Betting ROI Calculator — Track Profitability & Win Rate

Enter four numbers from your betting records: total bets placed, total winning bets, total amount staked (the sum of every wager), and total returned (the sum of all payouts received, including your returned stake on winning bets). Click "Calculate Betting ROI" to see your performance breakdown.

The primary result is your ROI percentage — displayed in green if positive and red if negative. A positive ROI means you have returned more money than you staked over this sample. You also see your win rate, average stake per bet, average profit per bet, and the implied average odds you have been betting at.

For meaningful results, you need a large enough sample. ROI calculated from 20 bets is almost entirely variance. Aim for at least 200–500 bets before drawing conclusions about whether your results reflect genuine skill or luck.

All metrics are calculated from four aggregate inputs:

1. Total Profit: P = Total Returned − Total Staked
2. ROI: ROI = (P ÷ Total Staked) × 100
3. Win Rate: W = (Wins ÷ Total Bets) × 100
4. Average Stake: avg_stake = Total Staked ÷ Total Bets
5. Average Profit Per Bet: avg_profit = P ÷ Total Bets
6. Implied Average Odds: avg_odds = (1 + ROI/100) ÷ (Win Rate/100)

The implied average odds figure is derived from your win rate and ROI together. It represents the average decimal odds you would need to have been betting at to produce your observed ROI given your win rate. Compare this to what you actually bet at to check for data entry errors or identify whether your results are driven by odds selection, win rate, or both.

Note that this calculator uses aggregate data only. Individual bet tracking (amount, odds, result per bet) provides far more analytical power — you can segment by sport, league, bet type, and time period. Aggregate ROI is the starting point for performance analysis, not the end point.

Example 1 — Typical Recreational Bettor

Over a football season a bettor places 200 bets, mostly at −110 (1.909 decimal odds). They win 95 bets and lose 105. Total staked: $2,000. Total returned: $1,819 (95 wins × $10 stake × 1.909 ≈ $181.36 per win... more precisely: 95 × $10 × 1.909 = $1,813.55 returned on wins).

• Total profit: −$186.45
• ROI: −9.3%
• Win rate: 47.5%
• Break-even win rate at 1.909 odds: 52.4%

The bettor won nearly half their bets but still lost money because −110 odds require a 52.4% win rate to break even. Their 47.5% win rate is 4.9 points below the threshold — a common outcome for recreational bettors paying the full sportsbook vig.

Example 2 — Sharp Bettor with Positive ROI

A professional bettor places 1,000 bets over six months, averaging $100 per bet. Total staked: $100,000. Total returned: $103,500. Win rate: 54%.

• Total profit: +$3,500
• ROI: +3.5%
• Average profit per bet: +$3.50
• Implied average odds: (1 + 0.035) / 0.54 ≈ 1.916

A 3.5% ROI over 1,000 bets is statistically significant and represents a genuine edge. At $100 average stake, this generates $3,500 profit per 1,000 bets placed. Scaled to $1,000 average stake, the same edge yields $35,000 — illustrating why bankroll size and bet sizing are critical to monetizing a genuine edge.

Example 3 — Identifying Variance vs Skill

Two bettors each show +5% ROI after 50 bets. One has a 60% win rate at low odds (1.83); the other has a 40% win rate at higher odds (2.625). Both look identical in ROI. However, the high-odds bettor's results are far more volatile — 50 bets at 40% win rate have a much wider confidence interval. Neither result is statistically meaningful at 50 bets. After 500 bets, the picture becomes much clearer.