Estimating Playing Plate Appearances Knowing Team Talent
I just got done writing up my hitter breakouts and need to make several playing time adjustments based on my projected lineup spot. I needed to find out how many plate appearances the lineup spot generated. After about a half dozen lookups, I decided to just create a simple table with the values.
To do this, I compared the preseason projection for runs scored for a team to the actual plate appearances from the leadoff batter. It’s important to use the projected numbers because that’s all that’s available before the season starts. Here is the graph comparing the two values since 2010 (ignoring 2020) that ended up with an r-squared under .10.

While the relationship isn’t significant (r-squared under 0.10, there is one. I was able to create the following formula to estimate the number of plate appearances using the projected runs scored per game and lineup spot.
Lineup Slot Plate Appearances = (10.655 x Proj RS/G +705) – ((Lineup slot – 1) * 17.81)
Using runs scored per game from our projected standings, here are the 2024 estimated plate appearances per lineup slot.
| Team | R/G | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
|---|---|---|---|---|---|---|---|---|---|---|
| Braves | 5.35 | 762 | 744 | 726 | 709 | 691 | 673 | 655 | 637 | 620 |
| Dodgers | 5.12 | 760 | 742 | 724 | 706 | 688 | 671 | 653 | 635 | 617 |
| Astros | 5.05 | 759 | 741 | 723 | 705 | 688 | 670 | 652 | 634 | 616 |
| Yankees | 4.97 | 758 | 740 | 722 | 705 | 687 | 669 | 651 | 633 | 615 |
| Rays | 4.66 | 755 | 737 | 719 | 701 | 683 | 666 | 648 | 630 | 612 |
| Mariners | 4.57 | 754 | 736 | 718 | 700 | 682 | 665 | 647 | 629 | 611 |
| Orioles | 4.73 | 755 | 738 | 720 | 702 | 684 | 666 | 649 | 631 | 613 |
| Phillies | 4.78 | 756 | 738 | 720 | 702 | 685 | 667 | 649 | 631 | 613 |
| Blue Jays | 4.72 | 755 | 737 | 720 | 702 | 684 | 666 | 648 | 631 | 613 |
| Twins | 4.64 | 754 | 737 | 719 | 701 | 683 | 665 | 648 | 630 | 612 |
| Diamondbacks | 4.74 | 756 | 738 | 720 | 702 | 684 | 666 | 649 | 631 | 613 |
| Cardinals | 4.82 | 756 | 739 | 721 | 703 | 685 | 667 | 649 | 632 | 614 |
| Rangers | 4.90 | 757 | 739 | 722 | 704 | 686 | 668 | 650 | 633 | 615 |
| Cubs | 4.66 | 755 | 737 | 719 | 701 | 683 | 666 | 648 | 630 | 612 |
| Red Sox | 4.92 | 757 | 740 | 722 | 704 | 686 | 668 | 651 | 633 | 615 |
| Padres | 4.52 | 753 | 735 | 718 | 700 | 682 | 664 | 646 | 628 | 611 |
| Giants | 4.47 | 753 | 735 | 717 | 699 | 681 | 664 | 646 | 628 | 610 |
| Brewers | 4.59 | 754 | 736 | 718 | 700 | 683 | 665 | 647 | 629 | 611 |
| Marlins | 4.51 | 753 | 735 | 717 | 700 | 682 | 664 | 646 | 628 | 611 |
| Mets | 4.66 | 755 | 737 | 719 | 701 | 683 | 666 | 648 | 630 | 612 |
| Guardians | 4.49 | 753 | 735 | 717 | 699 | 682 | 664 | 646 | 628 | 610 |
| Tigers | 4.46 | 753 | 735 | 717 | 699 | 681 | 663 | 646 | 628 | 610 |
| Reds | 4.85 | 757 | 739 | 721 | 703 | 685 | 668 | 650 | 632 | 614 |
| Angels | 4.77 | 756 | 738 | 720 | 702 | 685 | 667 | 649 | 631 | 613 |
| Pirates | 4.56 | 754 | 736 | 718 | 700 | 682 | 665 | 647 | 629 | 611 |
| Royals | 4.65 | 755 | 737 | 719 | 701 | 683 | 665 | 648 | 630 | 612 |
| Athletics | 4.17 | 749 | 732 | 714 | 696 | 678 | 660 | 643 | 625 | 607 |
| White Sox | 4.31 | 751 | 733 | 715 | 697 | 680 | 662 | 644 | 626 | 608 |
| Nationals | 4.30 | 751 | 733 | 715 | 697 | 680 | 662 | 644 | 626 | 608 |
| Rockies | 4.66 | 755 | 737 | 719 | 701 | 683 | 666 | 648 | 630 | 612 |
A major finding, at least for me, was that the difference between the Braves and A’s is just 13 PA. That’s it. The difference doesn’t seem to matter enough when making quick calculations.
I took the median values from the above table and created the 100% row in the following table. Besides Marcus Semien, hitters aren’t expected to play every game. I added a percentage of plate appearances to create a quick reference chart.
| % of PA | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
|---|---|---|---|---|---|---|---|---|---|
| 100% | 755 | 737 | 719 | 701 | 683 | 666 | 648 | 630 | 612 |
| 90% | 679 | 663 | 647 | 631 | 615 | 599 | 583 | 567 | 551 |
| 80% | 604 | 589 | 575 | 561 | 547 | 532 | 518 | 504 | 490 |
| 70% | 528 | 516 | 503 | 491 | 478 | 466 | 453 | 441 | 428 |
| 60% | 453 | 442 | 431 | 421 | 410 | 399 | 389 | 378 | 367 |
| 50% | 377 | 368 | 359 | 351 | 342 | 333 | 324 | 315 | 306 |
This table assumes that 2024 will have the same run-scoring environment as 2023. In the future, the run-scoring environment must be considered, and don’t assume the above table will work as a reference.
Jeff, one of the authors of the fantasy baseball guide,The Process, writes for RotoGraphs, The Hardball Times, Rotowire, Baseball America, and BaseballHQ. He has been nominated for two SABR Analytics Research Award for Contemporary Analysis and won it in 2013 in tandem with Bill Petti. He has won four FSWA Awards including on for his Mining the News series. He's won Tout Wars three times, LABR twice, and got his first NFBC Main Event win in 2021. Follow him on Twitter @jeffwzimmerman.
Excellent, Jeff, thank you! Again.
(umm, any chance of deriving whether warm weather pitchers’ parks play as more [relatively] neutral in cold April?? 🙂 )
Amazing Jeff!
This got me thinking. A team that scores more runs tends to win more. And a team that wins more also wins more at home and will therefore have fewer plate appearances while batting for only eight innings for most of those wins. And so they will tend to have fewer plate appearances at home overall.
Top 6 run-scoring teams’ Home/Away PAs in 2023:
ATL 3055/3194
LA 3057/3276
TEX 3096/3210
TB 2975/3189
HOU 3016/3237
CHC 3050/3170
This is an average of 18249/19276 = 5.6% more PAs on the road
Bottom 6 run-scoring teams’ Home/Away PAs in 2023:
OAK 2935/3031
CWS 2952/3028
DET 3020/3060
CLE 2965/3131
MIA 2971/3072
NYY(!) 2891/3082
This is an average of 17734/18404 = 3.8% more PAs on the road
The Yankees had the fewest home PAs in MLB last year.
One thing that doesn’t make sense that I see. Who is more likely to make the last out in an inning, Acuna or Ozuna? Ozuna, as when he comes up with 2 outs he’s more likely to actually make out.
So given that leadoff hitters have significantly higher OBPs than 9th hitters, I don’t think it (quite) works to just reduce each slot by 18. (again, close enough for “quick calculations”)
So to get really accurate, this is something you’d want to confirm with a bit of research/actual counting anyway.
You say that OAK has only 13 fewer PAs than Atlanta, but that is just for leadoff hitter. Summing across the whole lineup, ATL would have 113 more PAs. maybe just a missing 1 in the text?
Be honest, Jeff. This was a Gelof Project. 😆