Tampa Bay Rays Show Why Baseball Analytics Need Room for Exceptions

A low home run total, and a familiar debate

The Tampa Bay Rays’ World Series run offers a useful correction to a familiar debate: a low home run total doesn’t mean analytics have failed. It may mean teams are applying them well enough to recognize when a player’s strengths call for a different approach. The distinction matters because analytics is often described as a fixed set of instructions, when its real purpose is to help teams choose among options.

The Rays and Milwaukee Brewers hit four home runs combined in the Fall Classic, the fewest in a World Series since 1985. That unusual result prompted claims that small ball had returned and the analytics era was fading. Rob Mains has argued that the series was an outlier, not evidence of a wider shift. My read is that the more telling lesson lies in how both clubs tailored decisions to their players. One short series can show what happened; it can’t, by itself, establish that the sport has changed direction.

Jarrett Seidler made a similar point about Milwaukee in his front office rankings. “I don’t think it’s so much that they’re zagging against pulled fly balls—this is the team that spent a first-round draft pick last year on Andrew Fischer—but that they are perfectly willing to maximize skill sets which just aren’t going to include that.” A team can value power and still build opportunities for hitters whose best route to success looks different. That flexibility doesn’t refute an emphasis on power; it puts that emphasis in context.

Analytics works best with room for judgment

Baseball has formal rules, but its habits and conventions can carry just as much force. Traditional etiquette discourages stealing bases with a large lead or celebrating a home run too demonstratively. The analytical movement challenged many such assumptions, yet it also produced its own shorthand: seek strikeouts, discount batting average unless it helps on-base percentage, and avoid bunts or intentional walks. Such summaries are easy to repeat because they turn complicated tradeoffs into memorable rules.

Those ideas can describe useful tendencies. They become less useful when treated as commands. The point of analysis is to find an advantage, and the right advantage depends on the player, the matchup and the game in front of a team. A tactic that makes sense in general can still be wrong for a particular roster. Analysis gives decision-makers a way to test conventional wisdom; judgment is what keeps the test from becoming another convention.

The Rays’ choices illustrate that distinction. Pulling the ball in the air is often a productive way to generate power, but it may not suit Chandler Simpson. For Johnny DeLuca, meanwhile, that approach helped produce a .429 slugging percentage despite Statcast indicators that offered little support for it. The same broad principle can lead to different decisions because the players are different. A team that insists every hitter adopt the same swing plan may be following a tidy theory while ignoring the evidence in front of it.

When the usual limits don’t fit

Pitching decisions offer another example. Opponents tend to gain an advantage the third time through a batting order, but that pattern doesn’t mean a starter must leave at a fixed point. Drew Rasmussen faced 71 batters across three starts against the Yankees and Guardians. When an ace is pitching well, sticking to a rigid innings limit can cost a team the benefit of the performance in front of it. The general tendency still matters; the question is whether it outweighs what the pitcher is doing that day.

Pitch selection also depends on execution and matchup. Changeups are generally most effective against opposite-handed hitters, but a pitcher who can get same-handed batters out with the pitch has a reason to keep using it. The practical question isn’t whether a tactic matches the standard description. It’s whether it works for the player using it. And yet, one successful matchup doesn’t automatically make a tactic right in every situation; teams still have to weigh the opponent and the cost of sticking with a plan.

What the series suggests about the next decision

That’s the thread connecting the Rays’ approach to the broader analytics debate. The numbers can identify tendencies and help teams make better choices, but they don’t remove the need to judge individual skills. A World Series with four home runs doesn’t herald the return of one old style. It shows that teams can win by making the most of the players they have—and that the strongest playbook leaves room to adapt.

This is more significant than it looks: the useful measure of analytics isn’t whether every game produces the outcome a model might favor, but whether a club can recognize when its own players call for a different decision. If you’re working in this space, that’s the operational challenge: turning general evidence into choices that fit a specific roster without mistaking a tendency for a law.

(And this is the part most people overlook.) A low scoring total is an outcome, not a strategy. Four home runs can prompt a debate, but they can’t settle whether baseball is moving toward or away from power. The more durable lesson is simpler. Adaptation matters.