In the last couple of weeks there have been questions about the batting order. And historically there has much debate about who, and what kind of batter should bat in certain spots in the order.
So in response to those questions, and specifically about who is on base and what positions are run producers, this post will likely over-whelm you with more than enough numbers to play with.
But first a disclaimer. This data is based on the 2015 Game Day data and my summary of it. From prior experience, there are some errors/problems with the Game day data. And there is always the chance of a logic error in one of my programs. So if these numbers are not exactly the same as the numbers elsewhere, that should not be a surprise. But they should be more than good enough to provide some food for thought.
Let me first start with a description of the two sets of data. This first set of tables shows the distribution of who is on base by order in the lineup and is broken out by League, along with a table for just the Nats. Below that are comparable tables for RBIs by Batting Order.
What Bases are Occupied
The key to interpreting the columns in this first set of tables is hopefully simple once you understand the pattern.
- Order, PAs should be self-explanatory
- The LeadOff and ___ column add up to the number of times the position comes up with no one on base. I separated out those cases where that position in the order was leading off an inning vs. there simply was no one on base. Obviously, batting order 1 has way more leading off an inning (the first inning in every game for every team).
- The other column headers denote who is on base. For example:
- 123 is bases loaded
- 1__ is a man on first
- 1_3 is first and third
- and so on
- And RISP is the total of all the columns with a 2 (man on second) or 3 (man on third) in the column header.
- The data cells contain the count on the first line, and the percent of PAs on the second line.
Two things jump out at me when I look at these tables:
- Not much difference, overall, between the AL and NL. So yet another factoid that the DH does not have much of an impact on opportunities.
- Looking at the count of PAs by order (focus on the table for the Nats as the differences are easier to conceptualize), seems to say that deciding to bat someone 4th vs 3rd (as just one example) to get them more PAs/ABs seems to not be a terribly valid argument. Is roughtly .6 PAs more a week worth it? And note how much more often 4th leads off an inning.
American League
| ORDER | PAS | LeadOff | ___ | RISP | 123 | 12_ | 1_3 | 1__ | _23 | _2_ | __3 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 11,228 | 4,528 40.3% |
3,731 33.2% |
1,704 15.2% |
205 1.8% |
543 4.8% |
179 1.6% |
1,265 11.3% |
138 1.2% |
434 3.9% |
205 1.8% |
| 2 | 10,932 | 1,776 16.2% |
5,597 51.2% |
1,872 17.1% |
198 1.8% |
594 5.4% |
205 1.9% |
1,687 15.4% |
128 1.2% |
517 4.7% |
230 2.1% |
| 3 | 10,700 | 1,867 17.4% |
5,259 49.1% |
1,871 17.5% |
209 2.0% |
622 5.8% |
235 2.2% |
1,703 15.9% |
115 1.1% |
469 4.4% |
221 2.1% |
| 4 | 10,440 | 2,625 25.1% |
3,890 37.3% |
2,169 20.8% |
244 2.3% |
738 7.1% |
250 2.4% |
1,756 16.8% |
119 1.1% |
566 5.4% |
252 2.4% |
| 5 | 10,208 | 2,406 23.6% |
4,373 42.8% |
2,043 20.0% |
264 2.6% |
721 7.1% |
264 2.6% |
1,386 13.6% |
150 1.5% |
462 4.5% |
182 1.8% |
| 6 | 9,965 | 2,079 20.9% |
4,625 46.4% |
1,784 17.9% |
238 2.4% |
582 5.8% |
238 2.4% |
1,477 14.8% |
129 1.3% |
424 4.3% |
173 1.7% |
| 7 | 9,684 | 2,222 22.9% |
4,259 44.0% |
1,744 18.0% |
196 2.0% |
621 6.4% |
174 1.8% |
1,459 15.1% |
125 1.3% |
444 4.6% |
184 1.9% |
| 8 | 9,412 | 2,157 22.9% |
4,048 43.0% |
1,794 19.1% |
227 2.4% |
535 5.7% |
228 2.4% |
1,413 15.0% |
149 1.6% |
469 5.0% |
186 2.0% |
| 9 | 9,090 | 2,053 22.6% |
3,946 43.4% |
1,771 19.5% |
208 2.3% |
570 6.3% |
223 2.5% |
1,320 14.5% |
130 1.4% |
440 4.8% |
200 2.2% |
National League
| ORDER | PAS | LeadOff | ___ | RISP | 123 | 12_ | 1_3 | 1__ | _23 | _2_ | __3 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 11,248 | 4,676 41.6% |
3,785 33.7% |
1,696 15.1% |
157 1.4% |
418 3.7% |
170 1.5% |
1,091 9.7% |
162 1.4% |
598 5.3% |
191 1.7% |
| 2 | 10,989 | 1,904 17.3% |
5,506 50.1% |
1,805 16.4% |
189 1.7% |
611 5.6% |
178 1.6% |
1,774 16.1% |
100 0.9% |
516 4.7% |
211 1.9% |
| 3 | 10,738 | 1,775 16.5% |
5,311 49.5% |
1,863 17.3% |
170 1.6% |
629 5.9% |
220 2.0% |
1,789 16.7% |
107 1.0% |
475 4.4% |
262 2.4% |
| 4 | 10,518 | 2,566 24.4% |
3,831 36.4% |
2,294 21.8% |
240 2.3% |
799 7.6% |
264 2.5% |
1,827 17.4% |
116 1.1% |
609 5.8% |
266 2.5% |
| 5 | 10,269 | 2,377 23.1% |
4,249 41.4% |
2,202 21.4% |
255 2.5% |
789 7.7% |
327 3.2% |
1,441 14.0% |
147 1.4% |
474 4.6% |
210 2.0% |
| 6 | 10,010 | 2,192 21.9% |
4,517 45.1% |
1,938 19.4% |
268 2.7% |
630 6.3% |
216 2.2% |
1,363 13.6% |
149 1.5% |
475 4.7% |
200 2.0% |
| 7 | 9,721 | 2,172 22.3% |
4,249 43.7% |
1,844 19.0% |
213 2.2% |
569 5.9% |
217 2.2% |
1,456 15.0% |
126 1.3% |
506 5.2% |
213 2.2% |
| 8 | 9,407 | 2,136 22.7% |
4,098 43.6% |
1,712 18.2% |
200 2.1% |
619 6.6% |
225 2.4% |
1,461 15.5% |
80 0.9% |
402 4.3% |
186 2.0% |
| 9 | 9,112 | 2,027 22.2% |
3,840 42.1% |
1,789 19.6% |
213 2.3% |
659 7.2% |
203 2.2% |
1,456 16.0% |
105 1.2% |
445 4.9% |
164 1.8% |
Nationals
| ORDER | PAS | LeadOff | ___ | RISP | 123 | 12_ | 1_3 | 1__ | _23 | _2_ | __3 |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 752 | 306 40.7% |
264 35.1% |
116 15.4% |
7 0.9% |
30 4.0% |
11 1.5% |
66 8.8% |
7 0.9% |
46 6.1% |
15 2.0% |
| 2 | 735 | 115 15.6% |
373 50.7% |
125 17.0% |
13 1.8% |
40 5.4% |
17 2.3% |
122 16.6% |
7 1.0% |
37 5.0% |
11 1.5% |
| 3 | 717 | 132 18.4% |
335 46.7% |
119 16.6% |
10 1.4% |
47 6.6% |
9 1.3% |
131 18.3% |
5 0.7% |
30 4.2% |
18 2.5% |
| 4 | 702 | 169 24.1% |
249 35.5% |
159 22.6% |
17 2.4% |
67 9.5% |
17 2.4% |
125 17.8% |
5 0.7% |
37 5.3% |
16 2.3% |
| 5 | 681 | 154 22.6% |
271 39.8% |
159 23.3% |
19 2.8% |
65 9.5% |
27 4.0% |
97 14.2% |
12 1.8% |
25 3.7% |
11 1.6% |
| 6 | 664 | 138 20.8% |
290 43.7% |
147 22.1% |
21 3.2% |
37 5.6% |
19 2.9% |
89 13.4% |
10 1.5% |
47 7.1% |
13 2.0% |
| 7 | 648 | 141 21.8% |
289 44.6% |
111 17.1% |
10 1.5% |
42 6.5% |
8 1.2% |
107 16.5% |
10 1.5% |
23 3.5% |
18 2.8% |
| 8 | 626 | 143 22.8% |
289 46.2% |
113 18.1% |
15 2.4% |
43 6.9% |
21 3.4% |
81 12.9% |
6 1.0% |
20 3.2% |
8 1.3% |
| 9 | 604 | 141 23.3% |
254 42.1% |
111 18.4% |
9 1.5% |
42 7.0% |
18 3.0% |
98 16.2% |
2 0.3% |
32 5.3% |
8 1.3% |
Runs Produced by Batting Order
These tables show the runs produced by each batting order position. I label them RBIs, but they technically aren’t RBIs as they include runs scored due to errors, doubles plays, and so on. And the total runs produced by HRs and Solo HRs were split out from the RBIs column. Note that the HRs column includes the Solo HRs. The percentages are based on total PAs for that position.
And if you want to break things out yourself, the bottom of the post includes a link to download all of these tables as CSV files.
What jumps out at me when I look at this is how much better the Nats were in 2015 in producing runs (per PA) by the middle of the order – probably greatly influenced by Bryce Harper.
And thanks to Brandon at ImageWorksCreative, internal links now work – in other works you can click instead of scrolling to see the tables for OnBase by Batting Order.
American league
| Order | PAs | RBIs | HR RBIs | Solo HRs | RBIs per PA | HR RBIs per PA |
|---|---|---|---|---|---|---|
| 1 | 11,228 | 995 | 320 | 157 | 0.089 | 0.029 |
| 2 | 10,932 | 1,203 | 501 | 204 | 0.110 | 0.046 |
| 3 | 10,700 | 1,443 | 601 | 220 | 0.135 | 0.056 |
| 4 | 10,440 | 1,496 | 681 | 203 | 0.143 | 0.065 |
| 5 | 10,208 | 1,315 | 521 | 186 | 0.129 | 0.051 |
| 6 | 9,965 | 1,185 | 505 | 177 | 0.119 | 0.051 |
| 7 | 9,684 | 1,044 | 375 | 157 | 0.108 | 0.039 |
| 8 | 9,412 | 970 | 322 | 129 | 0.103 | 0.034 |
| 9 | 9,090 | 885 | 240 | 95 | 0.097 | 0.026 |
National League
| Order | PAs | RBIs | HR RBIs | Solo HRs | RBIs per PA | HR RBIs per PA |
|---|---|---|---|---|---|---|
| 1 | 11,248 | 962 | 316 | 164 | 0.086 | 0.028 |
| 2 | 10,989 | 1,123 | 412 | 156 | 0.102 | 0.037 |
| 3 | 10,738 | 1,439 | 609 | 187 | 0.134 | 0.057 |
| 4 | 10,518 | 1,569 | 652 | 224 | 0.149 | 0.062 |
| 5 | 10,269 | 1,388 | 566 | 210 | 0.135 | 0.055 |
| 6 | 10,010 | 1,085 | 347 | 138 | 0.108 | 0.035 |
| 7 | 9,721 | 1,023 | 329 | 130 | 0.105 | 0.034 |
| 8 | 9,407 | 890 | 267 | 85 | 0.095 | 0.028 |
| 9 | 9,112 | 628 | 147 | 62 | 0.069 | 0.016 |
Nationals
| Order | PAs | RBIs | HR RBIs | Solo HRs | RBIs per PA | HR RBIs per PA |
|---|---|---|---|---|---|---|
| 1 | 752 | 67 | 26 | 14 | 0.089 | 0.035 |
| 2 | 735 | 59 | 13 | 7 | 0.080 | 0.018 |
| 3 | 717 | 73 | 40 | 16 | 0.102 | 0.056 |
| 4 | 702 | 124 | 61 | 23 | 0.177 | 0.087 |
| 5 | 681 | 102 | 35 | 14 | 0.150 | 0.051 |
| 6 | 664 | 105 | 39 | 11 | 0.158 | 0.059 |
| 7 | 648 | 63 | 29 | 9 | 0.097 | 0.045 |
| 8 | 626 | 75 | 25 | 6 | 0.120 | 0.040 |
| 9 | 604 | 35 | 11 | 5 | 0.058 | 0.018 |
So at this point, we will leave it to our readers to weigh in with their thoughts.
And to download CSV (Comma Separated Values – which can be opened in Excel) files for the data in the above tables:
