diff --git a/AppImage/components/latency-detail-modal.tsx b/AppImage/components/latency-detail-modal.tsx
index bd324da3..968f6fae 100644
--- a/AppImage/components/latency-detail-modal.tsx
+++ b/AppImage/components/latency-detail-modal.tsx
@@ -63,21 +63,46 @@ interface LatencyDetailModalProps {
 const CustomTooltip = ({ active, payload, label }: any) => {
   if (active && payload && payload.length) {
     const entry = payload[0]
-    const packetLoss = entry?.payload?.packet_loss
+    const data = entry?.payload
+    const packetLoss = data?.packet_loss
+    const hasMinMax = data?.min !== undefined && data?.max !== undefined && data?.min !== data?.max
+    
     return (
       <div className="bg-gray-900/95 backdrop-blur-sm border border-gray-700 rounded-lg p-3 shadow-xl">
         <p className="text-sm font-semibold text-white mb-2">{label}</p>
         <div className="space-y-1.5">
-          <div className="flex items-center gap-2">
-            <div className="w-2.5 h-2.5 rounded-full flex-shrink-0 bg-blue-500" />
-            <span className="text-xs text-gray-300 min-w-[60px]">Latency:</span>
-            <span className="text-sm font-semibold text-white">{entry.value} ms</span>
-          </div>
+          {hasMinMax ? (
+            // Show min/avg/max when downsampled data is available
+            <>
+              <div className="flex items-center gap-2">
+                <div className="w-2.5 h-2.5 rounded-full flex-shrink-0 bg-green-500" />
+                <span className="text-xs text-gray-300 min-w-[60px]">Min:</span>
+                <span className="text-sm font-semibold text-green-400">{data.min} ms</span>
+              </div>
+              <div className="flex items-center gap-2">
+                <div className="w-2.5 h-2.5 rounded-full flex-shrink-0 bg-blue-500" />
+                <span className="text-xs text-gray-300 min-w-[60px]">Avg:</span>
+                <span className="text-sm font-semibold text-white">{data.value} ms</span>
+              </div>
+              <div className="flex items-center gap-2">
+                <div className="w-2.5 h-2.5 rounded-full flex-shrink-0 bg-red-500" />
+                <span className="text-xs text-gray-300 min-w-[60px]">Max:</span>
+                <span className="text-sm font-semibold text-red-400">{data.max} ms</span>
+              </div>
+            </>
+          ) : (
+            // Simple latency display for single data points
+            <div className="flex items-center gap-2">
+              <div className="w-2.5 h-2.5 rounded-full flex-shrink-0 bg-blue-500" />
+              <span className="text-xs text-gray-300 min-w-[60px]">Latency:</span>
+              <span className="text-sm font-semibold text-white">{entry.value} ms</span>
+            </div>
+          )}
           {packetLoss !== undefined && packetLoss > 0 && (
             <div className="flex items-center gap-2">
-              <div className="w-2.5 h-2.5 rounded-full flex-shrink-0 bg-red-500" />
+              <div className="w-2.5 h-2.5 rounded-full flex-shrink-0 bg-orange-500" />
               <span className="text-xs text-gray-300 min-w-[60px]">Pkt Loss:</span>
-              <span className="text-sm font-semibold text-red-400">{packetLoss}%</span>
+              <span className="text-sm font-semibold text-orange-400">{packetLoss}%</span>
             </div>
           )}
         </div>
@@ -1083,9 +1108,11 @@ export function LatencyDetailModal({ open, onOpenChange, currentLatency }: Laten
                   tickFormatter={(v) => `${Number(v).toFixed(1)}ms`}
                 />
                 <Tooltip content={<CustomTooltip />} />
+                {/* For longer timeframes (6h+), show max values to preserve spikes.
+                    For 1 hour view, show avg values since there's no downsampling */}
                 <Area
                   type="monotone"
-                  dataKey="value"
+                  dataKey={timeframe === "hour" ? "value" : "max"}
                   stroke="#3b82f6"
                   strokeWidth={2}
                   fill="url(#latencyGradient)"
diff --git a/AppImage/scripts/flask_server.py b/AppImage/scripts/flask_server.py
index 15f57832..17714c47 100644
--- a/AppImage/scripts/flask_server.py
+++ b/AppImage/scripts/flask_server.py
@@ -746,28 +746,21 @@ def get_latency_history(target='gateway', timeframe='hour'):
         
         conn.close()
         
-        # Compute stats
+        # Compute stats - always use actual min/max values to preserve spikes
         if data:
             values = [d["value"] for d in data if d["value"] is not None]
+            mins = [d["min"] for d in data if d.get("min") is not None]
+            maxs = [d["max"] for d in data if d.get("max") is not None]
+            
             if values:
-                # For gateway, use min/max of the averages (values) so stats match the graph
-                # For other targets (realtime), use actual min/max from individual pings
-                if target == 'gateway':
-                    stats = {
-                        "min": round(min(values), 1),
-                        "max": round(max(values), 1),
-                        "avg": round(sum(values) / len(values), 1),
-                        "current": values[-1] if values else 0
-                    }
-                else:
-                    mins = [d["min"] for d in data if d.get("min") is not None]
-                    maxs = [d["max"] for d in data if d.get("max") is not None]
-                    stats = {
-                        "min": round(min(mins) if mins else min(values), 1),
-                        "max": round(max(maxs) if maxs else max(values), 1),
-                        "avg": round(sum(values) / len(values), 1),
-                        "current": values[-1] if values else 0
-                    }
+                stats = {
+                    # Use actual min from all samples (preserves lowest value)
+                    "min": round(min(mins) if mins else min(values), 1),
+                    # Use actual max from all samples (preserves spikes)
+                    "max": round(max(maxs) if maxs else max(values), 1),
+                    "avg": round(sum(values) / len(values), 1),
+                    "current": values[-1] if values else 0
+                }
             else:
                 stats = {"min": 0, "max": 0, "avg": 0, "current": 0}
         else: