Sunday, September 27, 2015

Yogi Berra's Amazing HR-To-Strikeout Rate

He hit 358 HRs while the league average player would have hit 175 (358/175 = 2.04, which is multiplied by 100 to get the HR rate in the table below). He had 414 strikeouts while the league average player would have had 844. That gets us the 49 in the table below.

If we then do HR Rate/SO Rate we get 204/49 = 4.16. That leaves Berra 4th all-time. All data from the Lee Sinins Complete Baseball Encyclopedia.


Rank Player HR Rate HR SO RATE SO HR/SO
1 Ken Williams 370 190 75 237 4.93
2 Joe DiMaggio 277 361 59 369 4.69
3 Tris Speaker 145 72 33 104 4.39
4 Yogi Berra 204 358 49 414 4.16
5 Ernie Lombardi 222 190 54 262 4.11
6 Frank McCormick 151 128 39 189 3.87
7 Tommy Holmes 103 88 27 122 3.81
8 Albert Pujols 207 492 57 835 3.63
9 Ted Williams 286 521 79 709 3.62
10 Johnny Mize 306 359 86 524 3.56
11 Bill Dickey 185 202 55 289 3.36
12 Babe Ruth 622 665 189 1146 3.29
13 Stan Musial 174 475 55 696 3.16
14 Ted Kluszewski 176 279 56 365 3.14
15 Lou Gehrig 369 493 118 790 3.13
16 Mel Ott 327 511 106 896 3.08
17 Hank Aaron 237 755 77 1383 3.08
18 Barry Bonds 237 762 78 1539 3.04
19 Don Mattingly 120 222 40 444 3.00
20 Rogers Hornsby 322 274 109 492 2.95
21 Chuck Klein 291 300 99 521 2.94
22 Mickey Cochrane 147 119 52 217 2.83
23 Vladimir Guerrero 176 449 65 985 2.71
24 Gary Sheffield 176 509 67 1171 2.63
25 Billy Williams 191 426 74 1046 2.58

Now Berra did hit 210 HRs at home in Yankee Stadium, which was a great park for HR hitting if you were a lefty. But if we double his road total of 148 we get 296. If we divide that 296 by the league average of 175, we get a HR rate of 169. If that is divided by his SO rate of 49, we get 3.44. That would still leave him 11th.

Maybe Yankee stadium also cut down on his strikeouts. I don't know if it helped batters in that way. I also could have given him more than 296 HRs, since players usually hit more at home no matter what.

If we adjusted DiMaggio, who hit 213 of his HRs on the road (Yankee Stadium was tough on righties), his ratio would rise to 5.56, putting him ahead of Ken Williams.

DiMaggio hit only 41% of his HRs at home in his career while Williams hit 72%. So it is likely the case that DiMaggio would rank first, and probably by a wide margin, if HRs were park adjusted. Ted Williams hit less than 50% of his HRs at home.

See Should Joe DiMaggio's Offensive Value Be Estimated Upwards Because Of Yankee Stadium?

Saturday, September 19, 2015

Astros & Rangers

This is through games of Thursday
  • Astros have a team batting OPS of .733 and their pitchers have allowed .677. My regression estimates suggest the Astros should have a .573 pct or 84 wins, not 77

    For Rangers those are .732 & .743. So the Astros have a healthy positive differential while the Rangers are actually negative.

    Here are some things that might affect this and they are probably luck for the most part in favor of the Rangers

    Rangers allow a .666 OPS in close and late situations (much lower than what they normally allow). They are 26-20 in 1-run games and Astros are 19-26

    Astros Allow a .702 OPS with runners on and .660 with bases empty. Normally with runners on is higher but that is probably a bigger differential than normal. So that hurts them a bit

    Astros allow a .674 OPS in close and late situations, about what they normally do. So they don't gain like the Rangers do

    Astros hitting OPS in close and late situations is just .699. Rangers have .725. So the Astros hitters fall off more in those cases than the Rangers

Friday, September 18, 2015

Trout Joins Club With Ted Williams

They are the only two guys to get 300+ TBs at ages 20-21-22-23.

Trout has done 315-328-338-302.

So with 16 games left, he is going to clear the bar easily in all 4 seasons

Williams had 344-333-335-338

Wednesday, September 16, 2015

So Far, Both Leagues Have Had Their Highest OPS In September And That Is Somewhat Rare

Here are the years it happened in the AL since 1914, including this year (using the Baseball Reference Play Index-it also includes any regular season October games):


1914 0.662
1916 0.671
1918 0.768
1924 0.765
1973 0.722
1982 0.740
1985 0.750
2015 0.759

Now the NL


1939 0.733
1968 0.652
1973 0.714
1985 0.720
2007 0.784
2015 0.743

So 14 times out of 202 possible years (101 for each league, not counting 1994 when there were no games in September). So it happens about 6.9% of the time. This will be only the third time for both leagues in the same year. The AL came close in 2007 with a .770 OPS in September while May was highest with .771.

The second highest month in the AL so far was August with .739. In the NL, it is also August with .734. So the AL is a much better bet to have its highest OPS in September, since that month is currently .020 ahead of the next highest while it is only .009 higher for the NL.

Saturday, September 12, 2015

Cardinal's Pitching Has Been Great This Year, Especially With Runners On Base And Unusually So

With no runners on, they have allowed a .318 OBP and a .390 SLG but with runners on, those numbers are .295 and .329. This differential is much better than any team over the years 2101-14. We can measure this by using OBP and SLG to estimate wOBA or weighted on-base average, a stat from Tangotiger. See this definition at Fangraphs. All data from Baseball Reference.

The idea is that each event has a run value and once that is found it is divided by something like plate appearances. The following estimator is a good approximation:

wOBA = (1.7*OBP + SLG)/3

So that gives the Cards a .310 wOBA with no runners on (NONE) and .277 with runners on (ROB). So, they are .033 better with ROB. The team with the best differential from 2010-2014 was the 2011 Phillies, who allowed a .296 wOBA with NONE and a .276 with ROB. So they were only .020 better, not even close to the Cards this year. The 2013 Red Sox were next being .018 better.

I ran a regression to estimate runs per game allowed using this wOBA estimator for all teams (in all situations) from 2010-2014. Here is the equation:

R/G =  30.136*wOBA - 5.20

The standard error was 23.94 per 162 games. The Cards have about a .296 wOBA allowed in all situations this year. The equation predicts they would allow about 3.72 runs per game while it is actually 3.21. So they are allowing about half a run per game less than expected. Their performance with ROB helps out here.

I also ran the regression with wOBA in both NONE and ROB situations. Here is the equation:

R/G = 11.72*NONE + 18.52*ROB - 5.32

The standard error was 21.1 per 162 games.  It predicts the Cards would allow 3.44 runs per game (only .23 above the actual). So over half the difference between their actual runs allowed per game and that predicted by wOBA is eliminated if we break things down into wOBA allowed in NONE and ROB situations.

Some of the remaining differential is probably explained with their wOBA with runners in scoring position (RISP). That is just .269. 

Thursday, September 10, 2015

Big Jump So Far In OPS In Both Leagues In September


AL PA BA OBP SLG OPS
April/March 12432 0.251 0.319 0.395 0.713
May 16107 0.252 0.312 0.402 0.715
June 15109 0.255 0.314 0.407 0.721
July 14230 0.258 0.316 0.416 0.733
August 15956 0.259 0.319 0.420 0.739
Sept/Oct 4735 0.262 0.324 0.438 0.763





NL PA BA OBP SLG OPS
April/March 12276 0.249 0.311 0.385 0.696
May 16051 0.254 0.315 0.395 0.710
June 15429 0.256 0.314 0.391 0.706
July 14108 0.252 0.315 0.390 0.705
August 16077 0.256 0.319 0.414 0.734
Sept/Oct 4952 0.271 0.334 0.439 0.773

Saturday, September 5, 2015

Decade Distribution Of Top Defensive War Seasons

Baseball Reference Rankings.

The first table shows the number of seasons from a decade that are in the top 100 (actually the top 106 due to ties). 1900 means the decade of 1900-09. The 1950s had only one such season, Ernie Banks, 3.5 in 1959, which is tied for 62nd place. From 1945-58, there was not a single season in the top 106.

The percent of the total that each decade has is listed next. Then the total defensive WAR from the guys in that decade and that decade's percentage of all the WAR from the top 100 (actually 106).



Decade
Count
Percent
Defensive WAR
Percent
1900
11
0.104
40.5
0.102
1910
6
0.057
23.7
0.060
1920
5
0.047
19.8
0.050
1930
2
0.019
7.9
0.020
1940
9
0.085
31.6
0.080
1950
1
0.009
3.5
0.009
1960
15
0.142
55.4
0.140
1970
11
0.104
42
0.106
1980
11
0.104
40
0.101
1990
9
0.085
32.9
0.083
2000
11
0.104
40.2
0.102
2010
15
0.142
58.2
0.147


The 1930s also had only 2 seasons while the 2010s have already had 15, the most since the 1960s. Some of this has to do with how many games get played and teams there are, but the 2010s are still doing very well.

Here is the same table for the top 500 seasons (actually the top 546 due to ties)



Decade
Count
Percent
Defensive WAR
Percent
1880
13
0.024
31.8
0.020
1890
8
0.015
20.5
0.013
1900
40
0.073
117.5
0.076
1910
33
0.060
97.8
0.063
1920
23
0.042
68.7
0.044
1930
28
0.051
76.2
0.049
1940
31
0.057
89.5
0.058
1950
26
0.048
70
0.045
1960
48
0.088
140.4
0.090
1970
69
0.126
194.9
0.126
1980
62
0.114
172.3
0.111
1990
54
0.099
149.4
0.096
2000
58
0.106
165.5
0.107
2010
53
0.097
157.9
0.102