Field goal percentage is the stat we all learned first, and it's the one that quietly lies to us the most. It treats a wide-open dunk and a step-back three as the same event, and it pretends free throws never happened. True Shooting percentage fixes all three problems at once — and once you start reading it, the box score never looks the same.

Why field goal percentage lies

Imagine two guards. One goes 8-for-16 on twos for 16 points. The other goes 6-for-16, but all six are threes, for 18 points. Field goal percentage says the first guard (50%) is the better shooter than the second (37.5%). The scoreboard disagrees: the second guard produced more points on the same number of shots. Field goal percentage can't see the extra point a three is worth.

Then there's the foul line. A player who drives, draws contact, and sinks two free throws has produced two points and taken zero "field goal attempts." As far as FG% is concerned, that trip down the floor is invisible. For players who live at the line, that's a huge chunk of their scoring erased from the efficiency conversation entirely.

The True Shooting formula

True Shooting percentage rolls twos, threes, and free throws into a single number that answers one question: how many points did this player generate per shooting possession? The formula looks intimidating and is actually simple:

True Shooting %TS% = PTS / (2 × (FGA + 0.44 × FTA))

The denominator estimates how many scoring possessions a player used. Every field goal attempt is one. The 0.44 coefficient converts free throw attempts into possession-equivalents — most trips to the line are two shots, but some are one-and-ones, three-shot fouls, or and-ones, and 0.44 is the league's long-run average cost. Multiply by two because a "normal" possession that ends in a made two-pointer yields two points, and we want 50% to mean "league-average two-point efficiency."

Here's the same math with a real line. This past season the league's leading scorer, Luka Dončić, averaged 33.5 points on 22.8 field goal attempts and 10.1 free throw attempts:

Worked example — Luka Dončić, 2025-2633.5 / (2 × (22.8 + 0.44 × 10.1)) = 33.5 / (2 × 27.24) = 61.5%

That matches the .616 the NBA's own data reports (the tiny gap is rounding on the per-game inputs). His field goal percentage, by contrast, was a pedestrian-looking 47.6%. Those ten free throws a night — invisible to FG% — are doing a lot of work, and that's exactly the point.

True Shooting %: PTS / (2 × (FGA + 0.44 × FTA)). Enable JavaScript to use the interactive calculator, or try our calculators page.

Bar chart of the NBA's most efficient high-volume scorers by True Shooting percentage, led by Nikola Jokić at 67.0% and Shai Gilgeous-Alexander at 66.5%, against a league average of 58.6%.
The most efficient high-volume scorers (≥12 FGA per game) in 2025-26. Source: NBA Stats API via nba_api · 2025-26 · retrieved June 2026.

What the leaderboard actually shows

Among the 151 players who qualified as rotation regulars, the average True Shooting mark was 58.6%. That's your reference line: anything north of it is above-average scoring efficiency, and the gap between 58% and 65% is enormous over a full season.

At the top sits Nikola Jokić at a frankly absurd 67.0% on real volume, with Shai Gilgeous-Alexander right behind at 66.5% while carrying a 31-point-per-game scoring load. What's instructive is how different players get there. Look at the routes:

Selected high-volume scorers — efficiency by route. Source: NBA Stats API via nba_api, retrieved June 2026.
PlayerPTSFGAFTAFG%eFG%TS%
Nikola Jokić27.717.47.456.961.867.0
Shai Gilgeous-Alexander31.119.49.055.359.766.5
Austin Reaves23.314.97.349.056.764.1
Kevin Durant26.017.66.052.058.864.1
Kawhi Leonard27.919.46.450.557.362.9
Anthony Edwards28.820.27.248.957.261.7

Notice Austin Reaves and Kevin Durant landing at an identical 64.1% TS from completely different places. Durant gets there on raw shotmaking — a 52% field goal percentage that's elite for a high-volume wing. Reaves gets there at just 49% from the field, but he leans on threes (look at the gap between his FG% and eFG%) and gets to the line 7.3 times a night. Same destination, opposite maps. True Shooting is the only one of these columns that sees both routes as equally valuable, because on the scoreboard they are.

67.0% Nikola Jokić's 2025-26 True Shooting — on 17-plus field goal attempts a night. League average among qualified players: 58.6%.

Where True Shooting still falls short

True Shooting is a better efficiency stat, not a perfect one, and it's worth being honest about the edges. It says nothing about shot difficulty: a player feasting on wide-open catch-and-shoot looks and one creating contested shots off the dribble can post the same TS%, but they are not doing the same job. It's blind to turnovers — a possession a player coughs up never shows up as a shot. And it ignores volume entirely. A reserve who takes five careful shots a game can out-TS a 30-point primary option, which tells you who's efficient but not who's carrying the offense. That's why I almost never read True Shooting alone; I read it next to usage rate, because efficiency at high volume is a fundamentally harder feat than efficiency at low volume.

It's also worth knowing the close cousin, effective field goal percentage, which makes the three-point adjustment but skips free throws. When TS% and eFG% diverge for a player, the free-throw line is the reason — and that difference is its own little scouting report.

The takeaway

If you replace one stat in your basketball vocabulary, make it this one. When you hear "he's shooting 45% from the field," the honest follow-up is "okay, but what's his True Shooting?" — because that's the number that actually correlates with putting points on the board. Field goal percentage tells you how often a player's shots go in. True Shooting tells you how much those shots were worth. Only one of those wins games.

Sources & Further Reading

  • Background reading: Chapter 8: Shooting Efficiency Metrics, a free textbook chapter at DataField.dev.
  • Player efficiency data: NBA.com/stats, pulled via the nba_api Python package (2025-26, retrieved June 2026). The script is in scripts/true_shooting_explained.py.
  • Stat definitions and historical context: Basketball-Reference Glossary.
  • The 0.44 free-throw coefficient and possession estimation originate with Dean Oliver, Basketball on Paper.

C. B. Zakarian

C. B. Zakarian is an independent analyst who writes about what he can measure: ball sports and the player-run economies inside Roblox. He builds every model, chart, and calculator here himself from public data, shows the working, and never invents a number. When the data can't answer a question, he says so. On NBAAnalytic, that means NBA ratings, shot charts, and stat explainers built from the league's public data. More about the methodology →