BTTS Calculator — Both Teams To Score Probability

Model BTTS Yes/No from expected goals (xG) with a Poisson score grid — built for football bettors and analysts.

Educational probabilities only — not betting advice. Gamble responsibly where legal.

Enter expected goals (xG)

Independent Poisson goals model — same engine as our Poisson calculator.

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BTTS probability

BTTS Yes
54.29%
Fair odds: 1.84
BTTS No
45.71%
Fair odds: 2.19

Related markets (same xG)

BTTS Yes
54.29%
Fair odds: 1.84
Over 2.5
50.64%
Fair odds: 1.97
Correlation
BTTS and Over 2.5 probabilities are close.

Score matrix — BTTS Yes contribution

Heatmap shows Poisson score mass; green cells are BTTS Yes (both teams score). Table lists the scorelines that drive most Yes probability.

H\\A 0 1 2 3 4 5 6
0 0-0 0-1 0-2 0-3 0-4 0-5 0-6
1 1-0 1-1 1-2 1-3 1-4 1-5 1-6
2 2-0 2-1 2-2 2-3 2-4 2-5 2-6
3 3-0 3-1 3-2 3-3 3-4 3-5 3-6
4 4-0 4-1 4-2 4-3 4-4 4-5 4-6
5 5-0 5-1 5-2 5-3 5-4 5-5 5-6
6 6-0 6-1 6-2 6-3 6-4 6-5 6-6
Scoreline Probability Share of BTTS Yes
1-1 12.1% 22.3%
2-1 9.07% 16.7%
1-2 7.26% 13.4%
2-2 5.44% 10.0%
3-1 4.54% 8.4%
1-3 2.9% 5.4%
3-2 2.72% 5.0%
2-3 2.18% 4.0%

Quick answer

Enter home and away xG → get BTTS Yes/No probability and fair odds instantly. Yes means both teams score; No includes 0-0 and clean sheets.

What is BTTS (Both Teams To Score)?

BTTS (Both Teams To Score) is one of the most popular football betting markets. You win “Yes” if each team scores at least one goal; “No” if at least one team fails to score (including 0-0).

This calculator derives BTTS probability from home and away expected goals using the same independent Poisson model as our full Poisson match tool — ideal for comparing bookmaker prices to a fair line.

Worked example (current xG inputs)

Values update when you change home or away expected goals above.

Home xG: 1.5 · Away xG: 1.2

Market / lineModel probabilityFair decimal odds
BTTS Yes 54.29% 1.84
BTTS No 45.71% 2.19
Over 2.5 50.64% 1.97
Under 2.5 49.36% 2.03

Example BTTS analysis

Illustrative pre-match workflow: model fair BTTS from xG, then compare to a sharp closing-style price. Market odds shown are examples for education — not live quotes.

Liverpool vs Newcastle

  • Home xG: 2.1
  • Away xG: 1.5
Metric BTTS Yes Over 2.5
Model probability 68.17% 69.72%
Fair odds 1.47
Example market (BTTS Yes) 1.74 (57.47% implied)

Poisson BTTS Yes is 68.17% (fair 1.47) vs example market 1.74 (57.47% implied) — model exceeds market by 10.7 pp. The market may understate away-side scoring threat in an open home fixture; confirm with closing odds and EV sizing.

How we calculate BTTS probability

Under independent Poisson goals λ_home and λ_away, BTTS Yes equals the probability that home goals ≥ 1 AND away goals ≥ 1:

P(BTTS Yes) = (1 − e−λh)(1 − e−λa)

We also sum the joint score matrix for consistency with correct-score and Over/Under outputs on our Poisson calculator.

BTTS probability cheat sheet (Poisson)

Illustrative full-match xG inputs; use the calculator for your fixture.

Home xG Away xG BTTS Yes Fair odds BTTS No
1.0 1.0 39.96% 2.5 60.04%
1.2 1.0 44.17% 2.26 55.83%
1.5 1.2 54.29% 1.84 45.71%
1.8 1.5 64.85% 1.54 35.15%
2.0 1.8 72.17% 1.39 27.83%

Typical BTTS Yes rates by league style (illustrative xG)

League tempo shifts λ — use your fixture xG, not league averages alone. Table shows Poisson BTTS Yes for representative home/away xG pairs.

Market Home xG Away xG BTTS Yes
Premier League (open) 1.55 1.35 58.35%
Bundesliga (high tempo) 1.75 1.45 63.24%
Serie A (defensive) 1.25 1.05 46.38%
La Liga (balanced) 1.45 1.2 53.49%
Ligue 1 (low scoring) 1.2 1.0 44.17%

How BTTS Probability Is Derived from xG

Both Teams To Score (BTTS) is a binary market: Yes wins when each side scores at least once; No wins on 0-0 or any clean sheet (only one team scores). Bookmakers price BTTS from goal models similar to totals markets.

Under independent Poisson goals with rates λhome and λaway, the closed form is P(Yes) = (1−e−λh)(1−e−λa). Our tool also sums the joint score matrix (0–10 goals) so BTTS stays consistent with Over/Under and correct-score outputs.

Worked Example: λ_home 1.5, λ_away 1.2

P(home scores) = 1 − e−1.5 ≈ 77.7%. P(away scores) = 1 − e−1.2 ≈ 69.9%. BTTS Yes ≈ 0.777 × 0.699 ≈ 54.3% (fair odds ≈ 1.84). BTTS No ≈ 45.7%. High-scoring matchups push Yes; defensive fixtures favor No.

BTTS vs Over 2.5 — Not the Same Market

Over 2.5 only needs three total goals (e.g. 3-0 → Over but BTTS No). BTTS Yes allows 1-1. Use our Over/Under calculator for totals and this page for side-specific scoring risk.

Professional Workflow with Closing Odds

1) Model xG → 2) Fair BTTS here → 3) Compare closing odds → 4) Size with EV calculator if edge > your threshold. Gamble responsibly.

How to Use the BTTS Calculator

Enter home and away expected goals (xG), then read BTTS Yes/No probability or switch to fair decimal odds.

  1. Set expected goals: Use season xG, shot-based models, or OddsGPT match forecasts for λ_home and λ_away.
  2. Read BTTS probabilities: Yes = both teams score ≥1 goal; No = at least one team blank (including 0-0).
  3. Compare to bookmaker odds: Toggle fair odds and compare implied probability to Pinnacle or closing lines on OddsGPT.
  4. Explore related markets: Use Over/Under and full Poisson tools for totals and correct-score context.

Tips for BTTS Betting

  • BTTS Yes correlates with open games but not always with Over 2.5 — check both markets.
  • Cup ties and knockout legs often shift BTTS pricing — adjust xG for motivation.
  • Use No when a elite defense faces a low-xG away side even if the favourite is expected to win.
  • Always compare fair probability to the bookmaker implied % after vig removal.

What's Next?

Compare full markets on the Poisson calculator, totals on Over/Under tool, or find price edges via Expected Value calculator.

Glossary: BTTS & Poisson terms

BTTS (Both Teams To Score)
A market where you bet whether each team scores at least one goal in 90 minutes.
xG (expected goals)
Shot-quality model output used as Poisson rate λ for goal counts.
Poisson distribution
Models independent goal counts; basis for BTTS, totals, and scorelines here.
Fair odds
Decimal price 1/P(model) with no bookmaker margin.
Implied probability
1 ÷ decimal odds; compare to model % to spot value.
Closing odds
Final pre-kickoff price — the benchmark sharp bettors beat for +EV.
Sharp bettor
Bettor who compares model fair lines to closing prices and hunts CLV.
Vig (bookmaker margin)
Built-in margin in posted odds; remove with a no-vig calculator before comparing to model %.

Complete guide: BTTS probability for football betting

Both Teams To Score remains one of the highest-volume football props globally because it is easy to understand yet sensitive to match tempo. Professional bettors map BTTS to expected goals because shot-based models already estimate how often each side finds the net.

Start with reliable xG: season totals from OddsGPT xG tables, pre-match forecasts from predictions, or your own ratings. Enter λ_home and λ_away here to translate those rates into BTTS Yes/No percentages and fair decimal prices.

Compare the fair column to bookmaker BTTS odds after removing vig with the no-vig calculator. If your probability exceeds implied probability by more than the book margin, run stake sizing through the EV calculator.

Remember BTTS differs from Over 2.5 and from Asian totals — use the Over/Under tool for goal counts and keep correlation in mind when building parlays.

For low-scoring leagues or derbies, consider validating results on Poisson Pro with Dixon–Coles adjustment before risking larger stakes.

Why use this BTTS calculator?

Same Poisson engine as our full Poisson match calculator — BTTS stays consistent with Over/Under and correct-score outputs. Live updates, fair odds toggle, and links to closing odds and EV tools on OddsGPT.

BTTS vs Over/Under vs Asian Handicap vs 1X2

Same xG inputs, different settlement rules — use the right OddsGPT tool for each market.

Market Wins when… OddsGPT tool
BTTS (Both Teams To Score) Each team scores ≥1 goal (Yes) or at least one blank (No). BTTS probability calculator
Over/Under (e.g. 2.5) Total goals above/below the line (3-0 → Over 2.5). Over/Under goal probability
Asian Handicap Home team covers the goal handicap (quarter lines split). Asian handicap cover %
1X2 (Match result) Home win, draw, or away win after 90 minutes. xG win probability

This tool is for education and research. Bet responsibly and only where legal. BeGambleAware · NCPG

Frequently Asked Questions

How do you calculate BTTS probability from xG?

We use independent Poisson goal rates λ_home and λ_away. BTTS Yes probability equals the sum of joint scores where both i≥1 and j≥1, equivalent to (1−e^−λh)(1−e^−λa). Results update live when you change xG inputs.

What is the difference between BTTS Yes and BTTS No?

Yes wins if each team scores at least one goal (1-1, 2-1, 3-2, etc.). No wins on 0-0 or if only one team scores (1-0, 0-2, 4-0). Own goals count toward the team that benefits on the scoreboard.

Does 0-0 count as BTTS No?

Yes. Any match where at least one team fails to score settles BTTS as No, including 0-0 and clean-sheet wins.

How do I compare BTTS to bookmaker odds?

Switch to fair odds mode, convert your price to implied %, and compare to the bookmaker line (use our implied probability or no-vig tools to strip margin). Positive expected value appears when your model % exceeds the book implied % enough to overcome vig.

Is Poisson BTTS accurate for every league?

Poisson is a strong baseline for league football but underestimates low-scoring correlation in some derbies. For advanced fits use our Poisson Pro page (Dixon–Coles / ZIP).

Where do I get home and away xG?

Sources include OddsGPT xG statistics, public shot models, or your own ratings. Pre-match xG forecasts on our predictions pages can seed λ values.

What is a good BTTS Yes probability for a bet?

There is no universal threshold — compare model probability to the offered odds. A 55% model vs 50% implied (2.00) suggests edge before commission.

Can BTTS be combined in accumulators?

Yes, but goals in the same match are correlated across markets (BTTS + Over). For parlays use our parlay calculator and be aware of correlation risk.

How does BTTS probability vary by league?

High-scoring leagues (e.g. Bundesliga) lift BTTS Yes; defensive leagues lower it. Adjust λ from league-specific xG rather than global averages.

What bookmaker price beats this model?

If BTTS Yes fair odds are 1.84 (54.3%) and a book offers 2.00 (50% implied before vig), you may have value — confirm with no-vig and EV tools.

Is BTTS correlated with match winner?

Often yes in open games, but not always — a 2-0 home win is BTTS No. Model 1X2 separately on our xG calculator.

Can I embed these probabilities in a spreadsheet?

Use the live outputs above or call our Poisson API endpoints via /calculate-match-odds for JSON.

What is closing line value (CLV) for BTTS?

CLV means beating the final pre-kickoff BTTS price. Model fair odds here, then compare to Pinnacle or closing lines on our closing odds hub before staking.

Do injuries or red cards change BTTS mid-match?

Pre-match xG inputs ignore in-play events. For live BTTS, adjust λ manually or use in-play models — this page is pre-match Poisson only.

Which fixtures favour BTTS Yes vs No?

Open games (high λ both sides) lift Yes; elite defence vs low-xG attack favours No even if the favourite wins 2-0. Always model both markets with this tool and Over/Under.