Why batting average refuses to die
Sabermetrics has spent the better part of forty years arguing that batting average is the worst widely used hitting stat in baseball. The arguments are correct. Bill James made them in the 1980s, the front offices that adopted them in the late 1990s won several championships with rosters built around the insight, and by the mid-2010s every team in MLB had a department of analysts using OPS, wOBA, wRC+, and a dozen other better measurements as the basis of every personnel decision.
Batting average is still on every broadcast graphic. It is still the headline number in every player's biographical entry. The Triple Crown — leading the league in batting average, home runs, and RBI — is still a thing. Sabermetrics won the argument; it did not win the airtime. The interesting question is why a stat that is provably suboptimal has survived four decades of being provably suboptimal.
What's actually wrong with it
Batting average measures the number of hits a player records divided by the number of at-bats they took. The denominator excludes walks, hit-by-pitches, and sacrifices, which means the most patient, plate-discipline-aware hitter in the league and the most impatient hacker in the league can have identical batting averages while contributing very differently to their teams' run scoring. A walk is roughly two-thirds as valuable as a single in run-expectancy terms; the average column pretends it's worth zero.
The numerator is also flat. A single counts the same as a home run. This is the second of batting average's big sins. A power hitter who slugs .550 and a slap hitter who slugs .380 can have the same batting average; the first is producing nearly twice as many bases per at-bat. On-base plus slugging, or OPS, was invented in the 1980s primarily to fix this by adding two stats — on-base percentage and slugging percentage — that respectively repair each of batting average's two flaws.
The empirical case against batting average is overwhelming. Run a regression on hitter contribution to team runs scored, and OPS or wOBA explains the variance roughly twice as well as batting average does. Across a full season, the gap is not subtle. A team built around a high-OBP, moderate-power lineup outscores a team built around a high-batting-average, low-walk lineup by a meaningful number of runs even when the team batting averages are similar.
Why it survives anyway
Three reasons, working together. The first is that batting average is the oldest hitting stat in baseball — it predates even the modern strike zone — and the sport's traditions move slowly. Records that have existed for 150 years are difficult to unwind. The .400 batting average season, the .300 hitter as a career marker, the Triple Crown: all of them are batting-average artifacts, and all of them are too embedded to easily replace.
The second is that batting average is simple. Six characters, no units, intuitive on the scale of zero to one. You can be eight years old and understand what .350 means. OPS requires explaining what OBP and SLG are, and then explaining why those two get added together instead of weighted, and then explaining what wOBA does differently. Each step is reasonable; together they cross a complexity threshold the casual fan won't pay.
The third is that batting average is correlated, loosely, with the actually-useful stats. A player batting .340 is usually a good hitter; the average isn't doing the heavy lifting in the evaluation, but it isn't lying to you, either. A player batting .220 is usually a bad hitter, even if the version where they walk a lot and slug .450 exists and is genuinely valuable. Batting average rarely produces a completely wrong ranking. It just produces a fuzzy ranking, and the broadcasts have decided the fuzziness is an acceptable cost for the legibility.
The cases where it lies the loudest
High-walk, high-power hitters. The cleanest historical example is Adam Dunn, whose career batting average was .237 and whose career OPS was over .850. By the batting average column, Dunn was a below-average hitter for fifteen years. By every other reasonable measurement, he was an above-average power hitter who contributed roughly an All-Star season's worth of value in every healthy year. The columns disagreed about whether he was good. Only one column was right.
The reverse case is the slap-hitting middle infielder. A player batting .300 with a .330 OBP and a .375 SLG looks like a star on a graphic and is, in OPS terms, exactly league average. He's a useful player. He's not the player his batting average implies. The mismatch is biggest in eras when team batting averages run high — the late 1990s, the .280 league environment of the 2000s — and smallest in low-average eras like the present, but it never goes away.
What the better stats actually are
OPS is the easy first step. On-base percentage tells you how often the player avoided making an out; slugging tells you how many bases they got per at-bat. Add them together and you have a number that, at the high end, distinguishes the elite hitters from the merely good ones. League-average OPS sits around .720 most years; anything above .900 is excellent; anything above 1.000 is MVP-level.
Past OPS, the public sabermetrics community has standardized on wOBA (weighted on-base average), which fixes a known minor flaw in OPS — that it treats OBP and SLG as equally important when OBP is actually slightly more valuable — and produces a number on roughly the same scale as OBP for easy reading. Then there's wRC+, which scales everything to league average and park-adjusts. A wRC+ of 100 is league average; 130 is excellent; 160 is historic. These are the columns front offices actually use. Broadcasts still mostly don't, but the better ones are creeping toward at least OPS.
The reason this matters
The stat you use shapes the player you value. A front office that values batting average over OBP will undervalue hitters who walk, draft accordingly, and build a lineup that scores fewer runs than its talent suggests. A free-agent market that prices batting average over OPS will pay a premium for slap hitters and a discount for sluggers, and the teams that recognize the mispricing will sign the sluggers for a discount. This is, more or less, what happened in baseball between 1995 and 2010.
The arbitrage has mostly closed. Front offices have all caught up; the gap is no longer obvious in trade values or contracts. The casual side of the conversation — what the broadcasts say, what the awards reward, what fans remember — is slower. Batting average is the artifact of that slowness. It isn't a wrong stat. It's an early stat that the sport never quite retired, and probably won't until the .300 hitter stops being a thing anyone has heard of.