Add relevant metrics to backtest breakdowns

freqtrade/optimize/optimize_reports/bt_output.py

@@ -132,18 +132,18 @@ def text_table_periodic_breakdown(
     """
     headers = [
         period.capitalize(),
+        "Trades",
         f"Tot Profit {stake_currency}",
-        "Wins",
+        "Profit Factor",
-        "Draws",
+        "Win  Draw  Loss  Win%",
-        "Losses",
     ]
     output = [
         [
             d["date"],
+            d["trades"],
             fmt_coin(d["profit_abs"], stake_currency, False),
-            d["wins"],
+            d["profit_factor"],
-            d["draws"],
+            generate_wins_draws_losses(d["wins"], d["draws"], d["losses"]),
-            d["loses"],
         ]
         for d in days_breakdown_stats
     ]

freqtrade/optimize/optimize_reports/optimize_reports.py

@@ -231,8 +231,11 @@ def generate_periodic_breakdown_stats(
         profit_abs = day["profit_abs"].sum().round(10)
         wins = sum(day["profit_abs"] > 0)
         draws = sum(day["profit_abs"] == 0)
-        loses = sum(day["profit_abs"] < 0)
+        losses = sum(day["profit_abs"] < 0)
-        trades = wins + draws + loses
+        trades = wins + draws + losses
+        winning_profit = day.loc[day["profit_abs"] > 0, "profit_abs"].sum()
+        losing_profit = day.loc[day["profit_abs"] < 0, "profit_abs"].sum()
+        profit_factor = winning_profit / abs(losing_profit) if losing_profit else 0.0
         stats.append(
             {
                 "date": name.strftime("%d/%m/%Y"),
@@ -240,8 +243,9 @@ def generate_periodic_breakdown_stats(
                 "profit_abs": profit_abs,
                 "wins": wins,
                 "draws": draws,
-                "loses": loses,
+                "losses": losses,
-                "winrate": wins / trades if trades else 0.0,
+                "trades" : trades,
+                'profit_factor': round(profit_factor, 2),
             }
         )
     return stats