Points per game gets all the attention, but it hides a crucial detail: how many shots did it take to get there? True Shooting Percentage answers that by folding field goals, three-pointers, and free throws into one clean efficiency number — and it’s exactly the kind of stat that separates a real scoring threat from a volume shooter for prop betting purposes.
Loading calculator...
This calculator computes TS% from a box score line, rates it against standard NBA-level benchmarks, and — critically for betting purposes — lets you project expected points for an upcoming game by combining that efficiency number with an expected shot volume, then compares the projection directly against a bookmaker’s points prop line.
The volume piece matters because TS% alone can’t tell you how many points someone will score — it tells you how well they convert whatever shots they take. Pairing the two together is what actually gets you to a projected points total worth comparing against a prop line.
📊 How to Use the True Shooting Calculator
Enter a player’s points, field goal attempts, and free throw attempts for a game or over a stretch of games. The calculator computes their True Shooting % and rates it against standard bands from Poor through Elite.
TS% intentionally weights free throws at 0.44 per attempt rather than counting them as full shot attempts, since most trips to the line come from a smaller subset of possessions than field goal attempts — this weighting is the standard, widely-used approach.
Toggle on “Project Points vs. Prop Line” to extend the calculation. Enter a bookmaker’s points prop line for the player’s upcoming game, along with your expected field goal and free throw attempts for that specific matchup, to see a projected points total based on holding their TS% constant at the expected volume.
🔢 Calculator Fields Explained
Points – The player’s total points scored over the stat line being analyzed.
Field Goal Attempts (FGA) – Total field goal attempts (including three-pointers) over that same stat line.
Free Throw Attempts (FTA) – Total free throw attempts over that same stat line.
Bookmaker Points Prop Line – The over/under points total a sportsbook is offering for the player’s upcoming game.
Expected FGA / FTA (this game) – Your projection for how many field goal and free throw attempts the player will take in the specific upcoming game, used to convert their TS% into an expected points total.
💰 Understanding the Results
| Result Field | What It Means |
|---|---|
| True Shooting % | Scoring efficiency per true shooting possession, accounting for field goals, three-pointers, and free throws together |
| Rating (Poor to Elite) | Where the calculated TS% falls relative to standard NBA-level efficiency benchmarks |
| Projected Points | Expected points for the upcoming game, derived from the player’s TS% applied to your expected shot volume |
| Projection vs. Line | The difference between the projected points total and the bookmaker’s prop line |
TS% and shot volume are genuinely separate pieces of information — one tells you how efficient a player is, the other tells you how often they’re getting opportunities to use that efficiency.
A high TS% doesn’t guarantee a high points projection if the expected shot volume is low — an elite-efficiency player taking only 8 shot attempts will still project for fewer points than an average-efficiency player taking 20, since volume and efficiency multiply together, not efficiency alone.
The projected points figure assumes both TS% and shot volume hold steady from your inputs — real games introduce matchup difficulty, foul trouble, blowout risk, and pace changes that can shift the actual result well away from this baseline projection.
📐 Calculation Formulas
| Component | Formula |
|---|---|
| True Shooting % | Points ÷ (2 × (FGA + 0.44 × FTA)) × 100 |
| Projected points (given TS% and volume) | (TS% ÷ 100) × 2 × (Expected FGA + 0.44 × Expected FTA) |
| Projection vs. line | Projected Points − Bookmaker Prop Line |
The 0.44 free-throw weighting is a long-established sabermetric convention that accounts for the fact that not every free throw attempt stems from a distinct shooting possession (e.g., and-one situations, technical fouls) — it’s not an arbitrary number, but a standard correction factor.
The projected-points formula is simply the TS% formula solved in reverse — instead of computing efficiency from known points and attempts, it computes expected points from known efficiency and assumed attempts.
📝 Practical Examples
Example 1 – Elite efficiency scorer. 28 points on 18 FGA and 6 FTA: TS% = 28 ÷ (2 × (18 + 0.44×6)) × 100 ≈ 68.6%, rated Elite. This player is converting possessions at a very high rate relative to standard NBA benchmarks.
Example 2 – High volume, average efficiency. 30 points on 25 FGA and 8 FTA: TS% = 30 ÷ (2 × (25 + 0.44×8)) × 100 ≈ 52.6%, rated Below Average. Despite scoring more points than Example 1, this player needed considerably more attempts and shows meaningfully lower efficiency.
Comparing these two examples side by side is the whole point of TS% — raw points totals alone would rank Example 2 as the “better” scoring game, but the efficiency numbers tell a more complete story about how those points were generated.
Example 3 – Projecting against a prop line. A player with a 58% season TS% (Good band) projected for 18 expected FGA and 5 expected FTA in an upcoming game: projected points = 0.58 × 2 × (18 + 0.44×5) ≈ 23.4. Against a bookmaker’s line of 24.5, this projects modestly under the number.
Example 4 – Same efficiency, higher expected volume. The same player’s 58% TS%, but facing a matchup where you expect 22 FGA and 7 FTA instead. Projected points climb to roughly 28.7 — nearly a 5-point swing purely from the volume assumption changing, even though the efficiency input stayed identical.
💡 Tips & Best Practices
Use a large enough sample of games (not just one) when calculating TS% for prop-betting purposes — a single game’s efficiency number is noisy and can be skewed by an unusually hot or cold shooting night.
Pay close attention to the expected FGA/FTA inputs specifically — since projected points scale directly with volume, an inaccurate volume assumption will distort the entire projection even with a perfectly accurate TS% input.
Adjust expected shot volume for matchup-specific factors like opponent pace, expected blowout risk, or a tough individual defensive matchup, rather than defaulting to a simple season average every time.
Run the projection with a range of plausible volume assumptions (a low, middle, and high estimate) rather than a single point figure, to see how sensitive the projected points total is to your volume assumption specifically.
Cross-check a TS% rating against the player’s role — a role player with an Elite TS% on very low volume is a different bet than a high-usage star with the same rating, even though the efficiency number looks identical.
- Recalculate TS% whenever new game data comes in, rather than relying on a stale season-long figure for an in-form or recently-changed player
- Treat the projection as a baseline estimate to combine with other matchup research, not a standalone final answer
If a projection comes out very close to the prop line, treat that as effectively no edge rather than reading a marginal difference as a strong signal either way.
⚠️ Common Mistakes to Avoid
Treating TS% as a standalone points predictor
A high TS% by itself says nothing about how many points a player will actually score without also knowing their expected shot volume.
Assuming a player with an Elite TS% will automatically score a lot of points, without checking their expected attempt volume for the specific game, is the most common misuse of this stat in a betting context.
Always pair TS% with an expected volume figure before drawing any conclusion about likely point totals.
Using a stale or unrepresentative TS% sample
A TS% calculated from a single unusually hot or cold game, or from an outdated stretch of the season, doesn’t represent current form.
Relying on an old or single-game TS% figure rather than a reasonably recent, multi-game sample is a common way to project points based on efficiency that no longer reflects how the player is actually shooting — always use a current, representative sample before projecting against a live prop line.
Update the TS% input regularly, especially for players in a hot or cold shooting stretch.
Ignoring matchup-specific volume changes
Applying a generic season-average shot volume to every upcoming game ignores real matchup factors like opponent pace, foul trouble risk, or blowout potential.
Adjust the expected FGA/FTA inputs specifically for the matchup at hand rather than defaulting to a flat season average every time.
🎯 When to Use This Calculator
Use this any time you want to evaluate a player’s true scoring efficiency beyond raw points per game, or specifically when comparing a points prop line against a projection built from both efficiency and expected shot volume together.
Points per game tells you the outcome; True Shooting % tells you how that outcome was produced — this calculator exists to combine both pieces into a projection that’s actually useful for evaluating a points prop, rather than relying on either number alone.
🔗 Related Calculators
OBP Calculator, OPS Calculator, ERA Calculator, Passer Rating Calculator, Target Odds Calculator
📖 Glossary
True Shooting Percentage (TS%) – A scoring efficiency metric accounting for field goals, three-pointers, and free throws together in one rate stat.
Field Goal Attempts (FGA) – The number of field goal shot attempts, including both two- and three-point attempts.
Free Throw Attempts (FTA) – The number of free throw shot attempts.
Shot Volume – The total number of scoring opportunities (attempts) a player takes, distinct from how efficiently they convert them.
Points Prop – A bookmaker’s over/under betting line on a player’s total points in a specific game.
Usage Rate – A related sabermetric measuring the percentage of a team’s offensive possessions a player uses while on the floor.
Efficiency Metric – Any stat measuring output per opportunity, rather than total output alone.
Season Average – A player’s statistical rate calculated across an entire season, as opposed to a single game.
Matchup Difficulty – The relative strength of an upcoming opponent’s defense, which can affect both efficiency and volume projections.
Pace – The rate at which a team’s possessions occur, which affects total shot volume available in a game.
❓ Frequently Asked Questions
Why does True Shooting % weight free throws differently from field goal attempts?
Because not every free throw attempt corresponds to its own distinct shooting possession — some come in pairs or groups from a single possession (and-one situations, intentional fouling, technical fouls) — so weighting them at 0.44 rather than a full attempt corrects for this and produces a more accurate per-possession efficiency figure.
This weighting is a long-established convention in basketball analytics, not something specific to this calculator.
Can a player have a very high TS% but still score few points?
Yes — TS% only measures efficiency per attempt, not total attempts. A highly efficient player who takes very few shots in a given role can still score fewer total points than a less efficient player who shoots far more often.
This is exactly why the projection tool requires both TS% and an expected volume input — TS% alone can’t answer “how many points,” only “how efficiently were those points scored.”
What counts as a “good” True Shooting Percentage?
Using the standard bands in this calculator: below 50% is generally Poor, 50-54% Below Average, 54-58% Average, 58-62% Good, and above 62% Elite — these thresholds reflect typical NBA-level shooting efficiency distributions.
Keep in mind these bands are general guidelines, and what counts as “good” can shift somewhat depending on position, role, and era of play.
How should I choose the expected FGA/FTA inputs for an upcoming game?
Start with the player’s recent-game or season-average attempt volume, then adjust for matchup-specific factors — opponent pace, likely blowout risk, injury news affecting their role, or a particularly tough individual defensive assignment.
A single fixed number is a simplification; some bettors prefer running the projection at a low, middle, and high volume estimate to see the projection’s sensitivity to that input.
Why might my projected points differ meaningfully from the bookmaker’s prop line?
A meaningful gap between your projection and the prop line usually comes from a difference in volume assumptions — bookmakers build their lines using their own models, which may weight matchup pace, blowout risk, or recent role changes differently than your inputs.
Treat a gap as a prompt to double-check your volume assumption specifically, since it’s the input the projection is most sensitive to.
⚖️ Legal Disclaimer
This calculator is provided for informational and educational purposes only and does not guarantee any betting outcome. Points projections rely on user-provided efficiency and volume assumptions that may not reflect actual game conditions. Gambling involves risk, and you should never stake more than you can afford to lose. If you or someone you know has a gambling problem, contact the National Council on Problem Gambling helpline at 1-800-522-4700.
The methodology here directly addresses a gap that’s been plaguing the sports betting vertical for years. True Shooting Percentage has become standard in player evaluation circles, but its integration into prop betting workflows remains underutilized across retail sportsbooks and sharp syndicates alike. What’s particularly noteworthy is how the calculator weights free throws at 0.44 per attempt rather than as full possessions, which aligns with how NBA analytics firms like Cleaning the Glass and Synergy Sports structure their efficiency models. The separation of efficiency from volume is mathematically elegant but operationally critical for line-shopping: a player posting 58% TS% on 18 FGA per game projects dramatically different point totals than someone at 58% TS% on 12 FGA, yet many retail bettors conflate efficiency with outcome probability. From a market microstructure perspective, this creates persistent mispricing opportunities when bookmakers over-weight recent PPG volatility without contextualizing shot volume changes tied to lineup injuries, pace adjustments, or usage rate fluctuations. The projection versus line comparison function essentially operationalizes what sharp bettors have been doing manually: converting player-level efficiency metrics into expected value calculations. One consideration worth flagging: the model assumes TS% stability across matchup contexts, which breaks down against elite perimeter defenses where FGA compression can occur independent of the player’s baseline efficiency. DraftKings and FanDuel’s props markets have shown measurable inefficiency in this exact scenario during playoff periods when defensive schemes tighten. The calculator’s transparency about its assumptions is refreshing compared to the black-box nature of most commercial betting tools.
You’ve identified the exact constraint we built the projection feature around. The efficiency-stability assumption does break down in specific contexts, and you’re right that playoff defense compression is one of the clearest examples. We’ve noticed this particularly with guards facing switching-heavy playoff schemes where FGA drops 15-20% while TS% actually improves due to shot selection filtering. One approach some sharp bettors implement is layering defensive rating data alongside the projection, or adjusting expected FGA downward when facing top-10 perimeter defenses. We’re considering adding a ‘defensive adjustment factor’ toggle in a future version that would let users manually compress expected volume based on opponent profile. Regarding the market inefficiency window you mentioned during playoff periods: that’s been a consistent pattern. The props market tends to be slower than moneyline markets in repricing efficiency changes, partly because volume data lags PPG by a few days in media reporting. Have you found that pre-game injury announcements (which affect both volume and matchup difficulty simultaneously) create more pronounced mispricings than defensive scheme changes alone?