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MT5Sugar Ā· DailyStats StructureĀ¶

Daily trading statistics structure returned by GetDailyStats(). Contains comprehensive performance metrics for today's trading session.

šŸ“‹ Structure DefinitionĀ¶

type DailyStats struct {
    TotalDeals   int       // Total closed deals today
    WinningDeals int       // Number of profitable deals
    LosingDeals  int       // Number of losing deals
    WinRate      float64   // Win rate % (0-100)
    TotalProfit  float64   // Total realized profit/loss today
    BestDeal     float64   // Largest profitable deal
    WorstDeal    float64   // Largest losing deal
}

šŸ“Š Field DetailsĀ¶

TotalDeals (int)Ā¶

  • What: Total number of closed positions today (00:00 to now)
  • Example: 15
  • Includes: Both winning and losing trades
  • Excludes: Open positions (not yet closed)

WinningDeals (int)Ā¶

  • What: Number of profitable closed positions
  • Example: 9
  • Criteria: Profit > 0 (excludes zero-profit trades)
  • Use: Calculate win rate, performance tracking

LosingDeals (int)Ā¶

  • What: Number of losing closed positions
  • Example: 6
  • Criteria: Profit < 0
  • Note: TotalDeals = WinningDeals + LosingDeals (+ zero-profit deals)

WinRate (float64)Ā¶

  • What: Percentage of winning trades
  • Formula: (WinningDeals / TotalDeals) Ɨ 100
  • Range: 0.0 to 100.0
  • Example: 60.0 (means 60% win rate)
  • Important:
  • Above 60% = Excellent
  • 50-60% = Good
  • Below 40% = Concerning

TotalProfit (float64)Ā¶

  • What: Sum of all realized profits/losses today
  • Formula: Sum of all deal profits
  • Example: 350.75 (positive = profit, negative = loss)
  • Currency: Account base currency
  • Excludes: Floating P/L from open positions

BestDeal (float64)Ā¶

  • What: Largest single profitable trade today
  • Example: 125.50
  • Use: Track maximum gain, outlier detection
  • Note: Always positive (or 0 if no winners)

WorstDeal (float64)Ā¶

  • What: Largest single losing trade today
  • Example: -87.25
  • Use: Risk management, maximum loss tracking
  • Note: Always negative (or 0 if no losers)

šŸŽÆ Common CalculationsĀ¶

Average WinĀ¶

avgWin := 0.0
if stats.WinningDeals > 0 {
    // Approximation (need deal details for exact)
    avgWin = stats.BestDeal / float64(stats.WinningDeals)
}

Average LossĀ¶

avgLoss := 0.0
if stats.LosingDeals > 0 {
    avgLoss = stats.WorstDeal / float64(stats.LosingDeals)
}

Risk:Reward RatioĀ¶

riskRewardRatio := 0.0
if avgLoss != 0 {
    riskRewardRatio = avgWin / -avgLoss
}
// Values: 1:2 = 2.0, 1:1.5 = 1.5, etc.

Profit Per TradeĀ¶

profitPerTrade := 0.0
if stats.TotalDeals > 0 {
    profitPerTrade = stats.TotalProfit / float64(stats.TotalDeals)
}

Loss RateĀ¶

lossRate := 100.0 - stats.WinRate

Profit FactorĀ¶

// Requires individual deal data
profitFactor := totalWins / -totalLosses
// Above 2.0 = excellent, 1.5-2.0 = good, below 1.0 = losing

šŸŸ¢ Usage ExamplesĀ¶

Example 1: Basic stats displayĀ¶

stats, _ := sugar.GetDailyStats()

fmt.Println("šŸ“Š TODAY'S PERFORMANCE")
fmt.Println("=====================")
fmt.Printf("Total trades:   %d\n", stats.TotalDeals)
fmt.Printf("Winners:        %d\n", stats.WinningDeals)
fmt.Printf("Losers:         %d\n", stats.LosingDeals)
fmt.Printf("Win rate:       %.1f%%\n", stats.WinRate)
fmt.Printf("Total profit:   $%.2f\n", stats.TotalProfit)
fmt.Printf("Best trade:     $%.2f\n", stats.BestDeal)
fmt.Printf("Worst trade:    $%.2f\n", stats.WorstDeal)

Example 2: Performance ratingĀ¶

stats, _ := sugar.GetDailyStats()

rating := "Unknown"
if stats.TotalDeals >= 5 {
    if stats.WinRate >= 70 && stats.TotalProfit > 0 {
        rating = "ā­ā­ā­ Exceptional"
    } else if stats.WinRate >= 60 && stats.TotalProfit > 0 {
        rating = "ā­ā­ Excellent"
    } else if stats.WinRate >= 50 && stats.TotalProfit > 0 {
        rating = "ā­ Good"
    } else if stats.TotalProfit > 0 {
        rating = "šŸ‘ Profitable"
    } else if stats.TotalProfit > -500 {
        rating = "šŸ“‰ Minor loss"
    } else {
        rating = "šŸ”“ Significant loss"
    }
} else {
    rating = "ā³ Insufficient data (need 5+ trades)"
}

fmt.Printf("Today's rating: %s\n", rating)

Example 3: Risk analysisĀ¶

stats, _ := sugar.GetDailyStats()

fmt.Println("āš ļø RISK ANALYSIS")
fmt.Println("================")

// Worst trade vs total profit ratio
if stats.TotalProfit > 0 {
    worstImpact := (-stats.WorstDeal / stats.TotalProfit) * 100
    fmt.Printf("Worst trade impact: %.1f%% of profit\n", worstImpact)

    if worstImpact > 50 {
        fmt.Println("šŸ”“ Single loss took >50% of profit!")
    }
}

// Best vs worst comparison
if stats.WorstDeal != 0 {
    ratio := stats.BestDeal / -stats.WorstDeal
    fmt.Printf("Best:Worst ratio: 1:%.2f\n", ratio)

    if ratio < 1.0 {
        fmt.Println("āš ļø Largest loss exceeds largest win")
    }
}

Example 4: Trading consistencyĀ¶

stats, _ := sugar.GetDailyStats()

if stats.TotalDeals == 0 {
    fmt.Println("No trades today")
    return
}

profitPerTrade := stats.TotalProfit / float64(stats.TotalDeals)
consistency := "Unknown"

if profitPerTrade > 50 {
    consistency = "šŸ”„ Highly profitable per trade"
} else if profitPerTrade > 20 {
    consistency = "āœ… Good average profit"
} else if profitPerTrade > 0 {
    consistency = "šŸ‘ Slightly profitable"
} else if profitPerTrade > -20 {
    consistency = "šŸ“‰ Small average loss"
} else {
    consistency = "šŸ”“ Large average loss"
}

fmt.Printf("Avg profit/trade: $%.2f (%s)\n", profitPerTrade, consistency)

Example 5: Win/loss distributionĀ¶

stats, _ := sugar.GetDailyStats()

if stats.TotalDeals == 0 {
    return
}

// Visual representation
winPercent := int(stats.WinRate)
lossPercent := 100 - winPercent

fmt.Println("Win/Loss Distribution:")
fmt.Printf("[")
for i := 0; i < winPercent/2; i++ {
    fmt.Print("=")
}
fmt.Print("|")
for i := 0; i < lossPercent/2; i++ {
    fmt.Print("-")
}
fmt.Printf("]\n")
fmt.Printf("Wins: %d%% | Losses: %d%%\n", winPercent, lossPercent)

Example 6: Alert triggersĀ¶

func checkAlerts(stats *mt5.DailyStats) {
    // Alert 1: Low win rate
    if stats.TotalDeals >= 10 && stats.WinRate < 40 {
        fmt.Println("šŸšØ ALERT: Win rate below 40%")
    }

    // Alert 2: Large loss
    if stats.WorstDeal < -500 {
        fmt.Printf("šŸšØ ALERT: Large single loss $%.2f\n", stats.WorstDeal)
    }

    // Alert 3: Daily loss limit
    if stats.TotalProfit < -1000 {
        fmt.Printf("šŸšØ ALERT: Daily loss $%.2f exceeds limit\n", stats.TotalProfit)
    }

    // Alert 4: Consecutive losses
    if stats.LosingDeals >= 5 && stats.WinningDeals == 0 {
        fmt.Println("šŸšØ ALERT: 5+ consecutive losses")
    }

    // Alert 5: Excellent performance
    if stats.TotalDeals >= 10 && stats.WinRate >= 70 && stats.TotalProfit > 500 {
        fmt.Println("šŸŽ‰ EXCELLENT: Win rate >70% with >$500 profit!")
    }
}

Example 7: JSON exportĀ¶

stats, _ := sugar.GetDailyStats()

// Pretty print JSON
jsonData, _ := json.MarshalIndent(stats, "", "  ")
fmt.Println(string(jsonData))

// Output:
// {
//   "TotalDeals": 15,
//   "WinningDeals": 9,
//   "LosingDeals": 6,
//   "WinRate": 60.0,
//   "TotalProfit": 350.75,
//   "BestDeal": 125.50,
//   "WorstDeal": -87.25
// }

Example 8: CSV exportĀ¶

func exportStatsCSV(stats *mt5.DailyStats) {
    date := time.Now().Format("2006-01-02")

    csvLine := fmt.Sprintf("%s,%d,%d,%d,%.2f,%.2f,%.2f,%.2f\n",
        date,
        stats.TotalDeals,
        stats.WinningDeals,
        stats.LosingDeals,
        stats.WinRate,
        stats.TotalProfit,
        stats.BestDeal,
        stats.WorstDeal,
    )

    // Append to CSV file
    f, _ := os.OpenFile("daily_stats.csv", os.O_APPEND|os.O_CREATE|os.O_WRONLY, 0644)
    defer f.Close()

    f.WriteString(csvLine)
    fmt.Println("Stats exported to daily_stats.csv")
}

Example 9: Telegram notificationĀ¶

func sendTelegramReport(stats *mt5.DailyStats) string {
    emoji := "šŸ“Š"
    if stats.TotalProfit > 500 {
        emoji = "šŸš€"
    } else if stats.TotalProfit < -500 {
        emoji = "šŸ”“"
    }

    message := fmt.Sprintf(`
%s *Daily Trading Report*

šŸ“ˆ Performance:
ā€¢ Trades: %d
ā€¢ Win rate: %.1f%%
ā€¢ P/L: $%.2f

šŸ† Best trade: $%.2f
šŸ“‰ Worst trade: $%.2f

Status: %s
`,
        emoji,
        stats.TotalDeals,
        stats.WinRate,
        stats.TotalProfit,
        stats.BestDeal,
        stats.WorstDeal,
        getStatus(stats),
    )

    return message
}

func getStatus(stats *mt5.DailyStats) string {
    if stats.TotalProfit > 0 && stats.WinRate >= 60 {
        return "Excellent āœ…"
    } else if stats.TotalProfit > 0 {
        return "Profitable šŸ‘"
    } else {
        return "Needs improvement šŸ“‰"
    }
}

Example 10: Historical trackingĀ¶

type StatsHistory struct {
    Date  string
    Stats *mt5.DailyStats
}

var history []StatsHistory

func recordDailyStats(stats *mt5.DailyStats) {
    record := StatsHistory{
        Date:  time.Now().Format("2006-01-02"),
        Stats: stats,
    }

    history = append(history, record)

    // Calculate weekly averages (last 7 days)
    if len(history) >= 7 {
        last7 := history[len(history)-7:]

        totalTrades := 0
        totalProfit := 0.0
        totalWinRate := 0.0

        for _, rec := range last7 {
            totalTrades += rec.Stats.TotalDeals
            totalProfit += rec.Stats.TotalProfit
            totalWinRate += rec.Stats.WinRate
        }

        fmt.Println("\nšŸ“… WEEKLY SUMMARY (Last 7 days)")
        fmt.Printf("Total trades:  %d\n", totalTrades)
        fmt.Printf("Total profit:  $%.2f\n", totalProfit)
        fmt.Printf("Avg win rate:  %.1f%%\n", totalWinRate/7)
    }
}

āš ļø Important NotesĀ¶

  1. Today's range - 00:00 to current time (server time, not local)

  2. Closed positions only - Open positions not included

  3. Win rate - Based on closed deals, not tick-by-tick P/L

  4. Best/Worst - Absolute values, not averages

  5. Zero-profit deals - Excluded from win rate calculation

šŸ’” Quick ReferenceĀ¶

Field Range Good value Bad value
WinRate 0-100% >60% <40%
TotalProfit Any >$0 <-$500
BestDeal ā‰„0 Large Small
WorstDeal ā‰¤0 Small Large
TotalDeals ā‰„0 5-20 >50 (overtrading)

šŸŽ“ Performance BenchmarksĀ¶

Excellent DayĀ¶

  • Win rate: >70%
  • Total profit: >$500
  • Profit per trade: >$50
  • Best:Worst ratio: >2:1

Good DayĀ¶

  • Win rate: 55-70%
  • Total profit: >$200
  • Profit per trade: >$20
  • Best:Worst ratio: >1.5:1

Concerning DayĀ¶

  • Win rate: <40%
  • Total profit: <-$500
  • Profit per trade: <-$20
  • Best:Worst ratio: <1:1

Summary: DailyStats structure provides comprehensive daily trading metrics. Use WinRate and TotalProfit for performance assessment, BestDeal/WorstDeal for risk analysis. Essential for daily reports and trading journals.