Win Rate Analyzer

It depends on your reward-risk ratio. With 2:1 R:R, 35%+ is profitable. With 1:1 R:R, you need 50%+. Most strategies have 40-60% win rates. Focus on expectancy (win rate × avg win - loss rate × avg loss) rather than win rate alone.

Win Rate = Number of Winning Trades / Total Trades × 100%. Count your winners and total trades, then divide. Include all closed trades. Need at least 30 trades for meaningful calculation.

Because your losses are larger than your wins. If you win $200 on average but lose $400 on average, even 60% wins = (0.6 × $200) - (0.4 × $400) = $120 - $160 = -$40 per trade. Check your average win vs average loss.

Not necessarily. Aim for positive expectancy. A 40% win rate with 3:1 R:R is very profitable. Chasing high win rates often leads to small wins and big losses. Balance win rate with win/loss ratio.

Weekly for a quick check; monthly for detailed analysis. Don't obsess over short-term fluctuations - 5 trades don't tell you much. Look at trends over 30+ trades.

1) Identify your best setups and trade those more. 2) Filter out low-probability trades. 3) Improve entry timing. 4) Trade in favorable market conditions. 5) Review losing trades for patterns. But remember: improving win rate may reduce opportunity.

Breakeven WR = 1 / (1 + Reward-Risk Ratio). For 1:1 R:R, you need 50%. For 2:1, you need 33%. For 3:1, you need 25%. Your actual win rate must exceed breakeven to be profitable.

Tag each trade with its setup type (breakout, pullback, reversal, etc.). In spreadsheet, use a column for setup type. Then filter or pivot to calculate win rate for each type. Identify your best and worst performers.

Could mean: 1) Normal variance (temporary). 2) Market conditions have changed. 3) Strategy is degrading. 4) Execution has slipped. Investigate by looking at which setups/conditions are failing. Take action if sustained.

Often inversely. Larger positions create psychological pressure that can hurt execution. Some traders have lower win rates on big trades. Track separately. If true for you, consider sizing down or working on psychology.

Use binomial confidence interval: WR ± z × √(WR × (1-WR) / n). For 95% confidence, z = 1.96. Example: 45% win rate, 100 trades = 0.45 ± 1.96 × √(0.45 × 0.55 / 100) = 35% to 55%. This shows the range where true win rate likely falls.

Kelly formula: f* = (bp - q) / b, where p = win probability, q = 1-p, b = win/loss ratio. Example: 50% WR, 2:1 ratio → f* = (2×0.5 - 0.5) / 2 = 25%. Most use fractional Kelly (half or quarter) for safety.

Formula: log(N) / log(1/loss_rate) approximates max streak. For 45% WR over 100 trades, expect max losing streak of 6-8 trades. For 40% WR, expect 8-10. Knowing this prevents panic during normal streaks.

Decompose: Overall_WR = Σ(Setup_WR × Setup_Weight). Calculate each setup's contribution. Identify which setups drag down WR (targets for elimination) and which lift it (trade more). Also attribute by market condition.

1) Tighter stops raise WR but reduce avg win. 2) Stricter filters raise WR but reduce opportunities. 3) Taking quick profits raises WR but caps upside. Always optimize expectancy, not just win rate. Sometimes accepting lower WR with bigger wins is better.