.73	40.47	2.1	4.17	4.05
Affeldt	3.68	78	11.44	0.56	6.41	22.08	1.14	0.64	2.21
Ohman	3.63	58.7	8.94	0.88	7.86	17.25	0.89	0.79	1.72
Rivera	1.11	70	30.26	1.92	58.09	58.39	3.03	5.81	5.84

This shows us some pretty interesting things. First of all, Mariano Rivera is amazing. 5.84 wins above replacement at closer. Second of all, if guys like Jeremy Affeldt or Carlos Villanueva could maintain the type of raw production they get in the roles they have now, they could be very effective closers, at the level of a guy like Francisco Rodriguez.

Of course, this has to be taken with a grain of salt. We don't know if these players will thrive if thrust into a closer role, and it's possible that in these lower leverage situations that they aren't facing the same quality of hitters that closers are. But it does tell us that managers CAN use them better than they are being used, and that you don't necessarily have to spend 10 million dollars to get a guy that's a couple wins above replacement (or, in the Brewers case, -.882 WAR), and that Brewers GM Doug Melvin may have plenty of options available to bolster the bullpen with besides expensive guys like Wood and Fuentes.

Brewers Exercise Option on CF Cameron

GM Doug Melvin and crew finally exercised the 10M club option on Mike Cameron. The Brewers CF, in limited action due to a 25-game stimulant-related suspension (120 G, 508 PA), Cameron put up a .243/.331/.477 slash line, along with 25 HRs and 70 RBIs. These numbers (especially the .243 avg) may lead many casual fans to wonder why a small market team like the Brewers would be willing to spend 10 million dollars on a hitter of this caliber.

First off, Cameron's numbers where quite good among CFs this year. Cameron's .809 OPS ranked 30th among qualifying OFs, and when the sample is reduced to CFs, it ranks 7th among OF (and 3rd among NL CFs), only 1 point behind Torii Hunter's .810 OPS. However, Cameron's OPS is slightly misleading, because of his low OBP, he's not quite worth as much offensively as his OPS would suggest. For a better look, Cameron's WPA/LI this year was 1.42, meaning that Cameron, in reduced time, was still worth 1.42 wins above the average ML hitter.

However, anybody who watched the Brewers play over the course of the season knows that Cameron is also a fine defensive player, and we cannot ignore this contribution of the player. This is a major concern for the Brewers, who are losing 1 if not 2 aces this year in Ben Sheets and CC Sabathia. This means that the Brewers will have to rely on solid gloves (even moreso than last season, where they lead the NL in +/-) and not ace pitching in order to keep a solid run prevention.

Let's take a look at Justin's TotalValue Stats, a set of stats that uses Linear Weights for offense and Zone Ratings on defense to determine the total number of runs above (or below) replacement a player was over the 2008 season. Justin has Cameron at 26 runs above replacement (+23 runs offensively, +3 runs defensively), which, using a crude 10 runs = 1 win scale, puts Cameron at 2.6 wins above replacement. The current free agent market has a +1 win player going for somewhere in the range of 4.5 to 5 million dollars/year.

Even if we assume some sort of decline for Cameron (who will be 36 next year), the fact that he will likely accrue 100 more plate appearances and 20 more games in CF will be of enough value to the Brewers that it is fair to expect a similar performance next year. Cameron's BABIP was slightly lower than his career average (.300 vs .307), so no major regression either way should be expected there. Cameron's HR/FB rate was way up this year, 18.9% compared to 13.8%. While Cameron's career HR/FB is lowered by spending much of his career in pitcher's parks like Petco Park and Safeco Field, Miller Park also had a low HR park factor this year as well, so regression can be expected for his HR/FB rate.

Basically, the Brewers can expect to have a decent, +1.5 to +2.5 win hitter combined with a +.5 to +1.5 win outfielder, which is a great bargain at 10 million dollars for only one year. Also, if Cameron performs similarly to last year, he may reach the Type A free agent tier, netting the Brewers more draft picks on top of the picks they'll get if/when Sabathia, Sheets (both type A), Shouse, Gagne, and Torres (all type B) leave this year. Melvin made a genius deal last year, and I'm surprised it took the Brewers this long to realize that it will bring nothing but good things to the club once again.

From MLB.com: Nationals targeting slugger to clean up

They may have gone so far as to put a classified ad in the Washington Post!

A Lesson on Lineup Optimization, With Help From Everybody's Favorite 16-Bit Baseball Simulator

Lineup optimization is a topic that is on the minds of many managers, gms, and coaches at any level of baseball (and really any sport). In baseball, lineup optimization can be reduced to a statistical science, thanks to the ridiculous amount of data provided by 30 teams playing 162 game every year for the last 105 years (staying in the World Series era). I would like to take some time to explain a few of the findings found by some researchers through the example of one of my favorite video games of all time, Ken Griffey Jr. Presents Major League Baseball for SNES.




START

All data on lineup optimization is taken from The Book, by Tom Tango, Mitchell Lichtman, and Andrew Dolphin.

Today, we'll be looking at the lineup of my favorite team, the Milwaukee Brewers. One of the quirks of Ken Griffey Jr. Presents Major League Baseball is the use of fake names for all the players. This is because of the fact that Nintendo did not acquire the MLBPA license for this game, and thus could not use any names (other than that of Griffey Jr.'s). This will be interesting, because after the lineup is optimized, I will go back and replace the fake names with the real ones and we can compare stats using lineup optimization tools on the web. Rosters are from the 1993 season. Also, note that the Brewers are still in the AL at this time, and so they still use the DH.

Let's take a look at the current lineup.

FORMAT:
NAME AVG/HR/RBI "BAT/POW/SPD/DEF"

Bat = Contact rating, Pow = power, SPD = speed, DEF = defense (basically arm)

RF J. DRAKE .310/9/48 9/4/10/8
CF S. TEMPLAR .258/8/51 7/4/7/9
3B N. SOLO .274/7/79 8/4/5/6
LF J. STEED .267/30/97 7/9/5/6
DH E. PEEL .249/13/60 5/7/4/3
1B K. GALE .264/19/70 6/7/5/5
CA J. BOND .257/7/40 6/4/4/7
SS J. ROCKFORD.244/3/30 5/4/9/8
2B P. MARLOWE .238/2/36 5/4/5/6
BENCH
CA G. IRONSIDE.198/4/25 4/6/5/5
IF S. SLADE .228/5/36 4/4/5/8
IF T. PRISONER.269/11/57 7/7/4/6
IF P. COLUMBO .269/1/33 7/3/5/5
OF R. STEEL .183/6/29 3/8/4/6
IF P. MAGNUM .319/0/1 7/2/6/8

So that's what we have to work with here. Clearly not a whole lot, only one 20+ HR hitter, only 4 10+. Not a whole lot of team speed either, with only two players with above an "8" rating in speed (basically the cutoff needed to beat out any infield hit against a half decent defense). Now that we have our team, we need to think about what we want in our batting order. Here are some points that we should consider

1. The best hitters should bat the most times.
2. The best hitters should bat the most often with men on base.
3. The worst hitters should bat the least times.

That's the simple way to look at it. Point 2 is often why the best hitter is placed in the #3 order in the lineup. However, statistical analysis of MLB over multiple seasons show that this does not give the most leverage to the best hitter. This sounds odd, because you would expect that the #3 hitter would often expect to have runners on base in front of him and the ability to drive them in. However, when you realize that even the league leaders in OBP are rarely above .450 and almost never above .500 (except for one Barry Bonds), the chances are actually very high that the #3 hitter will bat with nobody on base and 2 outs in the first inning, a very low leverage situation. This is why it is better to have the best hitter in the #4 spot, where they are either batting with runners on base in front of them or leading off an inning, another relatively high leverage situation. According to The Book, in order to maximize leverage for a lineup
Your three best hitters should bat somewhere in the #1, #2, and #4 slots. Your fourth- and fifth-best hitters should occupy the #3 and #5 slots. The #1 and #2 slots will have players with more walks than those in the #4 and #5 slots. From slot #6 through #9, put the players in descending order of quality

OK, so now we have to decide how we will measure hitter quality. Simply using BAT + POW + (SPD/5) would give a simple measurement (since speed is relatively indeterminate in a hitters contribution but should not be ignored) would work well, but through personal experience in this game I know that a BAT 5 POW 5 player would be much better than a BAT 9 POW 1 player. This makes sense in the real world of baseball given that players like Adam Dunn and Jack Cust are far more productive than guys like, say, David Eckstein who are known as "contact" hitters but can barely hit the ball out of the infield. However, in this game there is a bit of relation of contact to power, so we can't let POW completely outweigh BAT. I suggest

BAT + 1.33POW + .2SPD + .5DEF

Defense is also quite important, especially in a video game in which the players are much smaller than they are in real life relative to the field and thus have to cover much more ground.

So using this equation, we get the following ranks:

RF J. DRAKE 16.32 20.32
CF S. TEMPLAR 13.72 18.22
3B N. SOLO 14.32 17.32
LF J. STEED 19.97 22.97
DH E. PEEL 15.11 16.61
1B K. GALE 16.31 18.81
CA J. BOND 12.12 15.62
SS J. ROCKFORD12.12 16.12
2B P. MARLOWE 11.32 14.32
BENCH
CA G. IRONSIDE12.98 15.48
IF S. SLADE 10.32 14.32
IF T. PRISONER17.11 20.11
IF P. COLUMBO 11.99 14.49
OF R. STEEL 14.44 17.44
IF P. MAGNUM 10.86 14.86

Now, let's make a lineup. In the first column is pure hitting value. In the second column, defensive value is included. Because defense is regardless of position in this game, we are free to take simply the top 9 overall values. This gives us the following 9:
LF J. STEED 19.97 22.97
RF J. DRAKE 16.32 20.32
IF T. PRISONER17.11 20.11
1B K. GALE 16.31 18.81
CF S. TEMPLAR 13.72 18.22
OF R. STEEL 14.44 17.44
3B N. SOLO 14.32 17.32
DH E. PEEL 15.11 16.61
SS J. ROCKFORD12.12 16.12

First, we need our top 3 batters. They are Steed (19.97), Prisoner (16.32), and Drake (16.32). In order to decide who goes at 1, 2, and 4, let's look at the value of the HR at each position. The average run value of the HR at the 1, 2, and 4 spot respectively is
1.291, 1.349, and 1.436. Therefore, power among these 3 hitters should increase. That means that Drake will leadoff (4 POW), Prisoner will bat 2nd (7 POW), and Steed will cleanup (9 POW).
Now we need the next two best hitters. They are Gale and Peel. Because these two hitters have equal POW numbers, the better BAT player will go in the 5 spot because the average run value of the single, double, and triple are slightly higher. So Gale will bat 5 (6 BAT) and Peel will bat 3 (5 BAT). After that, we merely go in descending order. So #6 is Steel, 7 is Solo, 8 is Templar, and 9 is Rockford. Here is the lineup, along with the real person they correspond to along with their OPS+ for the 93 season.

1. J. DRAKE = Darryl Hamilton 109
2. T. PRISONER = Kevin Seitzer 119
3. E. PEEL = Kevin Reimer 87
4. J. STEED = Greg Vaughn 128
5. K. GALE = John Jaha 103
6. R. STEEL = Tom Brunansky 58
7. N. SOLO = B.J. Surhoff 91
8. S. TEMPLAR = Robin Yount 90
9. J. ROCKFORD = Pat Listach 73

It would appear that I weighted POW slightly high, but this still worked pretty well overall. Since Brunansky appears to be an outlier, let's replace him with the next highest total value on the list, which would be J. BOND, or Dave Nilsson, who had a 93 OPS+, but has the lowest offensive value, so he'll bat 9th and everybody under him will move up. So our final lineup is:

1. J. DRAKE = Darryl Hamilton 109
2. T. PRISONER = Kevin Seitzer 119
3. E. PEEL = Kevin Reimer 87
4. J. STEED = Greg Vaughn 128
5. K. GALE = John Jaha 103
6. N. SOLO = B.J. Surhoff 91
7. S. TEMPLAR = Robin Yount 90
8. J. ROCKFORD = Pat Listach 73
9. J. BOND = Dave Nilsson 93

Finally, let's take a look at the expected runs/game for both the original lineup and the final lineup, using the lineup analysis tool at http://www.baseballmusings.com/cgi-bin/LineupAnalysis.py

Original lineup: 4.436 runs/game
Final lineup: 4.632 runs/game

So we've added .196 runs/game, which over the course of a 162 game season, adds 31.752 runs. At 10 runs/win, that adds a total of 3 wins to our total! That could very well be the difference between making or missing the playoffs, so we should be very happy with our results!

Now wasn't that fun?

Addendum: The people on Jim Rome's show also have no idea what they're talking about.

Mike Sando (or whatever his name is) needs to shut up. Long swings don't hit home runs. Did any of these guys actually play the game? Have they ever really watched a game? Hitting the ball to the right side to score a run either reduces win probability or is a wash. Your goal, as a hitter, with a runner on third base is not the ground ball to the right side that scores a run. The goal is a hit. That runner from third, with less than two outs, is going to score a high enough percentage of the time that the groundout, in most situations either does not effect win probability or

Check out the game log from last night.

B Myers	C Pena	1	0	_23	1-0	Carlos Pena grounded out to shortstop (Grounder). Akinori Iwamura scored. B.J. Upton advanced to 3B.	1.38	1.99	68.9 %		.005	-0.05
B Myers	E Longoria	1	1	__3	2-0	Evan Longoria grounded out to shortstop (Grounder). B.J. Upton scored.	1.21	0.94	70.9 %		.021	0.16

Those are the two plays from the first inning in which the Rays scored on groundouts. Total WPA is .026. This means that these two plays, combined, added a 2.6% chance to the Rays win probability. Really, the play that actually mattered this inning was here.

B Myers

B Upton

1

0

1__

0-0

B.J. Upton singled to right (Liner). Akinori Iwamura advanced to 3B on error. B.J. Upton advanced to 2B. Error by Jayson Werth.

1.42

0.88

68.4 %

.101

1.10

This play was essentially a double, although it was poorly played by Werth in RF. For all intents and purposes of win probability, it was a double. The play had a WPA of .101, meaning it added 10.1% to the Rays chances of winning. Basically, BJ Upton did all the working in making it so that those undesirable groundouts following him had slightly positive results. "Big Ball" will always beat "Small Ball," and don't let people like Rome and Sando let you think otherwise.



Also people are making a big deal about this play:

B Myers

J Bartlett

4

1

1_3

4-0

Jason Bartlett sacrificed to pitcher (Bunt Grounder). Cliff Floyd scored. Rocco Baldelli advanced to 2B.

0.87

1.19

91.1 %

.016

0.14

Again, WPA is only .016. This play made the Rays 1.6% more likely to win this game. The only reason that this is a marginally good play, in my eyes, is that Jason Bartlett can't hit his way out of a wet paper bag. The thing is, with a 3 run lead, adding one extra run doesn't make a big difference. You want to pile on the runs and create a legitimate rally, and while the bunt scores the run, it's a complete rally killer, whereas letting Bartlett swing away has a very high chance of the run scoring anyway, whether it's on his at bat or the at bats following his.

Once again, Jim Rome has no idea what he's talking about.

Don't get me wrong, I'm a big fan of Jim Rome. He's funny, and occasionally smart, and almost always entertaining. But this time, he's just plain wrong.

Basically, Rome summed up Game 2 of the World Series by saying that the Rays are "built to do it to you with pitching, speed, and defense," and more to the point, that "they don't beat you with the long ball."

Why don't you ask the White Sox and the Red Sox whether or not the Rays beat you with the long ball? Of course, just looking at those 11 playoff games in which the Rays hit 22 home runs (2 HR/g) gives us a ridiculously small sample size. Sure, the Rays 180 team homers isn't quite as great as the 235 put up by the White Sox or even the 214 put up by World Series opponent Phillies,
but it still amounts to 1.125 HR/g and came in 4th in the American League.

No team in major league baseball can sustain winning ways without consistent power production. It simply can't happen. The Angels found that out in a bad way when their ridiculous, unsustainable clutch hitting over the regular season fizzled against the Red Sox. The Rays will not win this series if their bats don't show up and show up soon, because against a team with as much power hitting as the Phillies, they will need to be able to score runs in bunches. If Joe Maddon decides to play "small ball" as sportscasters such as Jim Rome seem to suggest, they will be running themselves into the ground by not giving their power hitters the chances that they need.

Inside the mind of a statistically-inclined baseball aficionado.

I love baseball. I'm never happier than when I'm around a baseball field. I've played organized baseball since I was 5 and probably was introduced to the game much earlier than that. I've never been the most talented player on any team I've played on, but I've never let that deter my interest for the game. I currently play for the University of Wisconsin Club Baseball B team, and I play first base and right field.

I follow Major League Baseball intensely, and I am a big fan of the Milwaukee Brewers, but even when they're not playing, I always find something in the game to hold my interest. I now enjoy playing Fantasy Baseball, as well as watching any MLB game that happens to be on the TV. When I first got into Fantasy Baseball, 5 years ago, I was introduced to such crazy stats as "OPS" and "WHIP." At first, I was skeptical. I first thought that these stats were de-humanizing the game and that the game was random enough and based enough on things like "heart" that those stats couldn't possibly mean any more than your typical stats like batting average, and that the most valuable player was simply the one who hit the most home runs or had the highest batting average.

However, after aging a bit and learning much much more about statistics and mathematics, I've come to understand and love these statistics. If you're a skeptic like I used to be, I have two publications that I heartily recommend. First, check out the following website: www.fangraphs.com - this website has projections for every player and also a very cool scoreboard feature which shows the win probability of each team based on run expectancies and other crazy things. To learn more about that, check out my second suggested reading: The Book. To get a sneak peek before you invest, check out www.insidethebook.com - this book uses intense mathematical and statistical analysis to show what strategies and outcomes are better and simply shows the best way for a GM or manager to optimize his team.

Expect a lot of posts here talking about either my own personal baseball experiences, both as a coach and a player, as well as about the MLB and the MLB media. I can't wait to tear the people offering the MVP award to Ryan Howard a new one.