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True Shooting Percentage Calculator

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NBA Formula.
0.44 FT Weight.
Basketball-Ref Spec.
100% Free.
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How it Works

01Points Scored

Total points in a game, stretch, or full season. Includes 2s, 3s and free throws.

02FGA + FTA

Field-goal attempts plus free-throw attempts — the full shooting volume.

030.44 Free-Throw Factor

Multiplier derived from how often trips to the line result from fouled FGAs.

04TS% Output

A single efficiency score that beats raw FG% by crediting threes and free throws.

What Is a True Shooting Percentage Calculator?

A true shooting percentage calculator (TS%) computes the single most important scoring-efficiency stat in modern basketball. Unlike raw field-goal percentage, TS% accounts for three-pointers and free throws — so a player who shoots 40% from three is not unfairly penalised against a player who lives in the paint, and a foul-drawing machine gets full credit for every trip to the line.

The formula is the one used by Basketball-Reference, NBA.com advanced stats, the MIT Sloan Sports Analytics Conference, and every serious front office: TS% = PTS ÷ (2 × (FGA + 0.44 × FTA)) × 100. The 0.44 coefficient is the empirically derived rate at which a free-throw attempt "costs" a true possession — it accounts for the fact that and-ones, technical fouls, and flagrants do not start fresh possessions.

League-average TS% hovers between 54% and 58% in the modern NBA. Anything above 60% is elite; above 65% is typically an All-NBA tier efficiency number; above 70% is Nikola Jokić / peak-Steph territory. Below 50% is a red flag for a primary scorer, though acceptable for specialist defenders. The tool also shows the total True Shooting Attempts (TSA = 2 × (FGA + 0.44 × FTA)), which is the best single-number proxy for scoring volume.

Built for coaches, analysts, fantasy managers, high-school scouts, and fans alike, this calculator gives you an instant, accurate efficiency rating plus a qualitative rating band — Elite, Excellent, Above Average, Average, Below Average, or Poor — so you can contextualise a number the moment you see it.

How the TS% Calculator Works

TSA: compute True Shooting Attempts = 2 × (FGA + 0.44 × FTA). The 0.44 multiplier weights free throws as fractional possessions.
TS%: divide total points by TSA and multiply by 100. This gives points produced per true scoring possession.
Rating band: we map the TS% into six qualitative tiers based on historical NBA percentiles.
URL sync: your box-score inputs are reflected in the page URL so you can share a prepared calculation instantly.

True Shooting Formula

The official Basketball-Reference formula:

TSA = 2 × (FGA + 0.44 × FTA)
TS% = (PTS / TSA) × 100

The 0.44 coefficient approximates the fraction of FTA that end a possession. It is an empirical league-wide value — teams with very high and-one rates trend slightly higher, but 0.44 is the accepted standard.

Real-World Example

Worked Example

A player scores 25 points on 18 field-goal attempts and 6 free-throw attempts:

  • TSA = 2 × (18 + 0.44 × 6) = 2 × (18 + 2.64) = 2 × 20.64 = 41.28 attempts
  • TS% = (25 / 41.28) × 100 = 60.56%
  • Rating: Excellent (60–70% band)

For comparison, a 25-point night on 25 FGA and 2 FTA would be TS% ≈ 48.3% — Below Average despite identical scoring, because the player took many more shots to produce the same output.

Who Uses This Calculator?

1
Basketball coaches and assistants grading scoring efficiency game-by-game and over full seasons
2
Advanced-stats analysts benchmarking players against league averages and positional peers
3
Fantasy basketball managers evaluating whether a hot scorer is efficient or just high-volume
4
High-school and AAU scouts putting a number on efficiency in non-televised games
5
Journalists and content creators backing up takes on Twitter/X with the actual Basketball-Reference number
6
Players and parents tracking personal improvement across a season
7
Sports bettors quantifying shot-creation value for over/under lines
8
Statistics teachers showing why weighted formulas beat raw FG%

Technical Reference

Formula origin: popularised by John Hollinger and Dean Oliver in the early 2000s; codified on Basketball-Reference and NBA.com Advanced Stats. The 0.44 FTA coefficient was refined empirically from tracked play-by-play data.

Edge cases: if TSA = 0 (no shots and no free throws), TS% is undefined and the tool refuses to render a number. Pure defensive box scores are acknowledged but not scored.

Positional context: elite rim-runners (centers) tend to post the highest TS% because they avoid long twos. Primary ball-handlers with heavy usage typically settle 3-5 points below.

Key Takeaways

True Shooting Percentage is the gold-standard single-number scoring efficiency stat because it handles the three parts of modern basketball offence — 2-point shots, 3-point shots, and free throws — in one unified denominator. The 0.44 coefficient on FTA is what makes it possession-accurate. Use TS% to compare scorers who shoot from very different spots on the floor: a 40% three-point shooter and a 60% interior finisher can both hit 58% TS%, and that parity is the whole point. League average sits in the mid-50s; anything sustained above 62% is franchise-cornerstone level. Plug in any box score and you have an instant, defensible efficiency read.

Frequently Asked Questions

What is a test statistic?
A test statistic is a single number computed from sample data that you compare to a critical value (or convert to a p-value) to decide whether to reject a null hypothesis. Common examples are t, z, F, and chi-square statistics.
When do I use a t-statistic vs a z-statistic?
Use z when you know the population standard deviation (rare). Use t when you estimate the standard deviation from your sample (almost always — and especially with n < 30).
What's the formula for a t-statistic?
t = (sample mean − hypothesized mean) ÷ (sample SD ÷ √n). The denominator is called the standard error of the mean.
How do I interpret the test statistic?
Compare it to the critical value at your significance level (typically α = 0.05). If |t| exceeds the critical value, reject the null hypothesis. Equivalently, if the p-value < α, reject.
What are degrees of freedom?
For a one-sample t-test, df = n − 1. For two-sample, df depends on assumptions (Welch vs pooled). Higher df → t-distribution looks more like a normal distribution.
What's a 'large' test statistic?
Roughly: |t| > 2 is significant at α = 0.05 with reasonable sample size. |t| > 3 is highly significant. The exact critical value depends on degrees of freedom and one- vs two-tailed test.
What's the difference between one-tailed and two-tailed?
Two-tailed tests for any difference (more or less). One-tailed tests for a specific direction (e.g., greater than). One-tailed gives more power but is only justified when you have a directional hypothesis a priori.
What's a p-value?
The probability of observing a test statistic at least as extreme as yours, assuming the null hypothesis is true. Smaller p-value = stronger evidence against the null. Convention: p < 0.05 = significant.
Can a high test statistic ever be wrong?
Yes — it can be a Type I error (false positive). At α = 0.05, you'll falsely reject the null 5% of the time even when it's true. Replication and effect sizes matter.
Is my data private?
Yes. All calculations happen in your browser. Your sample data is not stored or transmitted.

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The ToolsACE Team

Our specialized research and development team at ToolsACE brings together decades of collective experience in financial engineering, data analytics, and high-performance software development.

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Disclaimer

Educational reference. TS% is a single-stat summary; always review box-score context alongside usage rate, eFG%, and PER.