In The Lab: Another Look at Offensive Efficiency
I might be one of the few writers here that has no experience in radio, but I remember my old journalism classes and one of the things they taught us is that the average audience turns over every 15 to 20 minutes. That was literally in the last century and I’m sure that ballpark has changed some, but the concept is still very much the same. I try to take the same concept to the writing game. There will be new readers all the time, so it pays off to revisit concepts every now and then.
Offensive efficiency is a very simple stat. You simply take the total percentage of base runners that have crossed home plate. Obviously, it’s not absolutely perfect. You get hitters that reach on an error and baseball-reference.com doesn’t keep track of those. It is what we in the stats world would call noise where we assume it is fairly constant throughout the 30 teams and simply move on. So, you add up hits, walks, and hit by pitches and then divide runs into that.
The results are important, but the why is probably more important. The main reason we do it is to guard against what we might call regional bias. In other words, we watch the Astros and mainly the Astros. So, it often seems they are bad at leaving runners on base and on third with less than two outs in particular. Are they really bad in comparison with the rest of the league? That’s where offensive efficiency comes in.
Of course, tracking this data tells us many other things. Where do the Astros rank in total base runners? Where do they rank in walks? Is this a good offense overall? They were one of the worst offenses in the AL last season and that was particularly true in terms of offensive efficiency. They ranked 13th out of 15 AL teams in that department and it got both hitting coaches fired. So, are the new hitting coaches doing any better? The stats below are the team stats coming into the fourth of July.
| Runs | Hits | Walks | HBP | TBR | EFF | |
| Yankees | 422 | 679 | 343 | 17 | 1039 | .406 |
| Twins | 431 | 739 | 292 | 54 | 1085 | .399 |
| White Sox | 418 | 702 | 298 | 52 | 1052 | .397 |
| Orioles | 406 | 704 | 339 | 23 | 1066 | .381 |
| Astros | 401 | 728 | 298 | 39 | 1065 | .377 |
| Angels | 393 | 712 | 290 | 54 | 1056 | .372 |
| Athletics | 406 | 747 | 326 | 32 | 1105 | .367 |
| Rays | 388 | 738 | 306 | 36 | 1080 | .359 |
| Tigers | 370 | 693 | 318 | 29 | 1040 | .356 |
| Blue Jays | 356 | 730 | 244 | 35 | 1012 | .353 |
| Royals | 363 | 714 | 285 | 32 | 1031 | .352 |
| Mariners | 357 | 679 | 298 | 57 | 1034 | .345 |
| Guardians | 355 | 669 | 333 | 29 | 1031 | .344 |
| Red Sox | 342 | 701 | 249 | 44 | 994 | .344 |
| Rangers | 364 | 723 | 293 | 44 | 1060 | .343 |
| Average | 385 | 711 | 301 | 38 | 1050 | .367 |
The average is pretty telling here and we can break this down with all kinds of regression analysis, but we should probably pair this down and keep it simple. The Astros have an above average offense in the American League. They are above average in runs scored, hits, total base runners, and offensive efficiency. They only really lag in one major category and that is walks. Of course, lagging needs to be put in air quotes. They are more or less league average in that category.
Numbers are always the easiest part of statistical analysis. The whys and what fors are the hardest. Are the gains primarily because of the hitting coaches or are they because Yordan Alvarez is healthy and playing the best baseball of his career? Most would probably point towards the latter. In fact, if you do nothing but look at Alvarez and Christian Walker then you probably have seen all of the gains the Astros have made between 2025 and 2026.
Do the hitting coaches deserve credit for that? That’s a harder question. Is Walker’s resurgence due to adjustments he has made or simple regression to the mean? It’s always some of both in these instances. In other words, Walker was probably not going to be as bad regardless of who the hitting coach was. Suffice it to say, this is the Walker the Astros thought they were signing. When you couple that with Alvarez and a healthy Isaac Paredes and you have the bulk of your offense right there.
Our default expectation is always a regression to the mean. In other words, teams will eventually tighten and get closer to the average. In the Astros case, the expectation is some form of slowing down. Of course, the components can change and if they do then the results can change. Adding Lamont Wade and Taylor Trammel to the starting lineup could change that some. A trade down the line could change that some as well. Getting Jeremy Pena back and hitting the way he was before he went on IR could change that calculus some.
The worry is that both the Texas Rangers and Seattle Mariners are due for positive regression. The Astros have worked very hard to get back into the race, but their finish depends not only on their ability to keep their head above water but on the other teams in the AL West continuing to struggle. A large part of that is going to be to see what the other teams in the division do at the trade deadline.
Next time around we will look at the pitching side of this equation. We know (or think we know) that the Astros are one of the worst pitching teams in baseball. Is that simply a function of allowing too many base runners or have they been inefficient in limiting those base runners from crossing home plate? Stay tuned for the next lab. In the meantime, what do you think is the best way to avoid falling back to the pack? What changes would you make?
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