The Percentage Stays the Same—The Eligible Player Pool Does Not

NBA true-shooting leaderboards change when you adjust the attempt minimum because the minimum is an eligibility filter, not part of a player’s displayed true-shooting rate. Raising the cutoff removes lower-volume players from the ranked pool; lowering it adds them. The leader and every rank beneath that player can therefore change even though nobody’s TS% changes.

Related: What Is a Good Free-Throw Percentage?.

The short answer: the cutoff changes who qualifies

True-shooting percentage is displayed as a rate. An attempt minimum is a volume-based condition that determines whether a player belongs on a particular leaderboard.

Suppose a leaderboard requires at least 500 attempts. A player below that threshold is outside the list, regardless of how high the player’s TS% may be. Reduce the minimum enough for that player to qualify, and the player enters the pool at the position determined by the already-recorded rate.

Changing the filter does not:

• add or subtract made shots;
• recalculate the player’s recorded TS%;
• change the player’s performance; or
• penalize an ineligible player by assigning a lower rank.

It changes the population being ranked. If a stricter minimum excludes the player with the highest rate, every qualifying player below that player may move up one place without improving.

The distinction becomes clearer when attempt counts and shooting rates are treated separately. The NBA statistical glossary defines measures such as three-point attempts and two-point attempts as totals, while 3P% and 2FG% are rates calculated from makes and attempts. A leaderboard cutoff operates on the stated volume measure; the ranking operates on the percentage. Those numbers serve different purposes.

A worked example with two attempt minimums

The following example is fictional:

Player	True shooting	Attempts
Player A	70% TS	400
Player B	66% TS	1,200
Player C	62% TS	2,000

With a 300-attempt minimum, all three players qualify:

1. Player A — 70% TS
2. Player B — 66% TS
3. Player C — 62% TS

Raise the minimum to 1,000 attempts, and Player A becomes ineligible. The visible order is then:

1. Player B — 66% TS
2. Player C — 62% TS

None of the rates changed. Player A remains at 70% TS, Player B at 66%, and Player C at 62%. Only the eligible population changed.

It would therefore be misleading to say Player A fell from first to last. Player A has no rank on the second leaderboard because that list is limited to players with at least 1,000 attempts. Player B is now the leader among qualifying players, not necessarily the highest-rate player in the unrestricted dataset.

The same logic explains why several rows can move when one filter changes. A leaderboard sorts only the records that survive its eligibility rule. Add a highly efficient player and existing entries can move down; remove that player and they can move up.

What lower and higher cutoffs are designed to show

A lower cutoff provides a broader view of efficiency. It includes more limited-volume performances, such as those produced by specialists, players with shorter careers, or players who received fewer shooting opportunities. The tradeoff is that unusually high rates achieved over fewer opportunities may appear near the top.

A higher cutoff emphasizes performance sustained over greater volume. That can be useful when the question concerns long-running production rather than the highest rate achieved at any meaningful volume. It can also exclude efficient specialists, shorter-career players, and others with fewer opportunities.

Neither choice is inherently better. The appropriate threshold depends on the leaderboard’s purpose:

Editorial goal	Suitable approach	Main tradeoff
Show peak or broad efficiency	Lower cutoff	Includes more limited-volume results
Balance rate and opportunity	Medium cutoff	Depends on a chosen boundary
Emphasize sustained volume	Higher cutoff	Excludes some efficient players
Test ranking stability	Show several cutoffs	Needs more explanation and space

Efficiency, scoring volume, and longevity should remain conceptually separate. A high TS% does not by itself prove high scoring volume. A large attempt total does not establish superior efficiency. A long career provides more opportunity to cross a career-volume threshold, but longevity is not the same statistic as shooting efficiency.

When the goal is analysis rather than a single headline, showing low, medium, and high thresholds can reveal how sensitive the result is to filtering. If the same players remain near the top, the ranking is relatively stable across the selected cutoffs. If the leader changes repeatedly, readers can see that the result depends heavily on the eligibility boundary.

Official NBA qualifications are not automatically TS% rules

The NBA’s statistical-minimums page does not list a qualification standard specifically for true-shooting percentage. It does document official qualifications for conventional shooting-percentage leaderboards in an 82-game season: 300 field goals made for FG%, 125 free throws made for FT%, and 82 three-pointers made for 3P%. Those are makes-based qualifications, not games-played requirements. The NBA also prorates them during the season; after a team’s 41st game, the listed thresholds are 150 field goals made, 63 free throws made, and 41 three-pointers made, according to the NBA Statistical Minimums page.

Those rules show how qualification standards define official leaderboards, but they should not be transferred to TS% without separate documentation. FG%, FT%, 3P%, and TS% are different measures, and a qualification written for one does not automatically govern another.

Custom rankings may use much larger or differently defined minimums. For example, a user-generated Reddit ranking used a threshold of at least 10,000 field-goal attempts. That is an example of a ranking-specific career filter—not an NBA rule, a universal TS% standard, or verification of the post’s player order.

Whenever a leaderboard presents an attempt selector, ask who chose it. The threshold may reflect an official league qualification, a statistics provider’s default, a publisher’s editorial decision, or a user-controlled setting. A label such as “minimum 1,000 attempts” defines the scope of that list; it does not by itself establish an official league standard.

How to compare two true-shooting leaderboards

Two true-shooting rankings do not necessarily conflict because they show different leaders. They may contain identical player data but apply different eligibility filters.

Check the following before comparing positions:

Check	What to identify	Why it matters
Metric definition	Raw TS%, an adjusted metric, or another measure	Similar labels may describe different calculations
Qualification	Attempts, makes, games, or a per-game condition	The denominator determines who can qualify
Cutoff	The exact minimum	Different boundaries create different player pools
Coverage	Regular season, playoffs, multi-season, or career	Scope changes both performance and opportunity
Data endpoint	Provider and latest included date	Tables may cover different periods

Do not assume that “attempt minimum” always means field-goal attempts. A site may use another stated opportunity measure, an attempts-per-game condition, a games requirement, or a different denominator. Read the label or methodology instead of inferring the rule from the table.

Next, match the time span and competition scope. A single regular-season leaderboard is not directly comparable to a playoff list, a multi-season window, or an entire-career ranking. Even two career tables can differ if one includes data through a later date.

Then identify who selected the cutoff. An NBA qualification, a statistics provider’s default, a publisher’s custom filter, and a user-adjusted setting are not interchangeable. If the threshold is custom, the presentation should say so.

The clearest leaderboard places TS% beside the applicable volume figure. That allows readers to assess efficiency and opportunity separately rather than treating eligibility as evidence that one player’s rate is better. Its methodology should also disclose the metric, qualification denominator, cutoff, competition scope, time span, and data endpoint.

The rule of thumb is simple: compare the filters before comparing the ranks. The percentage beside each player can remain fixed while the leaderboard changes because moving the minimum redraws the boundary around who is eligible to appear.