Power Rating

How it works

Power Rating is the team question, and its answer is on the scoreboard's own scale: the margin a team would be expected to win or lose by against an average opponent on neutral ground. Lakers +4.2 means four points better than average, a night in, a night out. Ask about a matchup and the answer is built from the two teams' ratings on the spot — the gap between them, a measured home advantage, and the win probability that follows. No matchup is ever precomputed; the rating is stored, the forecast is arithmetic.

What goes into it depends on the league, because the leagues taught us different things. In baseball and football the rating is a blend of two things every fan already watches — the record and the scoring margins — because that blend, and nothing fancier, is what survived testing, and each sport taught the margin half its own lesson. In baseball, run differential flatly does not work: it told us nothing the standings didn't, and the signal only appeared when we rebuilt expected runs from the ingredients — the hits, walks and homers on both sides — which strips out the luck of when hits happen to bunch together. A baseball matchup then counts the one player who changes every game: each side's starting pitcher, the announced one before the game, scored from his own record this season and last. A strong starter against a weak one moves the forecast by several points of win probability, and an unannounced starter is priced as an average one, with the answer saying so. In football, any points past a two-score lead turned out to carry no information at all, so blowout padding is capped out. In basketball the rating has moved past that blend and is built from the players. Every player carries his own measured number — how much his team's margin improves for every 48 minutes he is on the floor, judged against an average player, from two seasons of box scores — and the team's rating is the sum of those numbers over the players expected to play, each weighted by the minutes he is expected to get. In season that is the lineup that played last time out, and anyone the injury report marks Out is dropped first — checked again against the latest report when you ask about a game, so a player ruled out in the afternoon is out of the evening's answer. Tested against five seasons of the league's own pre-game injury reports, dropping those players closed about a third of the rating's gap to the betting line on the newest season. So an NBA rating answers for a named lineup, the answer says which lineup it assumed and who is missing, and the record and the margins appear beside it as context about the team rather than ingredients of the number.

Just as telling is what was tested and left out, and here one distinction matters. We checked — twice, from both directions — whether knowing how much of a roster's playing time returns makes a team more predictable across an offseason. It does not, in any sport, so DataBaller still won't tell you a team is safe because "they kept the core together" — that sentence sounds like analysis, and we measured it: it isn't. Summing the roster's own measured impacts is a different measurement of a different thing, and it passed its own test: "the player they lost was worth four points a game to that sum" is a fact about an NBA rating, while "they return 80% of their minutes" explains nothing about any rating. One guard rides with those player numbers. They exist to be summed, and on their own they are compressed and flatter role players on strong teams — so a player's own impact number is never a ranking of how good he is, and DataBaller won't present one as if it were.

Two honest limits ride along, and the first splits by league. Between seasons and in the first weeks of a new one, the baseball and football ratings are last season's team, discounted and projected forward — a roster remade over the summer will be mis-rated until its games say otherwise, and answers say "carried from last season" when that's what the number is. The basketball rating is the opposite: it sums the current roster at last season's minutes, so it describes the team the front office built over the summer — a club that lost its best player loses his number, a club that lost its bench loses almost nothing, and a player marked Out leaves the sum as soon as the report says so. What it cannot know is how the new pieces fit or how the minutes will be shared, and the confidence beside it says as much. The second limit holds everywhere: the edge over just reading the standings is real but small — most single games are closer to a coin flip than anyone likes to admit, and when the model says 58%, the honest answer is 58%, not a lock of the night.