Author: Leo Tesler

leotesler2026@u.northwestern.edu

There are a plethora of statistics available today to help fully explain how productive a batter was across an entire season of play. Stats like wRC+, wOBA, and OPS+ weigh and combine every contribution a batter makes in order to spit out a singular number that defines that batter’s value as precisely as possible. Advanced metrics like xBA, xSLG, and Barrel%, use the data collected on a batter’s batted balls to predict their outcomes across that time frame, and serve as guesses as to how they might fare in the future.

As great as those stats are, I wanted to dive even deeper into the bare bones of how runs are produced in baseball. I broke down a hitter’s performance by one of the simplest measures of offense we have: bases.

Total bases, or TB, gives us the amount of bases a batter gains on his hits, calculated by adding singles to two times doubles, to three times triples, and to four times home runs. It’s a good measure of how much raw offense a player contributes, but not specific enough. For one thing, it does not include walks or hit by pitches, an essential component of many offensive juggernaut’s gains.

But more crucially, it does not factor in the amount of bases gained by the batter moving over runners on base. A single with the bases empty and a single with the bases loaded are worth the same in total bases’ eyes, where in reality a single with the bases loaded adds much more to a team’s chances of winning than a single with nobody on does.

Additionally, total bases is a counting stat, not factoring in the amount of bases a player stood to gain as part of its calculation. Batters who come up to the plate more tend to have more total bases, and although total bases doesn’t include this, batters who bat towards the middle of the order tend to come up more with runners on base.

With all of that in mind, I took data from Baseball Savant on every final pitch of a plate appearance from 2023, and calculated both how many bases were gained by the batter on that event, and how many bases were available to gain by the batter when the event took place.

For example, if a batter comes up with the bases empty and hits a double, he gains 2 bases out of the available 4. If a batter comes up with the bases loaded and hits a grand slam, he gains 10 bases out of the available 10. And if a batter comes up with a runner on second and hits a sacrifice fly to move the runner over, he gains 1 base out of the available 6.

Then, I calculated base gain rate (Base Gain %) by dividing the number of bases a batter gained by the number of bases that were available for him to gain. Below is a table of the top 50 players by base gain rate from 2023, out of batters who had an above-average amount of bases available.

	Batter	Bases gained	Bases available	Base gain rate
1	Yordan Alvarez	385	4890	7.87%
2	Royce Lewis	183	2370	7.72%
3	Aaron Judge	336	4480	7.50%
4	Shohei Ohtani	424	5770	7.35%
5	Matt Olson	518	7080	7.32%
6	Corey Seager	377	5240	7.19%
7	Mookie Betts	495	6890	7.18%
8	Matt Wallner	179	2500	7.16%
9	Freddie Freeman	503	7130	7.05%
10	Ronald Acuna	514	7300	7.04%
11	Marcell Ozuna	413	5890	7.01%
12	J.D. Martinez	331	4730	7.00%
13	Juan Soto	477	6950	6.86%
14	Max Muncy	381	5740	6.64%
15	Nolan Jones	278	4190	6.63%
16	Danny Jansen	198	2990	6.62%
17	Yandy Diaz	394	5970	6.60%
18	Kyle Tucker	435	6630	6.56%
19	Isaac Paredes	373	5690	6.56%
20	Jonah Heim	327	4990	6.55%
21	Josh Lowe	323	4960	6.51%
22	Cody Bellinger	357	5490	6.50%
23	Jose Altuve	264	4070	6.49%
24	Mitch Garver	220	3420	6.43%
25	Christopher Morel	274	4260	6.43%
26	Sean Murphy	280	4370	6.41%
27	Josh Naylor	310	4840	6.40%
28	Adam Duvall	221	3510	6.30%
29	Stone Garrett	170	2700	6.30%
30	Pete Alonso	406	6460	6.28%
31	Adolis Garcia	395	6320	6.25%
32	Kyle Schwarber	445	7120	6.25%
33	Will Benson	205	3280	6.25%
34	Francisco Lindor	426	6820	6.25%
35	J.P. Crawford	397	6360	6.24%
36	Jake Burger	337	5400	6.24%
37	Ozzie Albies	407	6530	6.23%
38	Chas McCormick	284	4560	6.23%
39	Kerry Carpenter	281	4530	6.20%
40	Brandon Marsh	290	4680	6.20%
41	Triston Casas	309	4990	6.19%
42	Jorge Polanco	209	3380	6.18%
43	Matt McLain	249	4040	6.16%
44	Nolan Gorman	285	4630	6.16%
45	Yainer Diaz	231	3760	6.14%
46	Trevor Larnach	129	2100	6.14%
47	Julio Rodriguez	429	7000	6.13%
48	Gunnar Henderson	379	6190	6.12%
49	Wilmer Flores	275	4500	6.11%
50	Gary Sanchez	162	2660	6.09%

At the top, there are plenty of notable names, such as Yordan Álvarez, Aaron Judge, Shohei Ohtani, Corey Seager, and Mookie Betts. But scattered around those superstars are the likes of Royce Lewis, Matt Wallner, Nolan Jones, and Isaac Paredes; good players, but not considered to be elite-tier hitters by most of the baseball world.

So is base gain rate a fraudulent measure of offense? It’s a valid question, especially since the top 50 players it measures differ by only about 2 percentage points. Below, I graphed the relationship between each player’s base gain rate and wRC+ from 2023, to see how my metric stacks up against a more respected stat:

As the chart shows, there is a pretty strong, positive correlation between the two, with some outliers mainly consisting of unqualified batters. So how come players like Royce Lewis don’t measure up in traditional offensive measurements?

An easy answer is lineup construction. As I mentioned before, players who bat lower in the lineup don’t get as many opportunities to gain bases, and players at either end of the lineup tend to come up less with runners on base than players who bat in the middle of the lineup. Lewis, at #2 on the list, had less than half of the opportunities to gain bases than the one man ahead of him, Yordan Álvarez, but he came through when he got the chance.

Players like Lewis who gain a lot of bases in relatively few opportunities should get more opportunities to gain bases. In his 58 games last season, Lewis moved around a lot in the order, staying mostly in the three-, five-, and six-holes but often finding himself batting behind struggling hitters. Of course, the main culprit is all the games he missed due to his ACL injury, but it definitely didn’t help to have Jorge Polanco and Carlos Correa, who didn’t get on base at an outstanding clip, batting in front of him most of the time.

Below is a chart of every qualified batter’s base gain rate, plotted by the bases that were available to gain. Both values have been z-scored so they can be put on the same scale. 

In the top right quadrant are your stars; players who will contribute to the offense no matter where you bat them and no matter who is in front of them. In the bottom left quadrant are your stereotypical bottom-of-the-order hitters; guys who probably aren’t expected to contribute, aren’t given opportunities to, and perform as expected.

The bottom right quadrant is where things get interesting. Here are your Royce Lewises, the guys who don’t get much of a chance to contribute to the offense but do anyway, and are likely better suited for either different spots in the lineup, or more opportunities in the first place.

The only remaining quadrant is the top left, filled with hitters who are given a lot of opportunities for no good reason. This quadrant should mostly be populated by regulars on bad or rebuilding teams that simply do not have a better option. If a contender has one of these guys clogging up their lineup and not producing as much offense as they expected, they should look to put him in a different role.

Although it breaks down offensive production to its rawest, simplest component, base gain rate is no more of an end-all, be-all stat than any other leading metric that gets cited in front offices or popular baseball discourse today. But it does provide a window into the consequences of teams’ lineup construction, as well as suggestions for better optimization.