Education Jun 19, 2026 · 8 min read

American vs Decimal Odds: Conversions You’ll Actually Remember

American and decimal odds say the same thing: probability. Learn quick conversions, implied odds, and break-even so you can sanity-check any price.

Christian Starr
Christian Starr

Co-Founder & Backend Engineer

Sports Analytics Machine Learning Data Engineering Backend Systems
American vs Decimal Odds: Conversions You’ll Actually Remember

Odds aren’t “magic numbers” — they’re just probability in costume

You’ve seen them a thousand times: -110 on an NFL spread, +150 on a dog, 1.91 on a soccer side, 2.50 on a tennis underdog. Different outfits, same message.

Odds are a price for a probability. That’s it. Books don’t post odds because they enjoy confusing you. They post odds because odds tell you two things:

  • What you win if you’re right (your payout)
  • What the book thinks the chance is (the implied probability)

American odds (the plus/minus format) are common in the U.S. Decimal odds (like 1.91, 2.30, 3.75) show up everywhere else and on a lot of modern apps. If you can convert between them quickly, you can do a basic “sanity check” before you click Place Bet.

Here’s the mental model that makes this stick: decimal odds are your total return per $1 staked. Put up $1, get back “decimal” dollars (including your $1). American odds are the same idea, just expressed as “risk to win” (favorites) or “win on a $100 stake” (underdogs).

If you learn one thing from this post, make it this: every odds format is just a different way to say “what probability do I need to break even?”

Decimal odds in plain English (the easiest format, honestly)

Decimal odds are clean because they work like a multiplier.

  • Decimal 2.00 means you double your money. Bet $100, total return $200 (profit $100).
  • Decimal 1.50 means you get 1.5x back. Bet $100, total return $150 (profit $50).
  • Decimal 3.25 means you get 3.25x back. Bet $100, total return $325 (profit $225).

That’s why I like decimals for learning. They’re basically “payout math” in one number.

Implied probability (the win rate you need to break even) comes straight from decimals:

Implied Probability = 1 / Decimal Odds

Examples you should memorize:

  • 2.00 → 1/2.00 = 50%
  • 1.50 → 1/1.50 = 66.67%
  • 1.91 (typical -110 equivalent) → 1/1.91 = 52.36%
  • 3.00 → 1/3.00 = 33.33%

Quick analogy: think of decimal odds like a “coupon.” 2.00 is a 100% bonus on your stake. 1.91 is a 91% bonus. 3.00 is a 200% bonus. The smaller the bonus, the more often you have to win.

If you want a simple way to check yourself: anything below 2.00 is a favorite (you win less than your stake). Anything above 2.00 is an underdog (you win more than your stake). Exactly 2.00 is a true coin flip price (before vig).

American odds: favorites vs underdogs (and why people screw it up)

American odds use a plus or minus sign, and that sign matters.

Negative odds (like -150, -110, -250) are favorites. The number tells you how much you must risk to win $100 profit.

  • -110: risk $110 to win $100
  • -150: risk $150 to win $100
  • -250: risk $250 to win $100

Positive odds (like +120, +200, +450) are underdogs. The number tells you how much profit you win on a $100 stake.

  • +120: risk $100 to win $120
  • +200: risk $100 to win $200
  • +450: risk $100 to win $450

The most common beginner mistake: treating + and - like they’re just “bigger or smaller.” They’re not. The sign flips the whole meaning. That’s why a lot of recreational bettors get twisted up and end up thinking a -180 favorite is “only a little worse” than -150. It’s not. You’re paying a lot more for the same win.

Another mistake: confusing payout with probability. A +300 bet isn’t “3x more likely to win than +100.” It just pays more because it wins less often. Odds don’t tell you what will happen. They tell you what price you’re getting for a probability.

Once you can translate American odds into implied probability, you stop guessing. You can look at -180 and immediately know: “Okay, I need to win this a lot, or this price is garbage.”

Quick conversions that actually stick (American ↔ Decimal)

You don’t need to be a calculator. You need a couple of rules you can do in your head, plus a few anchor points you memorize.

American → Decimal

  • For underdogs (+): Decimal = 1 + (American/100)
  • For favorites (-): Decimal = 1 + (100/|American|)

Examples:

  • +150 → 1 + 150/100 = 2.50
  • +200 → 1 + 200/100 = 3.00
  • -110 → 1 + 100/110 = 1 + 0.909 = 1.91
  • -200 → 1 + 100/200 = 1 + 0.50 = 1.50

Decimal → American

  • If decimal ≥ 2.00 (underdog): American = (Decimal - 1) × 100
  • If decimal < 2.00 (favorite): American = -100 / (Decimal - 1)

Examples:

  • 2.50 → (2.50 - 1)×100 = +150
  • 3.20 → (3.20 - 1)×100 = +220
  • 1.91 → -100/(0.91) = -110 (close enough)
  • 1.60 → -100/(0.60) = -167

Anchor points worth memorizing (these save you time):

  • -110 ≈ 1.91 (spread standard)
  • -120 ≈ 1.83
  • -150 = 1.67
  • -200 = 1.50
  • +100 = 2.00
  • +150 = 2.50
  • +200 = 3.00
  • +300 = 4.00

Once those are in your head, most conversions are just “nearby math.”

Implied probability & break-even: the numbers that keep you from donating

Implied probability is the win rate the odds are “charging you for.” Break-even is the same idea from your perspective: what percentage you must win long-term to not lose money.

With decimal odds, it’s simple:

Break-even % = 1 / Decimal

With American odds, here are the formulas (use them a few times and they’ll start feeling normal):

  • For favorites (-A): Break-even = A / (A + 100)
  • For underdogs (+A): Break-even = 100 / (A + 100)

Examples you’ll see constantly:

  • -110: 110/(110+100) = 110/210 = 52.38%
  • -150: 150/250 = 60%
  • +150: 100/250 = 40%
  • +200: 100/300 = 33.33%

This is where a lot of people get wrecked by favorites. They’ll say, “Team X is definitely winning.” Cool. But at -250, your break-even is 250/350 = 71.43%. Do you really think they win that matchup more than 71 out of 100 times? If not, you’re paying too much.

Sanity-check trick: convert to decimal, then invert.

Example: -250 → decimal = 1 + 100/250 = 1.40. Then 1/1.40 = 0.714. Same answer, faster once you’re used to decimals.

If you want to see this in plain language without doing the math every time, ThunderBet’s Betting Assistant will spit out implied probability and break-even from either odds format. Use it as training wheels until the numbers start sticking.

One simple example that ties it all together (and shows you the “edge”)

Let’s say you’re betting an NFL side and you see two books dealing different prices on the same team:

  • Book A: Bears -110
  • Book B: Bears -105

Same pick. Different price. This is where you either act like a shopper… or you act like a donation box.

First, convert to break-even probability.

-110 break-even: 110/(110+100) = 110/210 = 52.38%

-105 break-even: 105/(105+100) = 105/205 = 51.22%

That difference is 1.16%. It looks tiny. It’s not tiny over volume.

Here’s the clean way to think about it: if your true win rate on this type of bet is, say, 53% (which is already hard to sustain), then:

  • At -110, you’re barely above break-even (53% vs 52.38%).
  • At -105, you’ve got more breathing room (53% vs 51.22%).

Same handicap. Different long-term result.

And if you want to step one level up: once you can translate odds into probability, you can start comparing books and hunting misprices. That’s literally what positive EV (expected value) betting is—finding prices where the payout is better than the probability suggests. If you’re ready for that, the Positive EV Finder does the scanning, but you still need the odds/probability basics so you can trust what you’re seeing.

Common pitfalls that cost you money (even if your picks are fine)

You can be “right” about a team and still lose long-term because you paid a bad price. These are the traps I see constantly.

  • Mixing up favorite/underdog conversions. If you forget the sign rules, you’ll turn -200 into 3.00 or +200 into 1.50 and nothing will make sense. Quick reminder: favorites are below 2.00 decimal, dogs are above 2.00.
  • Ignoring the vig (the book’s cut). If two sides are both -110, the implied probabilities add up to 52.38% + 52.38% = 104.76%. That extra 4.76% is the house edge baked into the market.
  • Thinking “high probability” equals “good bet.” A -400 favorite breaks even at 400/500 = 80%. If the true chance is 78%, it’s a bad bet even though it wins a lot. This is where parlays become sucker bets: you stack a bunch of overpriced favorites and wonder why you can’t cash.
  • Comparing payouts instead of probabilities. “+180 pays more than +160” doesn’t mean it’s better. If the true probability is 40%, +160 might be great and +180 might still be bad depending on your estimate. Price first, feelings second.
  • Not shopping lines. The easiest edge you’ll ever get is grabbing -105 instead of -110, or +155 instead of +145. No new knowledge required. Just discipline.

If you want a quick checklist for the moment before you click, From Pick to Plan: 6 Checks Before You Click “Place Bet” pairs perfectly with this odds lesson. Odds conversion is one of those checks that keeps you out of dumb spots.

And if you’re trying to understand why prices move and why the “same probability” shifts during the day, Reverse Line Moves: 4 Traps When the Price Goes the Wrong Way is a good next read.

Responsible gambling note: Bet with a fixed budget you can afford to lose, and step away if you’re chasing or tilting. If betting stops being fun, it’s time to take a break.

#Odds-Formats #American-Odds #Decimal-Odds #Implied-Probability #line shopping

About the Author

Christian Starr

Christian Starr

Co-Founder & Backend Engineer

Christian Starr is a full-stack engineer specializing in sports betting analytics and real-time data systems. He architected ThunderBet's backend infrastructure that processes thousands of betting lines per second.

10+ years in software engineering, specialized in building scalable betting analytics platforms. Expert in Python, Django, PostgreSQL, and real-time data processing.

Sports Analytics Machine Learning Data Engineering Backend Systems

10+ years of experience

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