diff --git a/freqtrade/templates/freqaiprimer.py b/freqtrade/templates/freqaiprimer.py
index ec7beb6a..bd743c68 100644
--- a/freqtrade/templates/freqaiprimer.py
+++ b/freqtrade/templates/freqaiprimer.py
@@ -743,69 +743,6 @@ class FreqaiPrimer(IStrategy):
         # 设置入场信号
         dataframe.loc[final_condition, 'enter_long'] = 1
         
-        # ========== 新增：入场诊断统计（回测可用） ==========
-        # 对每个入场信号输出详细诊断信息
-        entry_signals = dataframe[dataframe['enter_long'] == 1]
-        if len(entry_signals) > 0:
-            for idx in entry_signals.index[-5:]:  # 只输出最近 5 个信号，避免日志过多
-                row = dataframe.loc[idx]
-                current_close = float(row['close'])
-                
-                # 1. 价格与短期高点的关系
-                recent_high_5 = float(dataframe.loc[max(0, idx-4):idx+1, 'high'].max()) if idx >= 4 else current_close
-                price_vs_recent_high = (current_close - recent_high_5) / recent_high_5 if recent_high_5 > 0 else 0
-                
-                # 2. 价格与 EMA5 的关系
-                ema5_1h = float(row.get('ema_5_1h', current_close))
-                price_vs_ema5 = (current_close - ema5_1h) / ema5_1h if ema5_1h > 0 else 0
-                
-                # 3. 价格与布林带的位置
-                bb_upper = float(row.get('bb_upper_1h', current_close))
-                bb_lower = float(row.get('bb_lower_1h', current_close))
-                bb_position = (current_close - bb_lower) / (bb_upper - bb_lower) if (bb_upper - bb_lower) > 0 else 0.5
-                
-                # 4. RSI 状态
-                rsi_1h = float(row.get('rsi_1h', 50))
-                
-                # 5. MACD 状态
-                macd_1h = float(row.get('macd_1h', 0))
-                macd_signal_1h = float(row.get('macd_signal_1h', 0))
-                macd_cross = 'up' if macd_1h > macd_signal_1h else 'down'
-                
-                # 6. 市场状态
-                market_state = str(row.get('market_state', 'unknown'))
-                
-                # 7. ML 入场概率（如果有）
-                entry_prob = None
-                if '&s-entry_signal' in dataframe.columns:
-                    val = row.get('&s-entry_signal', 0)
-                    if val is not None and str(val).strip():  # 检查非空且非空白
-                        try:
-                            entry_prob = float(val)
-                        except (ValueError, TypeError):
-                            pass
-                elif '&-entry_signal' in dataframe.columns:
-                    val = row.get('&-entry_signal', 0)
-                    if val is not None and str(val).strip():
-                        try:
-                            entry_prob = float(val)
-                        except (ValueError, TypeError):
-                            pass
-                
-                # 输出诊断日志
-                ml_prob_str = f"{entry_prob:.2f}" if entry_prob is not None else "N/A"
-                self.strategy_log(
-                    f"[入场诊断] {metadata['pair']} | "
-                    f"价格: {current_close:.6f} | "
-                    f"vs 5K高点: {price_vs_recent_high:+.2%} | "
-                    f"vs EMA5: {price_vs_ema5:+.2%} | "
-                    f"布林位置: {bb_position:.2f} | "
-                    f"RSI: {rsi_1h:.1f} | "
-                    f"MACD: {macd_cross} | "
-                    f"市场: {market_state} | "
-                    f"ML概率: {ml_prob_str}"
-                )
-        # ========== 诊断统计结束 ==========
         
         # 设置入场价格：下调1.67%（使用乘法避免除零风险）
         final_condition_updated = dataframe['enter_long'] == 1
@@ -1016,7 +953,7 @@ class FreqaiPrimer(IStrategy):
                         
                         # 基本信息
                         basic_info = (
-                            f"[入场诊断] {pair} | "
+                            f"[入场诊断1] {pair} | "
                             f"价格: {current_close:.6f} | "
                             f"vs 5K高点: {price_vs_recent_high:+.2%} | "
                             f"vs EMA5: {price_vs_ema5:+.2%}"
@@ -1035,7 +972,6 @@ class FreqaiPrimer(IStrategy):
                             f"ML入场概率: {ml_prob_str}"
                         )
                         
-                        self.strategy_log(basic_info + " | " + tech_info + " | " + env_info)
                         # ========== 诊断统计结束 ==========
                         
                         if entry_prob is not None:
@@ -1062,6 +998,7 @@ class FreqaiPrimer(IStrategy):
                                 allow_trade = False
                             else:
                                 self.strategy_log(f"[{pair}] ML 审核官允许入场: entry_signal 概率 {entry_prob:.2f} >= 阈值 {entry_threshold:.2f}（市场: {market_state}）")
+                                self.strategy_log(basic_info + " | " + tech_info + " | " + env_info)
                 except Exception as e:
                     logger.warning(f"[{pair}] ML 审核官检查失败，忽略 ML 过滤: {e}")
         return allow_trade