Carlos Correa's WAR Is In Top 10 Already For Shortstops Aged 20 And Younger

From the Baseball Reference Play Index

For single seasons, From 1901 to 2015, Younger than 20, Played 50% of games at SS, (requiring WAR_bat>=1), sorted by greatest WAR Position Players. Player ages are computed as their age on June 30th. Correa has 1.1 offensive WAR and 0.7 defensive WAR (there must be a rounding issue).

Rk Player WAR Year Age PA 1 Alex Rodriguez 9.4 1996 20 677 2 Travis Jackson 4 1924 20 633 3 Arky Vaughan 3.8 1932 20 555 4 Elvis Andrus 3.6 2009 20 541 5 Edgar Renteria 3.2 1996 19 471 6 Alan Trammell 2.8 1978 20 504 7 Jose Reyes 2.3 2003 20 292 8 Travis Jackson 2.1 1923 19 350 9 Carlos Correa 1.7 2015 20 93 10 Starlin Castro 1.6 2010 20 506

SABR Names Dan Levitt As Winner Of This Year's Bob Davids Award

Click here to read about his achievements at the official SABR site. This seems well deserved. Dan excels at both history and sabermetrics.

Here is an excerpt from the announcement:

"Levitt is the author of four fine books: Paths to Glory: How Great Baseball Teams Got That Way (with Mark Armour; winner of the 2004 Sporting News-SABR Baseball Research Award); Ed Barrow: The Bulldog Who Built the Yankees' First Dynasty (a 2009 Seymour Medal finalist); The Battle That Forged Modern Baseball: The Federal League Challenge and Its Legacy (which won the 2013 Larry Ritter Award); and In Pursuit of Pennants: Baseball Operations from Deadball to Moneyball, published this spring with Mark Armour."

This was a good article by Dan: The Batter/Pitcher Match Up. Using the Bill James Log5 formula, Dan found that good hitters do about as well as we would expect against good pitchers. I think it is from the late 1990s.

Click here to go to Dan's Amazon page.

Here is part of what the award is about:

"The Bob Davids Award honors SABR members whose contributions to SABR and baseball reflect the ingenuity, integrity, and self-sacrifice of the founder and past president of SABR, L. Robert "Bob" Davids. Voluntary activities in the area of administration and research are among those contributions considered."

Where Does "The Sandberg Game" Rank In WPA?

On this date in 1984, Ryne Sandberg was 5 for 6 and hit game tying HRs in the bottom of the 9th and the bottom of the 10th (the latter with two outs and 1 on). The Cubs beat the Cardinals 12-11 in 11 innings.

But the big deal is that both of those HRs were off of Hall of Fame reliever Bruce Sutter. The game was televised nationally, I think on NBC. It was, if I recall correctly, a warm sunny day at Wrigley Field (I saw this game on TV).

Sandberg was not a big star yet, although he did win the MVP award that year. It was only his third full season and he had not yet played in an All-Star game. His career average entering the season was .261 with just 15 HRs in 327 games (all statistics used here are from Baseball Reference).

He did enter this game with a .321 average but just 7 HRs in 66 games (a pace of only 17 for a full season).

But how hard was it to homer against Sutter? He gave up 9 in 1984 while facing 477 batters. He faced Sandberg 6 times that year and gave up those 2 HRs. So when not facing Sandberg, Sutter gave up 7 HRs in 471 PAs. The year before he gave up 8 in 384 PAs. When not facing Sandberg over those two years, his HR per batter faced rate was 1.76%. This sounds about average.  The NL HR per batter faced rate over those two years was 1.81% (again, without IBBs removed).

He also issued 18 IBBs, so that HR rate might be higher than average. Sutter had a higher IBB rate than average, which was only about 1% (Sutter's was about 2%).

So yes, it was a big deal to hit those HRs. But at this point in his career, Sutter was about average in allowing HRs. In fact, not counting Sandberg, he allowed a higher HR% vs. righties (2.4%) than lefties (1.6%) over those two years.

Sandberg has said "It was one of those wild games, wind blowing out a little bit so it was going to be an offensive game from the get-go." See Wrigley 100 June 23: The Sandberg Game. There was, however, only one other HR in the game.

So what was Sandberg's WPA in that game? 1.063. It is the 35th highest since 1941, according to the Baseball Reference Play Index. Here are the top 40:

Rk	Player	Date	WPA
1	Art Shamsky	8/12/1966	1.503
2	Dolph Camilli	1941-09-01 (1)	1.398
3	Jim Pagliaroni	9/21/1965	1.287
4	Brian Daubach	8/21/2000	1.253
5	Nelson Cruz	9/7/2014	1.22
6	Bobby Grich	7/15/1979	1.211
7	Mel Hall	6/27/1984	1.206
8	Carlos May	1973-09-03 (1)	1.204
9	Willie Mays	5/26/1962	1.204
10	Del Ennis	4/26/1949	1.197
11	Jim Hickman	5/28/1970	1.181
12	Hank Aaron	9/10/1971	1.159
13	Dwight Evans	6/23/1990	1.145
14	Dante Bichette	6/10/1998	1.141
15	Ken Boyer	1961-09-14 (2)	1.14
16	Cody Ross	6/7/2008	1.139
17	Will Clark	6/22/1988	1.133
18	George Brett	5/28/1979	1.126
19	Bobby Bonds	4/29/1969	1.126
20	Ryan Langerhans	9/7/2005	1.119
21	Barry Bonds	8/12/1991	1.119
22	Brandon Inge	8/24/2003	1.113
23	Hank Aaron	8/18/1959	1.112
24	Bill Melton	1970-08-02 (2)	1.107
25	Tim Harkness	6/26/1963	1.107
26	Wilin Rosario	9/18/2014	1.087
27	Mike Young	5/28/1987	1.087
28	Fred McGriff	8/24/1996	1.084
29	Roy Sievers	7/16/1958	1.083
30	Bob Allison	4/16/1963	1.082
31	Josh Hamilton	7/9/2011	1.081
32	Ted Williams	1946-07-14 (1)	1.072
33	Kevin Mitchell	8/13/1987	1.064
34	Willie Montanez	7/11/1976	1.064
35	Ryne Sandberg	6/23/1984	1.063
36	Jerry Buchek	1967-09-22 (2)	1.063
37	Jose Bautista	5/22/2013	1.062
38	Eric Soderholm	5/13/1972	1.059
39	Raul Mondesi	4/5/1999	1.056
40	Steve Finley	9/10/1996	1.056

Top 10 Average Game Scores This Year, 8 Start Minimum

After Saturday's no-hitter (June 20), which was a 97, Scherzer is at 70.29. That would be 7th since 1938 for guys with 30+ starts.

Max Scherzer	68.2
Chris Sale	65.3
Dallas Keuchel	64.9
Zack Greinke	64.3
Sonny Gray	64.1
Chris Archer	63.6
Francisco Liriano	63.1
Gerrit Cole	63
Jacob deGrom	62.7
Johnny Cueto	61.8

Here is that top 10

Bob Gibson	76.1	1968
Luis Tiant	72.4	1968
Sandy Koufax	71.8	1965
Tom Seaver	70.9	1971
Pedro Martinez	70.8	1997
Dwight Gooden	70.4	1985
Vida Blue	69.9	1971
Sandy Koufax	69.8	1963
Steve Carlton	69.3	1972
Hal Newhouser	69.3	1946

SB% Lower So Far This Year

Here are the AL %'s in recent years

2003	70.04%
2004	68.62%
2005	70.49%
2006	71.46%
2007	73.19%
2008	72.96%
2009	73.98%
2010	73.59%
2011	72.10%
2012	74.98%
2013	73.57%
2014	73.91%
2015	69.37%

The AL has had at least 73% ever year since 2007 except 2008 which was very close at 72.96%. But for some reason this year is below 70%.

Now the NL

2003	68.87%
2004	71.71%
2005	70.67%
2006	71.29%
2007	75.56%
2008	73.04%
2009	70.74%
2010	71.20%
2011	72.34%
2012	73.13%
2013	71.92%
2014	71.62%
2015	70.10%

Maybe not as dramatic as the AL, but the NL had 75.56% in 2007 and this year could be the lowest since 2003.

For Pitchers That Change Teams, What Affects Their BABIP More? Their Own BABIP From The Year Before Or The BABIP For The Rest Of Their New Team?

This is related to the previous post Year to year correlation of BABIP for pitchers that changed teams and those that did not.

I ran another regression for the guys who changed teams. The dependent variable was their BABIP in year 2 and the independent variables were their BABIP in year 1 and the BABIP for the rest of their new team in year 2 (so that each guy's BABIP was removed from the team total). Here is the equation

BABIP2 = 0.232*OtherBABIP2 + 0.123*BABIP1 + 0.189

OtherBABIP2 means the BABIP for the rest of their new team in year 2

The r-squared is .022. Standard error is .02004. T-values are

OtherBABIP2 1.18
BAbip1 1.25

So neither is significant. But .232/.123 is 1.88. So the effect from the BABIP from the rest of the team (the guy's new team) is almost double from his previous year's BABIP.

The correlation between BABIP2 and OtherBABIP2 is .086, almost as high as .094, correlation between BABIP2 and BABIP1 for this same group of guys who changed teams (all the guys who had 150+ IP in the years 2003-14).

If we suppose that fielders have no influence on BABIP, then it means that the contribution from "the rest of the team" is due solely to the other pitchers. Then why is the effect  from other pitchers so much stronger than the pitcher himself (or at least what he did the year before)?

That would not make any sense. So it seems like there would have to be a big role for the fielders. If you think it is a "small" role, but not zero, the previous paragraph still applies.

The previous post showed that for guys who stayed on the same team, the impact of last year's BABIP on this year's BABIP was 2.5 times higher than it was for guys who changed teams.

And what is the big change when you switch teams? The fielders. The parks, too. The pitchers have a whole new set of fielders behind them and they pitched half their games (or around that) in a completely different park than the year before.

I don't know how much the makeup of a team's fielders change from year to year. My guess is that it is less than 50%. So guys who stay on the same team don't see much change in fielders and most of the time no change in park.

So it looks like the big difference between guys who change teams and guys who don't is the fielding. You could say guys staying on the same team see a change in fielding. But that is probably small compared to the guys who change teams.

And you could say that for guys who change teams the change in parks is a big deal. But you only pitch about half the time in one park, whereas it probably the same mix of fielders behind you all the time. So again, that points to the fielders.

Year to year correlation of BABIP for pitchers that changed teams and those that did not

I found all the guys who had 150+ IP in the years 2003-14.  If a guy pitched for two teams in a year, that guy in that year was disqualified. I found the year to year correlations for SO, BBs, HRs and BABIP (SO, BBs, HRs were all as a percentage of batters faced, which excluded IBBs and I included HBP in BBs). I used the Baseball Reference Play Index. (June 11-I made some corrections as mentioned in my first comment)

There were 488 cases of a guy being on the same team the next year (of course, if John Smith was on the Reds from 2011-13, we have one case of his 2011-12 seasons and another case of his 2012-13 seasons)

There were 107 cases of guys being on a different team the next year. Here are the correlations for each group

 Same team

 BABIP    0.234
 BB          0.704
 HR          0.384
 SO          0.811

 Different team

 BABIP    0.094 (p value is .33)
 BB          0.692
 HR          0.305
 SO          0.733

The p-value in all cases except for the one listed are under .01. So the only one which is not significant (and it is not even close) is BABIP for guys that changed teams.

Now the correlations are lower for the guys that switched teams for all four stats. But the difference for BABIP is by far the biggest.

It is not clear what causes this. The pitchers have a whole new set of fielders behind them and they pitched half their games (or around that) in a completely different park than the year before. It seems like if the pitchers had the most control over what happens on balls in play, the correlation for guys that change teams would be closer to that of guys who stayed on the same team.

Phil Birnbaum suggested I run a regression in which BABIP in year 2 depends on BABIP in year 1. Here it is for guys that stayed on the same team.

BABIP2 = .234*BABIP1 + .226

No the regression for guys that were on a different team

BABIP2 = .093*BABIP + .268

The effect is 2.53 times higher if you stay on the same team. That is, if you stayed on the same team, your BABIP in year 1 is about 2.5 times stronger in predicting your BABIP in year 2 than if you switched teams.

Team OPS Differentials Thru 6-4-15

The season is about a third over.

TEAM	OPS	OPSA	DIFF	Pct
LA Dodgers	0.789	0.668	0.121	0.574
St. Louis	0.730	0.655	0.075	0.667
Kansas City	0.738	0.668	0.070	0.588
Houston	0.722	0.666	0.056	0.618
Oakland	0.710	0.658	0.052	0.411
Pittsburgh	0.698	0.655	0.043	0.547
Tampa Bay	0.697	0.655	0.042	0.527
San Francisco	0.733	0.699	0.034	0.545
NY Yankees	0.723	0.696	0.027	0.537
Cleveland	0.734	0.709	0.025	0.491
Toronto	0.765	0.740	0.025	0.455
Detroit	0.737	0.715	0.022	0.509
Washington	0.723	0.701	0.022	0.537
LA Angels	0.684	0.666	0.018	0.519
Chicago Cubs	0.699	0.690	0.009	0.538
NY Mets	0.674	0.671	0.003	0.545
Cincinnati	0.707	0.716	-0.009	0.442
Texas	0.731	0.741	-0.010	0.519
Baltimore	0.707	0.718	-0.011	0.453
Arizona	0.733	0.747	-0.014	0.472
Seattle	0.689	0.703	-0.014	0.444
Miami	0.683	0.699	-0.016	0.407
Colorado	0.750	0.780	-0.030	0.462
Boston	0.683	0.728	-0.045	0.436
Atlanta	0.689	0.738	-0.049	0.491
Minnesota	0.687	0.738	-0.051	0.604
San Diego	0.676	0.758	-0.082	0.491
Milwaukee	0.659	0.760	-0.101	0.333
Philadelphia	0.635	0.739	-0.104	0.382
Chicago Sox	0.651	0.756	-0.105	0.462

It looks like the big an0molies are the Twins and the A's. Twins are 11-7 in 1-run games (about what they normally do). The A's are 3-15. Both their pitchers and hitters are really bad when it is late & close. See tables below.

The Twins hitters doing much better with runners on but not so good when it is late & close:

Twins	Hitters
Split	BA	OBP	SLG	OPS
RISP	0.299	0.371	0.451	0.823
None on	0.232	0.276	0.355	0.631
Men On	0.280	0.343	0.421	0.764
Late & Close	0.199	0.264	0.280	0.544

Now the Twins pitchers. Seems to be the opposite of the hitters. So-so with runners on but great when it is late & close.

Twins	Pitchers
Split	BA	OBP	SLG	OPS
RISP	0.264	0.345	0.404	0.749
Men On	0.273	0.340	0.417	0.757
None on	0.270	0.305	0.418	0.723
Late & Close	0.211	0.257	0.289	0.545

Now the A's hitters. They seem okay with runners on but are pretty bad when it is late & close.

A's	Hitters
Split	BA	OBP	SLG	OPS
RISP	0.254	0.310	0.414	0.724
None on	0.258	0.320	0.387	0.706
Men On	0.254	0.318	0.397	0.715
Late & Close	0.241	0.294	0.337	0.631

Now the A's pitchers. They are doing poorly in RISP and late & close situations

A's	Pitchers
Split	BA	OBP	SLG	OPS
RISP	0.260	0.345	0.410	0.755
Men On	0.241	0.323	0.371	0.693
None on	0.235	0.291	0.341	0.632
Late & Close	0.276	0.350	0.429	0.779

How Overmatched Were The Mets Against The Orioles In 1969?

Very. The Orioles had the 4th highest OPS differential ever (from 1914-2014). It was .136. The Mets had just .017 (and several NL teams had better that year). So the Orioles had an advantage of .119.

The only time there was a greater difference before 1969 for the teams meeting in the World Series was in 1944 when the Cardinals had an OPS differential of .130 and the Browns had just .005. So the Cards had an advantage of .125. But that was a war year.

The 1927 Yankees had the greatest OPS differential of .196 and their opponent, the Pirates, had .084 (which is very good). So the Yanks had an advantage of .112.

Thru 1969, these are the only cases of an advantage being at least .100. There were also only three other cases reaching even .080. 42 cases had an advantage of less than .050. And that is out of 56 World Series.

So the Orioles came into the 1969 Series with an incredible edge over the Mets but the Mets still won.

If we go by OPS differential, 1969 was the greatest upset ever. The next biggest was

1931: A's had a .109 differential, Cardinals .045. A's had a .064 advantage yet Cards won.

So with an advantage of .119, the Orioles losing to the 1969 Mets was not just the biggest upset (at least since 1914), it was far and away the biggest.

One year before 1914 that was a big upset was 1906 when the White Sox beat the Cubs. But we don't have opponents SLG for before those years. But we can make an educated guess about how big of an advantage the Cubs had.

The Cubs had an OPS of .667 on offense while the Sox had .588. That gives the Cubs an advantage of .079.

The pitchers of each team allowed an OBP of .280. For the Cubs to have an edge of .119 in OPS differential, they would have to have allowed an SLG of .040 less than the Sox.

The Cubs did allow their opponents a batting average of .207 while it was .239 for the Sox. Now if each allowed the same isolated power, then the Cubs would have an SLG which is .032 lower. That would bring their advantage up to .111 (.079 + .032). That would make 1906 the 4th biggest upset.

The Cubs allowed 12 HRs and the White Sox 11. That suggests that they had the same isolated power allowed. But if the Cubs had allowed an ISO that was .008 less than the Sox, it would bump their advantage up to .119 and the upset would be just as big as the one in 1969 (SLG = AVG + ISO).

Since ISO is extra bases divided by ABs, it would mean that the Cubs would have to have allowed about 39 fewer extra bases (based on 4,918 ABs, which we can get by dividing their hits allowed by .207).

That would mean something like the Cubs allowing 20 fewer 2Bs and 10 fewer 3Bs. That would be 40 extra bases. That seams plausible. But we don't know for sure. There is just a possibility that 1906 was a bigger upset than 1969.

Harper Has Fourth Best Monthly OPS+ Ever For A Player 22 Or Younger

Here is the top 20 with 75+ PAs for the month using the Baseball Reference Play Index:

Rk	Player	Month	Year	PA	OPS+
1	Ted Williams	Sept/Oct	1941	101	297
2	Ted Williams	July	1941	80	284
3	Ted Williams	August	1941	157	279
4	Bryce Harper	May	2015	109	279
5	Joe DiMaggio	July	1937	139	277
6	Ted Williams	Sept/Oct	1939	127	265
7	Eddie Mathews	Sept/Oct	1954	97	263
8	Boog Powell	June	1964	86	259
9	Cesar Cedeno	June	1972	127	251
10	Mike Trout	June	2014	102	248
11	Ted Williams	June	1941	125	243
12	Bernie Carbo	May	1970	80	239
13	Mike Trout	July	2012	112	238
14	Pete Reiser	Sept/Oct	1941	114	235
15	Ken Griffey	July	1991	94	235
16	Johnny Bench	June	1970	104	235
17	Johnny Bench	May	1969	77	233
18	Al Kaline	August	1956	131	233
19	Jimmie Foxx	May	1929	121	232
20	Hank Aaron	July	1956	130	231

Now for 23 and under. Harper is 6th. He is in excellent company on each list

Rk	Player	Month	Year	PA	OPS+
1	Ted Williams	Sept/Oct	1942	90	348
2	John Mayberry	June	1972	76	299
3	Ted Williams	Sept/Oct	1941	101	297
4	Ted Williams	July	1941	80	284
5	Ted Williams	August	1941	157	279
6	Bryce Harper	May	2015	109	279
7	Reggie Jackson	June	1969	126	277
8	Joe DiMaggio	July	1937	139	277
9	Ted Williams	May	1942	125	268
10	Ted Williams	Sept/Oct	1939	127	265
11	Dick Wakefield	Sept/Oct	1944	127	264
12	Eddie Mathews	Sept/Oct	1954	97	263
13	Boog Powell	June	1964	86	259
14	Eddie Mathews	June	1955	118	256
15	John Mayberry	Sept/Oct	1972	131	252
16	Alex Rodriguez	May	1999	75	251
17	Rudy York	August	1937	126	251
18	Cesar Cedeno	June	1972	127	251
19	Mike Trout	June	2014	102	248
20	Jose Canseco	Sept/Oct	1988	108	247