This just in – strikeouts are up again in 2013, averaging more than 7.5 per 9 innings. This is the 10th year-over-year increase in the past 14 seasons, and the 5th straight year setting a new all-time high. Not news to most readers here. Question, though, is this – is it good for the game? Does striking out a lot as the price for belting more homers really help a team score more runs? At what point, if any, does the cost outweigh the benefits?

What follows is a visual statistical analysis of strikeouts and home runs, the relationship between the two, and how that relationship contributes to or detracts from run scoring. No heavy lifting, but I hope you may come away with some new insights on this very pervasive influence on today’s game.

All of the data depicted below were obtained from FanGraphs and Baseball-Reference. The various (and oddball) metrics derived from them are my own, so I am to blame for any errors in their conception or execution.

So let’s start with the frequency of strikeouts and home runs in the live ball era. Below is a chart showing a mostly consistent increase in both home runs and strikeouts from the start of the live ball era to today.

Strikeout-Home Run Trends

The overall trend is that strikeouts and home runs increase in tandem. However, that trend has broken down at times, typically after periods of rapid increases. Two such periods are shown in the circled areas. In each the steep rise in home runs and strikeouts was interrupted by a home run decline accompanied by strikeouts leveling off, as indicated by the arrows in the circled areas.

The most recent period, beginning early this century is different from at any time previously. Home runs are declining but strikeouts have not leveled off. Instead, they have continued to rise, trending in the opposite direction from home runs, a pattern not seen previously for more than a few years without correcting.

Note also that the decline in home runs has been substantial, with home run rates in 2010 and 2011 at the same level as was seen as far back as the early 1960s. The big difference between then and now – the “cost” for producing that home run output has soared, with strikeouts up by more than 2 SO/9 from the level of more than 50 years ago.

Next, let’s look at run production. The chart below shows R/9 (the brown line) always between 3 and 6 runs per 9 innings, and usually in a much tighter range than that. In fact, with just a few exceptions (notably the late 1960s and early 1970s), R/9 was between 4 and 5 for almost 60 years, from 1937 to 1995. Before and after those dates, runs were higher as was BABIP. Note though the relationship between BABIP and Hits in Play (i.e. H – HR). In the 1920s and 1930s a BABIP in the .290 to.310 range equated to close to or above 9 HIP/9, whereas a .290 to .300+ BABIP in the 1990s and 2000s yielded only around 8 HIP/9 (more on that later).

Scoring-Hitting Trends

Interesting phenomenon with BABIP. Cratered during the war due to inferior baseballs and hitters, but the steep downward trend was already evident in the late 1930s. Then basically bounced around in the .270s for 35 years, before starting to trend gradually upwards. Then in the early 1990s it suddenly spiked way up, almost as sharply as BABIP had spiked down at the end of the 1930s.

But, look what has happened since 2005. Runs, Hits in Play and BABIP are all declining steadily. As with home runs, runs and hits are also now at about the same level as in the early 1960s, but BABIP, despite its decline, is still a good 10 or 15 points higher than 50+ years ago. So, why are runs seemingly tougher to produce now than in the past?

The chart below provides an answer. In essence, to produce the same quantity of runs, batters have to produce more with the balls they put in play to compensate for producing less with the balls not put into play. Ergo, the cost of the ever-increasing strikeout count.

Balls Not In Play Trends

Since 1920, balls not in play (HRs, SOs, BBs, HBPs) have doubled to about 12 per 9 innings today, almost one-third of the PAs (31.2% in 2012) in a game. That upward trend in BNIP has been pretty consistent throughout the live ball era with the exception of the decade of the 1970s.

As balls not in play have risen, the on-base percentage arising from them has steadily declined. Strikeouts first exceeded the sum of other BNIPs in the mid 1950s and, aside from the 1970s, have been rising at a faster rate than walks and home runs. To maintain run scoring, then, home runs must compensate for the negative effects of ever-increasing strikeouts. How well has that worked?

The chart below has a lot of information. The bottom three lines are all showing the increasing influence of home runs, measured as a % of Hits, a % of Runs, and as the % of runs resulting directly from home runs (i.e. RBI on HRs). The top two lines show the effects of that influence: the purple line indicates the % of baserunners (excluding baserunners out on base) scoring, being (R – HR) / (BF – HR – IP*3); and the teal or cyan line indicates baserunners left on base, being (BF – R – IP*3).

Home Run Trends

So, home runs have more than tripled since 1920, both as a proportion of hits and as a proportion of runs scored. That being said, by far the largest proportion of this increase occurred prior to 1960. Runs driven in by home runs (only available from P-I since 1950), as a proportion of all runs scored, are up over 60% since 1950 with the largest proportion of that increase again occurring prior to 1960. Notwithstanding the timing of the increases in those metrics, all three are currently at or very near all-time highs.

So, what has been the effect of this burgeoning increase in long balls? Less than you might suppose. The % of baserunners scoring has held in a tight range of 30%-35% since the late 1930s and is currently in a declining trend since peaking in the mid-1990s. Similar story for runners left on base. Even though home runs ought to be very efficient in clearing the bases, runners left on base has been hovering around 7 per game since the early 1970s. The downward trend since 2005 has more to do with having fewer baserunners overall (recall the recent decline in HIP/9 in the second chart) than with increased efficiency of run scoring via the home run.

So, what does it all mean? I alluded in the title of this post to a zero-sum game. What I meant is that most of the time there is a kind of balance between home runs and strikeouts that usually results in a fairly stable run scoring environment. However, when that balance is thrown out of whack, there can be some fairly sudden and dramatic jolts to run scoring. This phenomenon is illustrated in the chart below.
Strikeout to Homerun Ratio
What I’m showing with the blue line is the ratio between strikeouts and home runs. While there is certainly some whipsawing in the year-to-year fluctuations in that ratio, most of the time, that ratio is running between 5.5 and 8.0 strikeouts per home run. The jolts to run scoring seem to occur when the SO/HR ratio moves into either the Red or Green areas shown on the chart.

For example, SO/HR moved from the green area (favorable to run scoring) in 2006 into the red area (unfavorable) by 2010. The effect? R/9 moved down by more than half a run from 2006 to 2012. Similarly, SO/HR moved from green in 1962 to bright red in 1967, reducing R/9 by over 0.7 and by over a full run when SO/HR shot up over 9 the following year. On the flip side, SO/HR went from red to green from 1946 to 1947, with an immediate increase in R/9 of over one-third of a run. By 1950, SO/HR was well into the green range and R/9 had improved by almost a full run from 1946 levels.

What does 2013 look like? Well, it’s only a month into the season, but SO/HR is pushing 8.0, well into red territory. At this juncture further declines in run scoring seem likely.

To close, here are players with a minimum 200 career HRs and a career SO/HR ratio below 2.0.

Rk Player HR WAR/pos OPS+ SO From To Age G PA R H RBI BB Tm
1 Hank Aaron 755 142.3 155 1383 1954 1976 20-42 3298 13941 2174 3771 2297 1402 MLN-ATL-MIL
2 Babe Ruth 714 163.3 206 1330 1914 1935 19-40 2503 10622 2174 2873 2220 2062 BOS-NYY-BSN
3 Ted Williams 521 123.2 190 709 1939 1960 20-41 2292 9788 1798 2654 1839 2021 BOS
4 Mel Ott 511 107.8 155 896 1926 1947 17-38 2730 11348 1859 2876 1860 1708 NYG
5 Lou Gehrig 493 112.6 179 790 1923 1939 20-36 2164 9663 1888 2721 1992 1508 NYY
6 Albert Pujols 479 91.7 167 793 2001 2013 21-33 1886 8229 1388 2272 1452 1042 STL-LAA
7 Stan Musial 475 128.2 159 696 1941 1963 20-42 3026 12717 1949 3630 1951 1599 STL
8 Joe DiMaggio 361 78.3 155 369 1936 1951 21-36 1736 7673 1390 2214 1537 790 NYY
9 Johnny Mize 359 70.9 158 524 1936 1953 23-40 1883 7370 1118 2011 1337 856 STL-NYG-TOT-NYY
10 Yogi Berra 358 59.3 125 414 1946 1965 21-40 2120 8359 1175 2150 1430 704 NYY-NYM
11 Chuck Klein 300 43.5 137 521 1928 1944 23-39 1753 7170 1168 2076 1201 601 PHI-CHC-TOT
12 Ted Kluszewski 279 32.1 123 365 1947 1961 22-36 1718 6469 848 1766 1028 492 CIN-PIT-TOT-CHW-LAA
13 Hal Trosky 228 30.4 130 440 1933 1946 20-33 1347 5749 835 1561 1012 545 CLE-CHW
14 Sid Gordon 202 38.3 129 356 1941 1955 23-37 1475 5813 735 1415 805 731 NYG-BSN-MLN-PIT-TOT
15 Bill Dickey 202 55.9 127 289 1928 1946 21-39 1789 7064 930 1969 1209 678 NYY
Provided by Baseball-Reference.com: View Play Index Tool Used
Generated 5/2/2013.

At the other end of the spectrum, these are the 200 HR hitters with a SO/HR ratio above 6.0.

Rk Player HR WAR/pos OPS+ SO From To Age G PA R H RBI BB Tm
1 Craig Biggio 291 64.8 112 1753 1988 2007 22-41 2850 12504 1844 3060 1175 1160 HOU
2 Bobby Abreu 287 60.5 129 1819 1996 2012 22-38 2347 9926 1441 2437 1349 1456 HOU-PHI-TOT-NYY-LAA
3 Mike Cameron 278 46.7 106 1901 1995 2011 22-38 1955 7884 1064 1700 968 867 CHW-CIN-SEA-NYM-SDP-MIL-BOS-TOT
4 Derek Jeter 255 72.2 117 1743 1995 2012 21-38 2585 11895 1868 3304 1254 1039 NYY
5 Rick Monday 241 33.1 125 1513 1966 1984 20-38 1986 7162 950 1619 775 924 KCA-OAK-CHC-LAD
6 Ray Lankford 238 37.8 123 1550 1990 2004 23-37 1701 6675 968 1561 874 828 TOT-SDP-STL
7 Rob Deer 230 13.7 109 1409 1984 1996 23-35 1155 4513 578 853 600 575 SFG-MIL-DET-TOT-SDP
8 Travis Fryman 223 34.2 104 1369 1990 2002 21-33 1698 7217 895 1776 1022 602 DET-CLE
9 Devon White 208 47.0 98 1526 1985 2001 22-38 1941 8080 1125 1934 846 541 CAL-TOR-FLA-ARI-LAD-MIL
10 Pete Incaviglia 206 10.2 104 1277 1986 1998 22-34 1284 4677 546 1043 655 360 TEX-DET-HOU-PHI-TOT
Provided by Baseball-Reference.com: View Play Index Tool Used
Generated 5/2/2013.

Among active players, here are the players with the best SO/HR ratio, all below 3.25 (Pujols, at 1.66, is the only player below 3.0).

Rk Player HR WAR/pos OPS+ SO From To Age G PA R H RBI BB Tm
1 Alex Rodriguez 647 115.7 143 2032 1994 2012 18-36 2524 11163 1898 2901 1950 1217 SEA-TEX-NYY
2 Albert Pujols 480 91.8 167 793 2001 2013 21-33 1887 8233 1389 2273 1453 1042 STL-LAA
3 Paul Konerko 426 29.6 121 1287 1997 2013 21-37 2168 8869 1116 2205 1351 873 LAD-TOT-CHW
4 Todd Helton 355 61.6 135 1094 1997 2013 23-39 2136 9056 1364 2431 1355 1299 COL
5 Aramis Ramirez 342 30.2 116 1044 1998 2013 20-35 1836 7603 966 1964 1229 547 PIT-TOT-CHC-MIL
6 Carlos Quentin 139 8.9 119 441 2006 2013 23-30 720 2836 372 614 438 256 ARI-CHW-SDP
Provided by Baseball-Reference.com: View Play Index Tool Used
Generated 5/3/2013.

And, the worst of today’s hackers, all above 6.0, in descending HR order.

Rk Player HR WAR/pos OPS+ SO From To Age G PA R H RBI BB Tm
1 Derek Jeter 255 72.2 117 1743 1995 2012 21-38 2585 11895 1868 3304 1254 1039 NYY
2 Mark Reynolds 189 7.4 111 1145 2007 2013 23-29 877 3543 493 725 523 418 ARI-BAL-CLE
3 Michael Young 178 25.7 104 1171 2000 2013 23-36 1852 8157 1096 2263 990 543 TEX-PHI
4 Alex Gonzalez 157 10.4 80 1152 1998 2013 21-36 1579 6174 658 1405 686 298 FLA-BOS-CIN-TOT-ATL-MIL
5 Brandon Inge 151 19.7 83 1281 2001 2013 24-36 1491 5536 561 1156 644 442 DET-TOT-PIT
6 Jayson Werth 149 22.4 117 965 2002 2013 23-34 1033 4039 561 930 505 483 TOR-LAD-PHI-WSN
7 Jhonny Peralta 147 21.9 100 1086 2003 2013 21-31 1302 5347 635 1276 656 446 CLE-TOT-DET
8 Miguel Olivo 143 8.0 82 1036 2002 2013 23-34 1098 3928 429 891 483 154 CHW-TOT-FLA-KCR-COL-SEA-MIA
9 Jeff Francoeur 138 8.7 94 869 2005 2013 21-29 1170 4799 548 1183 610 242 ATL-TOT-KCR
10 Jonny Gomes 137 4.1 109 844 2003 2013 22-32 902 3121 395 656 413 321 TBD-TBR-CIN-TOT-OAK-BOS
11 Eric Hinske 137 8.4 99 937 2002 2013 24-35 1356 4275 548 943 520 447 TOR-BOS-TBR-TOT-ATL-ARI
12 Lyle Overbay 137 17.2 108 952 2001 2013 24-36 1349 5110 586 1209 593 571 ARI-MIL-TOR-TOT-NYY
Provided by Baseball-Reference.com: View Play Index Tool Used
Generated 5/3/2013.

Of the above group, Gonzalez, Inge, Peralta and Olivo all have a SO/HR ratio above 7.0, with Inge leading the way at a whopping 8.5.

Finally, the top 50 all-time home run hitters (aka the 400 home run club) all have a SO/HR ratio below 5.0, with a lone exception, whom I’m sure most of you will be able to guess. So, here is our 400 HR club in order of SO/HR ratio.

Top 50 HR Hitters

 

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