What Does Odds-On Mean in Betting?
Odds-on is a betting term describing a selection priced so that the potential profit is less than the stake. In fractional terms, odds-on means the denominator is larger than the numerator: 1/2, 1/3, 4/6, 2/7. In decimal format, any odds below 2.0 are odds-on. The fundamental characteristic is this: the selection is expected to win more often than not, which is why the bookmaker pays less per unit risked.
An odds-on selection has an implied probability above 50%. This probability is calculated by dividing 1 by the decimal odds. For example, 1.50 decimal odds imply a 66.7% chance of winning (1 ÷ 1.50 = 0.667). The higher the implied probability, the shorter the odds—and the larger your stake relative to your potential profit.
The key characteristic of odds-on betting is the asymmetry of outcomes. You risk a large amount to gain a small amount. At 1/4 (1.25 decimal), a £100 stake returns just £25 profit. If the selection loses, you lose four times as much as you stood to gain. This creates a scenario where even a relatively small losing rate is catastrophic: lose just one in five bets at 1/4 and you break even over five bets.
Why Bookmakers Offer Odds-On Prices
Bookmakers offer odds-on prices to manage their risk and ensure profitability. When they assess that a selection has a high probability of winning, they price it below even money (1/1 or 2.0 decimal). This pricing strategy serves two purposes: it reflects the selection's likelihood of winning, and it embeds the bookmaker's margin—the profit built into every price.
The bookmaker's margin is the difference between the implied probability in the odds and the true probability of the outcome. For example, if a selection has a true probability of 60%, a bookmaker might price it at 1.50 (66.7% implied probability), keeping a 6.7% margin. This margin ensures that even when the selection wins, the bookmaker profits over time.
This is why blindly backing all odds-on selections is a losing strategy. The bookmaker's margin makes it difficult to achieve profitability without genuine edge—a situation where your assessment of true probability exceeds the odds-on price.
How Do You Calculate Odds-On Returns?
Understanding how to calculate returns is essential for evaluating odds-on bets. The process differs depending on whether you're working with fractional or decimal odds, but the underlying mathematics is the same.
Fractional Odds Calculation
Fractional odds express the potential profit relative to the stake. With odds-on, the numerator (first number) is smaller than the denominator (second number).
Formula: (Stake ÷ Denominator) × Numerator = Profit
Example 1: 1/2 Odds
- Stake: £100
- Calculation: (£100 ÷ 2) × 1 = £50 profit
- Total return: £150 (stake + profit)
Example 2: 1/3 Odds
- Stake: £90
- Calculation: (£90 ÷ 3) × 1 = £30 profit
- Total return: £120 (stake + profit)
Example 3: 4/6 Odds (simplified to 2/3)
- Stake: £60
- Calculation: (£60 ÷ 6) × 4 = £40 profit
- Total return: £100 (stake + profit)
Notice how in each case, the profit is substantially less than the stake. This is the defining characteristic of odds-on betting.
Converting to Decimal Odds
Decimal odds are increasingly popular and provide a simpler way to calculate returns. All decimal odds below 2.0 represent odds-on selections.
Conversion Formula: Decimal = (Denominator + Numerator) ÷ Denominator
Example Conversions:
- 1/2 = (2 + 1) ÷ 2 = 1.50
- 1/3 = (3 + 1) ÷ 3 = 1.33
- 2/5 = (5 + 2) ÷ 5 = 1.40
- 4/5 = (5 + 4) ÷ 5 = 1.80
- 4/6 = (6 + 4) ÷ 6 = 1.67
Calculating Returns with Decimal Odds:
Formula: Stake × Decimal Odds = Total Return (including stake)
Or: (Stake × Decimal Odds) - Stake = Profit
Example: 1.50 Decimal Odds
- Stake: £100
- Total return: £100 × 1.50 = £150
- Profit: £150 - £100 = £50
Example: 1.33 Decimal Odds
- Stake: £100
- Total return: £100 × 1.33 = £133
- Profit: £133 - £100 = £33
Decimal odds make it immediately obvious that you're risking far more than you stand to gain.
Calculating Implied Probability
The implied probability of odds-on selections is always above 50%. This figure tells you what probability the bookmaker has assigned to the outcome.
Formula: Implied Probability = 1 ÷ Decimal Odds
Examples:
- 1.50 odds: 1 ÷ 1.50 = 0.667 or 66.7%
- 1.33 odds: 1 ÷ 1.33 = 0.752 or 75.2%
- 1.80 odds: 1 ÷ 1.80 = 0.556 or 55.6%
- 1.25 odds: 1 ÷ 1.25 = 0.800 or 80.0%
Understanding implied probability is crucial because it reveals the break-even win rate. To profit over time, you must win more often than the implied probability suggests. If you win exactly at the implied probability rate, you break even (accounting for the bookmaker's margin, you actually lose slightly).
Where Did the Term "Odds-On" Come From?
The term "odds-on" has roots in traditional betting terminology that predates modern sports betting. Understanding its origin provides context for how it's used across different betting formats today.
Historical Origins
The phrase "odds-on" derives from the concept of betting "on" a likely outcome. In traditional betting, particularly in horse racing and games of chance, the term reflected the likelihood of an event. When something was "odds-on," it meant you were betting on a selection that was more likely to happen than not—hence the smaller odds offered by the bookmaker.
The terminology emerged from the fractional odds system, which was the dominant format in British and Irish betting for centuries. In fractional odds, the structure naturally reflects probability: smaller numerators relative to denominators indicate higher probability (odds-on), while larger numerators indicate lower probability (odds-against).
The term is distinctly British in origin and remains most commonly used in UK and Irish betting, though it has spread globally as sports betting has expanded.
Evolution in Modern Sports Betting
As betting has modernized, the term "odds-on" has been standardized across all major odds formats. Today, odds-on is not limited to fractional odds—it applies equally to decimal and moneyline formats.
- Fractional: 1/2, 2/5, 4/6 (numerator < denominator)
- Decimal: 1.50, 1.40, 1.67 (any decimal < 2.0)
- Moneyline (American): Negative odds like -200, -150, -300 (favorite odds)
Despite the proliferation of odds formats, the underlying principle remains unchanged: odds-on selections are priced to reflect a greater than 50% probability of winning, and the bettor receives less profit than stake.
How Do Odds-On Differ from Odds-Against?
Odds-on and odds-against are opposite ends of the betting spectrum. Understanding their differences is fundamental to evaluating any wager.
Key Differences Explained
| Aspect | Odds-On | Odds-Against |
|---|---|---|
| Fractional Format | Numerator < Denominator (e.g., 1/2, 1/3) | Numerator > Denominator (e.g., 2/1, 5/2) |
| Decimal Format | Below 2.0 (e.g., 1.50, 1.33) | Above 2.0 (e.g., 3.0, 3.50) |
| Implied Probability | Above 50% (e.g., 66.7%, 75%) | Below 50% (e.g., 33.3%, 25%) |
| Profit vs Stake | Profit < Stake | Profit > Stake |
| Example | £100 stake at 1/2 = £50 profit | £100 stake at 2/1 = £200 profit |
| Bookmaker Assessment | Selection likely to win | Selection unlikely to win |
| Risk Profile | Higher capital required for same profit | Lower capital required for larger profit |
Odds-On Example: 1/2 (1.50 Decimal)
- Stake: £100
- Profit if win: £50
- Loss if lose: £100
- Win rate needed to break even: 66.7%
Odds-Against Example: 2/1 (3.0 Decimal)
- Stake: £100
- Profit if win: £200
- Loss if lose: £100
- Win rate needed to break even: 33.3%
Profit Asymmetry and Risk
The asymmetry between odds-on and odds-against creates fundamentally different risk profiles. With odds-on, you must risk significantly more capital to achieve the same profit as an odds-against bet.
Consider this scenario: You want to profit £100.
Using Odds-On (1/2):
- Required stake: £200
- If you win: £100 profit
- If you lose: £200 loss
- Risk-to-reward ratio: 2:1 (unfavorable)
Using Odds-Against (2/1):
- Required stake: £100
- If you win: £200 profit
- If you lose: £100 loss
- Risk-to-reward ratio: 1:2 (favorable)
This is why long-term profitable betting often focuses on odds-against selections—the risk-to-reward ratio is more favorable. However, this only applies if you can identify selections with genuine edge. An odds-against selection with negative expected value is still a losing bet, regardless of the attractive payout.
What's the Implied Probability of Odds-On Selections?
Implied probability is a critical concept for evaluating odds-on bets. It reveals what probability the bookmaker has assigned to an outcome and, crucially, whether that probability aligns with reality.
Understanding Implied Probability
Implied probability is always above 50% for odds-on selections. It's calculated by dividing 1 by the decimal odds:
Formula: Implied Probability = 1 ÷ Decimal Odds
Common Odds-On Examples:
| Decimal Odds | Fractional Equivalent | Implied Probability |
|---|---|---|
| 1.25 | 1/4 | 80.0% |
| 1.33 | 1/3 | 75.2% |
| 1.50 | 1/2 | 66.7% |
| 1.67 | 4/6 | 59.9% |
| 1.80 | 4/5 | 55.6% |
| 1.91 | 10/11 | 52.4% |
The implied probability represents the bookmaker's assessment of how often the selection will win. A 1.50 selection (66.7% implied) should win approximately two out of every three times, according to the bookmaker's model.
Why Implied Probability Doesn't Equal Actual Probability
Here's the critical issue: implied probability always exceeds true probability because the bookmaker's margin is built into the odds.
Example:
- True probability of a selection: 60%
- Bookmaker's implied probability: 66.7% (at 1.50 odds)
- Bookmaker's margin: 6.7%
This margin is how bookmakers profit. Over thousands of bets, even if the bookmaker's probability assessments are accurate, the margin ensures consistent profit.
The overround (or "vig" in American betting) is the sum of all implied probabilities across an event's possible outcomes. For a two-outcome event (like a match winner), the overround should theoretically be 100% if odds were perfectly fair. In reality, it's typically 102–110%, representing the bookmaker's profit margin.
Practical Implication: To profit on odds-on selections, your assessment of true probability must exceed the implied probability. If you believe a 1.50 selection (66.7% implied) actually has a 70% true probability, you have a 3.3% edge. Over many bets, this edge translates to long-term profit. If your true probability assessment is below the implied probability, the bet has negative expected value, and you'll lose money over time.
Can Odds-On Selections Lose?
Yes, odds-on selections lose frequently. This is one of the most important facts to understand about odds-on betting. Many bettors mistakenly believe that short odds equal certainty—they don't.
Yes, and More Often Than You Might Think
Even selections with very high implied probabilities lose regularly. Consider these examples:
1/4 Odds (1.25 Decimal, 80% Implied Probability)
- The bookmaker believes this selection will win 80% of the time
- This means it will lose 20% of the time—one in every five bets
- Over 100 bets, you'd expect approximately 20 losses
Real-World Example: Football Manchester United, one of Europe's strongest teams, plays a lower-league opponent at home. Manchester United is priced at 1.25 (4/1 odds, 80% implied probability). Despite the heavy odds-on pricing, upsets happen. The lower-league team, with a well-organized defense and a lucky goal, wins 1-0. Your £100 bet at 1.25 loses entirely.
Real-World Example: Tennis Novak Djokovic, the world's top-ranked player, faces a unseeded opponent in the first round of a Grand Slam. Djokovic is priced at 1.30 (implied 76.9% probability). Djokovic is the clear favorite—but the unseeded player, playing the match of his life, pulls off a shocking upset. Your £100 bet at 1.30 loses.
Real-World Example: Horse Racing A horse with excellent recent form is priced at 1/4 (1.25 decimal) in a 12-horse race. The odds-on pricing reflects the horse's quality. However, the horse stumbles at a jump, the jockey loses balance, and the horse finishes fourth. Your bet loses entirely.
The point is simple: no odds-on selection is guaranteed to win. Upsets, injuries, bad luck, and unexpected performances happen in every sport. The shorter the odds, the rarer the upset—but it will eventually occur.
The Importance of True vs Implied Probability
The distinction between true probability and implied probability is where edge emerges.
If you assess that a selection's true probability of winning is higher than the implied probability in the odds, you have a positive expected value (EV) bet. Over many repetitions, such bets will profit.
If you assess that a selection's true probability is lower than the implied probability, you have a negative EV bet. Over many repetitions, such bets will lose.
Example:
- Odds: 1.50 (66.7% implied probability)
- Your assessment: 70% true probability
- Expected value: Positive (you have edge)
- Long-term outcome: Profit
Example:
- Odds: 1.50 (66.7% implied probability)
- Your assessment: 60% true probability
- Expected value: Negative (you have no edge)
- Long-term outcome: Loss
This is why blindly backing all odds-on selections is a losing strategy. Without genuine edge—a reasoned assessment that your probability estimate exceeds the bookmaker's—you're simply accepting a negative expected value bet.
Is Betting on Odds-On Selections Profitable?
The short answer: not by default. However, odds-on betting can be profitable if approached strategically.
The Short Answer: Not by Default
Empirical evidence shows that blindly backing all odds-on selections—or all favorites in general—results in losses over time. This is because of the bookmaker's margin. The implied probability in every odds-on price includes a profit margin for the bookmaker. To break even, you must win at the exact implied probability rate; to profit, you must win more often than the odds suggest.
For a 1.50 selection, you need to win 66.7% of bets just to break even. In reality, if the bookmaker's assessment is accurate, you'll win exactly 66.7% of the time—meaning you break even before accounting for the margin. When you account for the margin, you actually lose slightly.
Long-term studies of sports betting show that backing favorites (which includes most odds-on selections) produces negative returns. The bookmaker's margin is simply too large to overcome without genuine edge.
When Odds-On Betting Can Be Profitable
Odds-on betting becomes profitable when you identify selections where the true probability exceeds the implied probability. This requires:
- Thorough Analysis: Research form, injuries, matchups, weather, and other relevant factors
- Honest Assessment: Estimate the true probability without bias
- Comparison: Compare your estimate to the implied probability in the odds
- Selective Backing: Only back selections where your estimate exceeds the odds
Example:
- Selection: Manchester City to beat a lower-league team at home (1.40 odds, 71.4% implied)
- Your analysis: Manchester City's recent form, injury status, historical matchup data, and the opponent's defensive record suggest a 75% true probability
- Decision: Bet, because 75% > 71.4%
- Expected value: Positive
This approach requires discipline and expertise. Many bettors overestimate their ability to assess true probability, leading to losses despite selective betting. However, for skilled analysts, odds-on selections can be profitable.
The Accumulator Trap
Accumulators (also called parlays) combining multiple odds-on selections create an attractive-looking return but are particularly dangerous.
Example: Five 1.50 Selections Combined
- Individual odds: 1.50 each
- Combined odds: 1.50 × 1.50 × 1.50 × 1.50 × 1.50 = 7.59
- Return on £100 stake: £759
The 7.59 return looks attractive, but here's the problem: each leg carries the bookmaker's margin. While a single 1.50 bet might have a small edge (if your probability assessment exceeds 66.7%), combining five such bets compounds the margin.
The Mathematics:
- Single 1.50 bet: 66.7% implied probability
- Five 1.50 bets combined: (0.667)^5 = 13.1% implied probability for all five to win
If you believe each individual selection has a 70% true probability, the combined probability is (0.70)^5 = 16.8%. While this exceeds 13.1%, the margin has widened significantly. The overround across five legs is much larger than across one leg.
Why Accumulators Are Risky:
- Compounding margin: Each leg adds the bookmaker's margin
- Correlation risk: Selections may be correlated (e.g., if one team loses, related teams may also lose)
- All-or-nothing outcome: One loss means the entire accumulator loses
For these reasons, pure odds-on accumulators are generally poor value. If you want to use accumulators, mixing short and longer odds is wiser—it reduces the compounding effect of the bookmaker's margin.
Common Misconceptions About Odds-On
Several myths persist about odds-on betting. Addressing them is essential for developing a rational betting approach.
"Odds-On Means Guaranteed Win"
The Myth: Short odds equal certainty. If something is 1/4 (80% implied), it will definitely win.
The Reality: No odds-on selection is guaranteed to win. Even selections with 80% implied probability lose 20% of the time. Upsets, injuries, bad luck, and unexpected performances happen regularly in sports. The shorter the odds, the rarer the upset—but it will eventually occur.
Why This Matters: Bettors who believe odds-on equals certainty often stake too much on single bets or accumulators, risking ruin when the inevitable upset happens. Proper bankroll management requires acknowledging that even 1.20 odds can lose.
"Odds-On Selections Are Always Better Than Odds-Against"
The Myth: Higher probability = better bet. Always back odds-on over odds-against.
The Reality: The value of a bet depends on whether the odds reflect true probability, not on the implied probability itself. An odds-on selection with negative expected value is a worse bet than an odds-against selection with positive expected value.
Example:
- Odds-on selection: 1.50 (66.7% implied), but your assessment is 60% true probability = Negative EV, avoid
- Odds-against selection: 3.0 (33.3% implied), but your assessment is 40% true probability = Positive EV, back
The odds-against selection is the better bet, despite the lower implied probability, because it has positive expected value.
Why This Matters: Bettors who blindly back odds-on selections due to their higher implied probability often lose money. Evaluation must focus on whether the odds offer value, not on the implied probability alone.
"Betting Multiple Odds-On Selections Reduces Risk"
The Myth: More short-priced legs = safer accumulator. Five 1.50 selections are safer than five 3.0 selections.
The Reality: Multiple odds-on selections in an accumulator actually increase risk through compounding. Each leg carries the bookmaker's margin, and combining them multiplies this margin. The overall expected value deteriorates with each addition.
Example:
- Single 1.50 bet: 66.7% implied probability, 3.3% margin (if true probability is 70%)
- Five 1.50 bets: 13.1% implied probability, much larger compounded margin
Additionally, if your edge on each leg is small, combining five legs makes the overall edge negligible or negative.
Why This Matters: Bettors seeking "safer" accumulators often construct all-odds-on parlays, which are actually among the riskiest accumulators due to compounding margins. Mixing odds provides better expected value.
Real-World Examples of Odds-On Betting
Concrete examples illustrate how odds-on pricing works across different sports.
Football: Top Team vs Lower-Ranked Opponent
Scenario: Manchester United plays a League Two team in the FA Cup. Manchester United is heavily favored and priced at 1.25 (4/5 odds, 80% implied probability).
Calculation:
- Stake: £100
- Potential profit: (£100 ÷ 5) × 4 = £80
- Total return if win: £180
- Loss if lose: £100
- Win rate needed to break even: 80%
Reality: Manchester United is the clear favorite, and the 80% implied probability reflects their quality and home advantage. However, football is unpredictable. The League Two team, despite being massive underdogs, could get a lucky goal and hold on for a draw or even win. Your £100 stake would be lost entirely.
Analysis: To profit on this bet, your assessment of Manchester United's true win probability must exceed 80%. If you believe they'll win 85% of the time based on your analysis, you have a 5% edge. Over many similar bets, this edge generates profit. If you believe they'll win 75% of the time, the bet has negative expected value, and you should avoid it.
Tennis: Seeded Player vs Unseeded Opponent
Scenario: Novak Djokovic, the world No. 1, plays an unseeded opponent in the first round of a Grand Slam. Djokovic is priced at 1.30 (implied 76.9% probability).
Calculation:
- Stake: £100
- Potential profit: (£100 ÷ 10) × 3 = £30
- Total return if win: £130
- Loss if lose: £100
- Win rate needed to break even: 76.9%
Reality: Djokovic is one of the greatest players ever, and the 76.9% implied probability reflects his dominance. However, Grand Slams are unpredictable. The unseeded opponent could play the match of his life, Djokovic could have an off day, or injury could play a role. While upsets at this probability level are rare, they happen. In 2024, multiple seeded players lost in early rounds of Grand Slams to unseeded opponents.
Analysis: If your assessment of Djokovic's true win probability is 80%, you have a small edge (80% - 76.9% = 3.1%). Over many such bets, this edge generates modest profit. However, if you assess his true probability at 75%, the bet has negative expected value, and you should avoid it.
Horse Racing: Heavy Favourite
Scenario: A horse with excellent recent form is priced at 1/4 (1.25 decimal, 80% implied probability) in a 12-horse race.
Calculation:
- Stake: £40
- Potential profit: (£40 ÷ 4) × 1 = £10
- Total return if win: £50
- Loss if lose: £40
- Win rate needed to break even: 80%
Reality: The horse's recent form justifies the heavy odds-on pricing. However, horse racing is notoriously unpredictable. Horses can stumble, jockeys can make mistakes, and unexpected injuries can occur. The 80% implied probability means the horse is expected to win four out of five races—but that also means it loses one in five. Over a season, the heavy favorite will suffer unexpected defeats.
Analysis: Horse racing is particularly difficult to predict because of the many variables involved (track condition, jockey form, horse fitness, etc.). If you have genuine expertise and believe your assessment of true probability exceeds 80%, the bet may have value. However, for most bettors, odds-on horse racing bets are difficult to profit from without specialized knowledge.
How to Use Odds-On Selections in Your Betting Strategy
Rather than avoiding odds-on selections entirely, the key is using them strategically within a broader betting approach.
Selective Backing: The Key to Profitability
The most important principle is selective backing: only back odds-on selections when your assessment of true probability exceeds the implied probability in the odds.
Process:
- Identify a selection (e.g., Manchester City to beat a lower-league team)
- Research thoroughly: Form, injuries, matchups, weather, recent trends
- Assess true probability: Based on your analysis, estimate the percentage chance of winning
- Compare to odds: Calculate the implied probability (1 ÷ decimal odds)
- Evaluate edge: If true probability > implied probability, you have positive expected value
- Decide: Only back selections with positive expected value
Example:
- Selection: Liverpool to beat Southampton at home (1.40 odds, 71.4% implied)
- Your research: Liverpool's recent form is excellent, Southampton's defense is weak, Liverpool's home record is strong
- Your assessment: 76% true probability
- Decision: Back, because 76% > 71.4%
- Expected value: Positive (approximately 4.6%)
This approach requires discipline. Many bettors overestimate their ability to assess probability and back selections without genuine edge. However, if you can honestly assess your probability estimates, selective backing can be profitable.
Combining Odds-On with Longer Odds
Rather than pure odds-on accumulators, consider mixing short and longer odds to balance risk and reward.
Example: Mixed Accumulator
- Leg 1: 1.50 odds (odds-on, high confidence)
- Leg 2: 2.50 odds (odds-against, moderate confidence)
- Leg 3: 1.80 odds (odds-on, high confidence)
- Combined odds: 1.50 × 2.50 × 1.80 = 6.75
Compared to a pure odds-on accumulator (1.50 × 1.50 × 1.50 = 3.375), this mixed accumulator offers better value because the longer odds reduce the compounding effect of the bookmaker's margin.
Why This Works:
- The 2.50 selection has a lower implied probability (40%), which means less margin built in
- Mixing odds-on and odds-against selections reduces the overall margin
- The 6.75 return is more attractive than 3.375 while maintaining reasonable odds
Bankroll Management with Odds-On Bets
Because odds-on bets require higher capital per bet to achieve the same profit as odds-against bets, bankroll management is critical.
Unit Sizing Principle: Use smaller units on odds-on bets than on odds-against bets.
Example:
- Your bankroll: £1,000
- Standard unit: £10 (1% of bankroll)
- Odds-against bets: 2 units (£20) per bet
- Odds-on bets: 1 unit (£10) per bet
This approach ensures that a losing streak on odds-on bets (which will happen, because they lose more frequently) doesn't deplete your bankroll as quickly.
Why This Matters:
- Odds-on selections lose more frequently than odds-against selections
- If you stake the same amount on each, odds-on bets will generate more losses
- Smaller units on odds-on bets reduce variance and protect bankroll
Break-Even Analysis: Before placing an odds-on bet, calculate the win rate needed to break even:
- 1.50 odds: 66.7% win rate needed
- 1.33 odds: 75.2% win rate needed
- 1.25 odds: 80.0% win rate needed
If you cannot honestly assess a win rate exceeding these thresholds, the bet has negative expected value.
Frequently Asked Questions
What does odds-on mean in practical terms?
Odds-on means the potential profit is less than your stake. At 1/3 (1.33 decimal), a £3 stake wins £1. The selection is expected to win more often than not, but you risk significantly more than you stand to gain on a single bet.
Is betting on odds-on favourites a good strategy?
Not by default. Odds-on selections lose more often than the odds suggest due to the bookmaker's margin. Over the long run, backing all odds-on favourites at face value is a losing strategy. You need genuine edge—where your assessment of true probability exceeds the implied probability in the odds—to profit consistently.
How do I express odds-on in decimal format?
Any decimal odds below 2.0 are odds-on. Examples: 1.50 = 1/2, 1.33 = 1/3, 1.80 = 4/5. The implied probability is always above 50% for odds-on selections, calculated as 1 ÷ decimal odds (e.g., 1 ÷ 1.50 = 0.667 or 66.7%).
Can odds-on selections lose?
Yes, frequently. Even a 1/4 shot (80% implied probability) loses 20% of the time. Upsets happen in every sport. The key question is whether the true probability of the outcome matches the implied probability in the odds. If it doesn't, you may have an edge—or you may be making a poor bet.
What's the implied probability of 1.50 odds?
The implied probability is 66.7%. This is calculated as 1 ÷ 1.50 = 0.667. This means the bookmaker believes the selection will win approximately two out of every three times. However, this figure includes the bookmaker's margin, so the true probability may be lower.
Why do bookmakers offer odds-on prices?
Bookmakers offer odds-on prices because they've assessed that a selection has a high probability of winning. By pricing it below even money, they ensure that even if the selection wins, their profit margin is preserved. The bookmaker's margin—the difference between implied and true probability—is built into every odds-on price.
How do I calculate the break-even win rate for odds-on odds?
The break-even win rate equals the implied probability of the decimal odds. For 1.50 odds (66.7% implied), you need to win 66.7% of bets to break even. For 1.33 odds (75% implied), you need 75%. Any win rate below this means losses over time; above it means profits.