Hank Greenberg vs. The Yankees

I got interested in this recently when David Ortiz became the sixth player to hit 50+ career HRs vs. the Yankees. It turns out that Greenberg is the only one of the six who never played for the Red Sox (Hat tip to Ryan Pollack for that info). Also, if anyone asks who hit the most career HRs by a guy who attended NYU, Greenberg is the answer.

Greenberg hit 331 career HRs and 1/7 of those would be 47.29. He had 53 against the Yankees. So a bit more than you would expect. The Yankees allowed a HR% of 1.52% over the years 1933-46 (he was in the military from 42-44 and good chunks of 41 & 45 so this is not quite right, but I hope it is close). The league average was 1.56%. So the Yankees were about average in terms of allowing HRs. Also, the Yankees and Tigers were just about tied for the lowest SLG allowed in the AL over these years, .351 (Tigers were 0.00064 lower-what teams allowed is in a table at the end of the post). They Yankees allowed the lowest average of .254. So against what might have been the best pitching staff of these years in the AL, Greenberg upped his game. Of course, the Yankee fielders might have helped.

He had a career HR% of 6.37% but against the Yankees it was 7.26%. So he did especially well against them. Here are his AVG-OBP-SLG against them: .333-.409-.667. His whole career was .313-.412-.605 (if we take out 1947, his year in the NL, they were .319-.412-.616). So he really hit alot better against them than other teams (probably walked less frequently)

In Yankee Stadium he had .319-.375-.608. Pretty good for a righty with that death valley they had, over 400 to left center. His HR% there was 5.45%. He probably had an SLG of over .700 against them at Tiger Stadium.

Why did he hit so well against them? Was it because he was from New York? Who knows.

Here are the top 25 guys in SLG vs. the Yankees since 1913 with 250+ PAs (from the Baseball Reference Play Index). SLGtot is their career SLG. Then the difference between their career SLG and what they did against the Yankees. Then how many PAs vs. the Yankees along with their BA and OBP.

Rk	Player	SLGvNY	SLGtot	Diff	PA	BA	OBP
1	Hank Greenberg	0.667	0.615	0.052	826	0.333	0.409
2	Miguel Cabrera	0.665	0.570	0.095	255	0.335	0.412
3	Alex Rodriguez	0.651	0.581	0.070	374	0.334	0.386
4	Manny Ramirez	0.617	0.589	0.028	861	0.322	0.413
5	Albert Belle	0.611	0.564	0.047	503	0.301	0.366
6	Ted Williams	0.608	0.633	-0.025	1351	0.345	0.495
7	Ken Griffey	0.595	0.549	0.046	572	0.311	0.392
8	Curt Blefary	0.592	0.410	0.182	257	0.313	0.414
9	Jim Rice	0.582	0.506	0.076	714	0.330	0.387
10	Mike Napoli	0.580	0.482	0.098	299	0.300	0.418
11	Rafael Palmeiro	0.579	0.519	0.060	820	0.311	0.396
12	Jay Buhner	0.578	0.496	0.082	409	0.283	0.379
13	Jimmie Foxx	0.577	0.616	-0.039	1260	0.303	0.400
14	Jose Bautista	0.576	0.509	0.067	425	0.253	0.402
15	David Ortiz	0.576	0.550	0.026	1003	0.307	0.395
16	Mo Vaughn	0.569	0.526	0.043	484	0.285	0.380
17	Nomar Garciaparra	0.556	0.544	0.012	404	0.326	0.360
18	Ramon Hernandez	0.553	0.420	0.133	300	0.333	0.403
19	Paul Konerko	0.551	0.491	0.060	443	0.306	0.378
20	Ken Williams	0.544	0.543	0.001	763	0.303	0.380
21	Edgar Martinez	0.542	0.516	0.026	594	0.317	0.423
22	Larry Parrish	0.542	0.453	0.089	314	0.301	0.354
23	Magglio Ordonez	0.541	0.502	0.039	407	0.301	0.369
24	Rusty Staub	0.541	0.437	0.104	255	0.320	0.369
25	Earl Averill	0.540	0.535	0.005	1070	0.323	0.395

It was not until the 1990s and 2000s that anyone came close to what Greenberg did (Rodriguez and Cabrerra). Tiger's pitcher Frank Lary (from the 1950s and 60s) was called "The Yankee Killer." But maybe Greenberg should have had that nickname.

Here are the top 10 in terms of how much better they did against the Yankees

Rk	Player	SLGvNY	SLGtot	Diff	PA
1	Curt Blefary	0.592	0.410	0.182	257
2	Jim Spencer	0.516	0.379	0.137	335
3	Ramon Hernandez	0.553	0.420	0.133	300
4	Ernie Whitt	0.530	0.418	0.112	274
5	Rusty Staub	0.541	0.437	0.104	255
6	Jonny Gomes	0.531	0.428	0.103	290
7	Mike Napoli	0.580	0.482	0.098	299
8	Miguel Cabrera	0.665	0.570	0.095	255
9	Larry Parrish	0.542	0.453	0.089	314
10	Dick Wakefield	0.530	0.447	0.083	349

Now those leaders with 400+ PAs

Rk	Player	SLGvNY	SLGtot	Diff	PA
1	Jay Buhner	0.578	0.496	0.082	409
2	Ruben Sierra	0.529	0.453	0.076	531
3	Jim Rice	0.582	0.506	0.076	714
4	Jose Bautista	0.576	0.509	0.067	425
5	Paul Konerko	0.551	0.491	0.060	443
6	Rafael Palmeiro	0.579	0.519	0.060	820
7	Chili Davis	0.526	0.471	0.055	476
8	Charlie Maxwell	0.505	0.452	0.053	549
9	Hank Greenberg	0.667	0.615	0.052	826
10	Vernon Wells	0.516	0.467	0.049	730

Here are all the right-handed batters with a .500+ SLG and 200+ career PAs in Yankee Stadium (I think this includes only the original park but both before and after the renovations of the 1970s when LF center was brought in from like 450 to 400 or so). Again, Greenberg is up there and no one passed him until Jim Rice in the 1970s and 80s, after the wall got closer.

Rk	Player	SLG	PA
1	Jim Rice	0.661	308
2	Albert Belle	0.645	258
3	Jay Buhner	0.623	235
4	Hank Greenberg	0.608	421
5	Manny Ramirez	0.605	440
6	Alex Rodriguez	0.597	1878
7	Mike Stanley	0.560	877
8	Harry Heilmann	0.557	315
9	Joe DiMaggio	0.547	3789
10	Edgar Martinez	0.545	303
11	Gary Sheffield	0.532	856
12	Al Simmons	0.532	646
13	Red Kress	0.520	439
14	Mariano Duncan	0.509	247
15	Ben Paschal	0.506	389
16	Shane Spencer	0.506	570
17	Roy Sievers	0.503	426

Here is what each AL team allowed opposing hitters from the years 1933-46. The league averages were BA .270, OBP .342, SLG .368

Team	BA	OBP	SLG	OPS
DET	0.263	0.335	0.351	0.686
NYY	0.254	0.325	0.351	0.676
CLE	0.265	0.339	0.359	0.699
BOS	0.271	0.344	0.365	0.709
WSH	0.273	0.344	0.365	0.709
CHW	0.269	0.336	0.371	0.706
SLB	0.285	0.357	0.386	0.743
PHA	0.278	0.353	0.397	0.750

Is Mike Trout Mickey Mantle Reborn?

Tim Kurkjian said he was on ESPN this week (or something like that). Trout, like Mantle, has both great speed and power to go along with a high OBP. Let's look at the record of each of these players through age 24

First Mantle

Mantle/Age	PA	OPS+	WAR
19	386	117	1.4
20	626	162	6.5
21	540	144	5.3
22	649	158	6.9
23	638	180	9.5
24	652	210	11.2
Age 19-23 Totals	2839	155	29.6

Now Trout

Trout/Age	PA	OPS+	WAR
19	135	89	0.7
20	639	168	10.8
21	716	179	9.3
22	705	168	7.9
23	682	175	9.4
24	120	183	1.9
Age 19-23 Totals	2877	169	38.1

Trout has better numbers thru age 23. Mantle's highest OPS+ was 180 while Trout's was 179. But Trout's next best was 175 while Mantle's was 162. Trout has a big edge in career OPS. That might be misleading since Mantle had many more PAs at age 19, and we would not expect too much from a player so young. That might depress Mantle's averages.

If we look at ages 20-23, Trout leads in OPS+, 173-162. So he still has a solid edge in hitting.

But at age 24, Mantle won the triple crown and had an OPS+ of 210. Trout is 24 this year and he is at 183 so far. To finish with 210 this year, he would need to be close to 220 the rest of the season.

Mantle got off to a sensational start that year (at age 24), batting over .400 in both April (11 games) and May (31 games). His SLG was over .800 in both months as well.

At both age 23 and 24, Mantle had big gains in OPS+ (22 and 30, respectively). If Trout has a gain of 30 this year, that would give him a 205, not too far off from Mantle's 210.

Mantle went on to have two other seasons in his career with OPS+ over 200, plus one at 195. He finished with 172. Trout is at 169 in his career so far, not too far behind. But he will have a decline phase later in his career. So to stay close to Mantle, he will have to have some high OPS+ numbers at some point. Can Trout also have three seasons over 200? If he does, that would put him on a par with Mantle.

April Hitting, 2010-2016

From Baseball Reference. First table is AL, then NL. Biggest story seems to be NL gain in SLG of .025 over last year.

American League

Year	PA	AB	HR	BA	SLG	OBP	HR%
2010	12399	10952	304	0.255	0.406	0.330	0.028
2011	14148	12624	349	0.249	0.394	0.319	0.028
2012	11962	10742	342	0.252	0.409	0.319	0.032
2013	14825	13282	417	0.255	0.411	0.322	0.031
2014	15303	13611	344	0.252	0.392	0.324	0.025
2015	12432	11120	317	0.251	0.395	0.319	0.029
2016	13142	11836	375	0.245	0.399	0.311	0.032

National League

Year	PA	AB	HR	BA	SLG	OBP	HR%
2010	14207	12476	344	0.257	0.406	0.332	0.028
2011	16236	14436	375	0.252	0.389	0.320	0.026
2012	13615	12149	296	0.247	0.383	0.314	0.024
2013	14980	13380	383	0.247	0.391	0.313	0.029
2014	15714	14115	376	0.246	0.386	0.310	0.027
2015	12276	11061	275	0.249	0.385	0.311	0.025
2016	13613	12052	365	0.253	0.410	0.326	0.030

White Sox A Bit Lucky So Far This Year

The White Sox OPS in high-medium-low leverage situations .874-.642-.654 Their pitchers allow .510-.629-.673. Thru yesterday. So a bit luck.

They had a team OPS of .688 and allowed .622 for a differential of .066. Using all teams from 2010-14, the relationship between OPS differential and winning pct is

Pct = .5 + 1.3246*OPSDIFF

That estimates the Sox to have a .587 pct (much lower than their actual of .680 thru yesterday). In 25 games, that is about 14.7 wins or 2.3 fewer than they actually have (they may have increased their OPS differential with today's game).

.587 is not bad, but it is far below .680.

Using the same years, here is the equation when breaking things down by leverage

Pct = .5 + .306*LOW +.420*MED + .564*HIGH

Estimating the Sox pct here would be

Pct = .5 + .306*(-.0058) + .420*(.013) + .564*(.364) = .705

That is a bit high, but much closer to .680 than .587. It estimates the Sox win total to be 17.6. That is only off by .6 wins, much less than the 2.3 from using overall OPSDIFF. That differential in high situations is probably not going to last very long. From 1960-2014, the biggest differential in high leverage situations belongs to the 1995 Indians, with .208.

The lowest OPS allowed in high leverage situations was .552 by the 1965 Dodgers. The Sox .854 OPS by their hitters would rank tied for 25th out of 1,432 teams. So they have been incredible both ways in high leverage situations.

A Look At Jim Konstanty's 1950 MVP Award

He easily won the award, getting 18 of the 24 first place votes. Click here to see the voting results at Baseball Reference.

He was not in the top 10 in WAR (from Baseball Reference) and he was only 9th in WAR for pitchers, as the two tables below show. 18 players and pitchers who received MVP votes had a higher WAR than he did.

1	Stanky (NYG)	8.0
2	Robinson (BRO)	7.5
3	Musial (STL)	7.3
4	Blackwell (CIN)	6.9
5	Roberts (PHI)	6.8
6	Pafko (CHC)	6.6
7	Gordon (BSN)	6.4
8	Torgeson (BSN)	6.0
9	Snider (BRO)	5.9
10	Spahn (BSN)	5.6

1	Roberts (PHI)	7.3
2	Blackwell (CIN)	7.2
3	Jansen (NYG)	5.5
4	Roe (BRO)	5.4
5	Spahn (BSN)	5.2
6	Dickson (PIT)	5.1
7	Bickford (BSN)	5.0
8	Maglie (NYG)	4.8
9	Konstanty (PHI)	4.7
10	Lanier (STL)	4.6

He did pitch 152 innings, all in relief. He led the league in games (74, a post 1900 record at that time), games finished (62) and saves (22). But only 7 of those saves came in 1-run victories for the Phillies. He also had a 16-7 record. So although he trailed others by quite a bit in WAR, maybe he pitched well in key situations, and that enhanced his value, at least in the minds of the writers. Being on the pennant winning Phillies certainly helped.

Did he do exceptionally well when it mattered? He did finish high in Win Probability Added (WPA) for pitchers, which adds up all the changes in a team's chance of winning after each event (if he pitched in key situations alot, then he had the opportunity to help his team's chances more than other guys). It looks like he came in 2nd, only trailing his teammate Robin Roberts. The two were very close, maybe with just a slight difference that is not seen due to rounding. Musial led batters with 5.6.

1	Roberts (PHI)	5.4
2	Konstanty (PHI)	5.4
3	Maglie (NYG)	4.2
4	Jansen (NYG)	4.0
5	Blackwell (CIN)	4.0
6	Roe (BRO)	3.6
7	Lanier (STL)	3.0
8	Hearn (2TM)	2.7
9	Simmons (PHI)	2.6
10	Brazle (STL)	2.3

If WPA is divided by the average Leverage Index (LI), it removes context, so that a guy that gets to be in alot of key situations does not get an advantage. Musial led batters with 5.4. Six batters had a total of 3.4 or higher (none of them were position players on the Phillies), so that would leave Konstanty 9th in the league.

1	Roberts (PHI)	4.0
2	Jansen (NYG)	4.0
3	Konstanty (PHI)	3.3
4	Blackwell (CIN)	3.0
5	Hearn (2TM)	2.7
6	Spahn (BSN)	2.5
7	Palica (BRO)	2.4
8	Newcombe (BRO)	2.3
9	Church (PHI)	2.3
10	Maglie (NYG)	2.2

So he still ranks high, but he does slip just a bit. Maybe the writers accurately sensed that he performed well and often in key situations, although there were others who did better. Again, being on the first place team helps.

One thing the writers might have noticed is how well and often he pitched in extra innings. He had 25.2 extra IP. That was 1.2 more IP than the next two highest in all of MLB combined.  He allowed  an AVG-OBP-SLG  of .140-.253-.174 and OPS of .427. The league average was .723, so Konstanty beat that by a wide margin. His BAbip in extra innings was just .149 (batting average on balls in play).

For the whole season, his BAbip was .208 while his overall AVG allowed was .202. For the whole NL the AVG was .261 and the BAbip was .275. So he had a somewhat smaller overall difference than the rest of the league. The Phillies staff as a whole allowed a .248 AVG and a .261 BAbip. So his differential was about half what it was for the rest of the team. Maybe he had a bit of luck.

The year before his AVG allowed was .264 and his BAbip was  .279. The next year those were .281 and .284. For his career, they were  .265 & .266. So maybe 1950 was normal for him, having these two numbers be close. Maybe he was a bit better than other pitchers on balls in play.

But his FIP ERA (3.77) was much higher than his overall ERA (2.66). I found all the pitchers who had 150+ IP from 1946-60 (902) and ranked them by their difference between FIP ERA and regular ERA. Konstanty was 13th. So that indicates some luck for him. Here is the top 20.

Rk Player IP Year ERA FIP FIPDiff 1 Roger Craig 152.2 1959 2.06 3.56 1.50 2 Gene Bearden 229.2 1948 2.43 3.89 1.46 3 Joe Beggs 190 1946 2.32 3.64 1.32 4 Art Ditmar 200 1960 3.06 4.36 1.30 5 Ruben Gomez 221.2 1954 2.88 4.18 1.30 6 Sal Maglie 206 1950 2.71 3.93 1.22 7 Bob Buhl 216.2 1957 2.74 3.95 1.21 8 Billy Pierce 245 1958 2.68 3.87 1.19 9 Johnny Antonelli 258.2 1954 2.30 3.48 1.18 10 Eddie Lopat 178.1 1953 2.42 3.59 1.17 11 Tommy Byrne 196 1949 3.72 4.86 1.14 12 Monty Kennedy 186.2 1946 3.42 4.53 1.11 13 Jim Konstanty 152 1950 2.66 3.77 1.11 14 Bucky Walters 151.1 1946 2.56 3.67 1.11 15 Harry Taylor 162 1947 3.11 4.21 1.10 16 Bobby Shantz 173 1957 2.45 3.55 1.10 17 Ken Heintzelman 250 1949 3.02 4.11 1.09 18 Howie Pollet 266 1946 2.10 3.19 1.09 19 Bob Turley 245.1 1958 2.97 4.04 1.07 20 Fred Hutchinson 188.2 1949 2.96 4.02 1.06

His career ERA was 3.46 while his career FIP ERA was 4.01, a difference of .055, only half of the 1950 difference.

He did pitch better as the leverage went up. His OPS in low leverage situations was .644. Medium was .599 and high was .544. So he improved as the leverage increased, but it was nothing earth shattering.

But compared to everyone else in MLB that year, his High Leverage performance was great. Here is the top 20 in lowest OPS allowed in High Leverage situations for guys who had 25+ IP overall and faced at least 100 batters in High Leverage Situations.

Rk	Player	OPS	BF
1	Sal Maglie	0.512	174
2	Jim Konstanty	0.544	261
3	Allie Reynolds	0.589	218
4	Preacher Roe	0.596	211
5	Paul Minner	0.599	170
6	Steve Gromek	0.599	114
7	Larry Jansen	0.616	189
8	Curt Simmons	0.623	172
9	Max Lanier	0.624	160
10	Hal Newhouser	0.625	131
11	Monk Dubiel	0.625	130
12	Robin Roberts	0.631	262
13	Johnny Sain	0.635	196
14	Vic Raschi	0.637	264
15	Johnny Schmitz	0.653	181
16	Joe Dobson	0.661	175
17	Ken Raffensberger	0.664	183
18	Howie Fox	0.667	178
19	Don Newcombe	0.670	214
20	Willie Ramsdell	0.671	169

Although he is 2nd to Maglie, he had many more batters faced and the next guy behind him, Reynolds, is pretty far back. So again, maybe the writers picked up on his outstanding performance in key situations.

But he did not do that well in September, while the Phillies were in the midst of a tough pennant race (although they were up by 7.5 games with 11 left to play, they entered the last day of the season with just a 1 game lead as they had lost 8 out of 10 games and had to beat the Dodgers in extra innings to avoid a tie). In 36.2 IP, his ERA was 3.44 and he had just one save with a 3-3 record. His OPS allowed was .680. The league average was .694 in Sept/Oct.

While the Phillies lead fell from 7.5 games to just 1 in 10 days and 10 games, Konstanty pitched in relief 6 times. His record was 0-2, 0 saves and a blown save. His ERA in 13 IP was 6.23 with an OPS allowed of .915. He allowed 14 hits and 9 BBs (4 IBBs) while striking out just 2. 2 of the hits were HRs. So when it perhaps counted the most, Konstanty was not effective. It seems like that is something the voters would have noticed.

His teammate Robin Roberts had 70 IP in Sept/Oct (yes, 70) with a 2.44 ERA. But his record was just 2-5, maybe due to a lack of run support. He did pitch a 10 inning complete game on the last day of the season, allowing just 1 run. In 6 of those 9 starts, the Phillies scored 2 or fewer runs.

Del Ennis, who led the NL with 126 RBIs that year, a Phillie teammate, had an OPS of .908 in Sept/Oct (.333-.403-.505). His full season OPS was .923 and his WAR was 4.9. So he, along with Roberts, would have been a worthy choice for MVP if being on the first place team was important. Ennis was 4th in the voting while Roberts was 7th.

The New York Times article about the award does not discuss him pitching well in key situations, just his 16-7 record and suggests he saved at least 25 games. Konstanty said he could not have won the award without the help of his teammates.

The Sporting News did not go into too much detail either. They emphasized his total games pitched and one time he came in against the Giants with a 1 run lead in the bottom of the 9th and bases loaded and got the next three hitters out. It also mentioned the confidence that Phillie manager Eddie Sawyer had in him, often bringing him in with several innings left in the game. He had a 10 inning relief appearance (on Sept. 15-maybe it wore him out and that explains his poor performance in late Sept), a 9 inning one and 15 others of 3+ innings.

Bill James On Jackie Robinson's Fielding

See Jackie Robinson: Brooklyn Dodgers teammates and foes remember how he could do it all: Yes, Robinson broke barriers, but the pioneer was a player, too; one helluva player by Anthony McCarron of The New York Daily News in 2013. Excerpt:

"James says it’s generally true throughout Robinson’s career that his defensive stats, no matter where he played, are “tremendously good.” When James’ book came out, one of his measures ranked Robinson fifth all-time among second basemen on defense.

“The mystery of his career is that, while Jackie was never regarded as a really good defensive player at any position, when you look at his stats, he looks like a great defensive player at every position,” James writes in an email.

“You can attribute that to whatever you want, but I attribute it to intelligence,” James adds. “I think that he knew how to make plays, in the same way that he knew how to work the count as a hitter.”"

Did Al Simmons Have The Greatest Clutch Season Ever Recorded In 1930?

The definition of clutch that I am using can be found at Fangraphs-Clutch. Excerpt:

"Clutch measures how well a player performed in high leverage situations. It’s calculated as such:

Clutch = (WPA / pLI) – WPA/LI

In the words of David Appelman, this calculation measures, “…how much better or worse a player does in high leverage situations than he would have done in a context neutral environment.” It also compares a player against himself, so a player who hits .300 in high leverage situations when he’s an overall .300 hitter is not considered clutch."

The WPA stands for "Win Probability Added" and it tells us how much each plate appearance by a batter increased or decreased his team's chance of winning. LI is leverage index. Games that are late and close with runners on have a higher leverage than normal.

pLI: A player’s average LI for all game events.

Play by play data does not exist for all years. That is necessary for this stat.

I looked at all seasons with 300+ PAs and a clutch of 2.5 or higher using the Baseball Reference Play Index. The 3.5 for Simmons means he added 3.5 more wins by hitting better in the clutch than if he had just had his usual numbers.

Player	Clutch	Year
Al Simmons	3.5	1930
David Ortiz	3.3	2005
Eddie Murray	3.3	1985
Troy O'Leary	3.2	1996
Mickey Stanley	3.2	1968
Nellie Fox	3.2	1959
Arky Vaughan	3.2	1943
Tony Gwynn	3.1	1984
Dave May	2.9	1973
Rickey Henderson	2.8	1988
Tony Gwynn	2.8	1988
Kirby Puckett	2.8	1985

Simmons batted .381 that year with 36 HRs and a 157 RBIs. His OBP was .423 and his SLG was .708. Click here to see his 1930 splits Here is a sample

Split	BA	OBP	SLG	OPS
RISP	0.437	0.449	0.826	1.275
None on	0.379	0.417	0.692	1.109
Men On	0.383	0.411	0.730	1.141
2 outs, RISP	0.402	0.437	0.732	1.168
Late & Close	0.429	0.461	0.857	1.318
High Lvrge	0.469	0.488	0.867	1.355
Medium Lvrge	0.370	0.416	0.648	1.064
Low Lvrge	0.345	0.367	0.706	1.073

How the error rate can affect the run value of OBP & SLG

This is something I did several years ago and I think originally I just mentioned it on the SABR list.

Here is an example of how the error rate can affect things. The error rate is 1 - fielding pct. The regression below shows runs per game as a function of OBP & SLG for each season of the NL from 1920-2012 (I used the whole league instead of teams)

R/G = 22.77*OBP + 6.7*OBP - 5.68

Now what if we add in the error rate. The regression becomes

R/G = 15.75*OBP + 9.7*SLG + 15.69*ERATE - 4.94

The relative value of OBP & SLG changed quite a bit. But this is for a whole league. The ERATE applies to the whole league.

I have used the ERATE and applied it to teams. That assumes that the rate of errors made against each team is the same. Not totally realistic, but that is what I have. Sof it the ERATE was .02 one year in a league, every team got that rate.

I did all teams from 1920-1998. Here are the two regressions

R/G = 19.89*OBP + 9.79*SLG - 5.95

R/G = 17.63*OBP + 10.7*SLG + 13.51*ERATE - 5.87

So again the relative values of OBP & SLG change