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FAQ.md

@@ -61,6 +61,19 @@ Use the full methods if you want richer diagnostics.
 The bundle will still run.
 But prediction quality may be weaker because richer fields will use fallback defaults.
 
+## Why does the model talk about 48 signals if the sample CSV has fewer raw columns?
+Because the wrapper builds the final model input row before inference.
+
+Some signals come from:
+- raw columns already present in the history CSV
+- rolling features derived from past match results
+- fallback defaults when richer optional columns are missing
+
+So:
+- the model expects `48` numeric signals at prediction time
+- your history CSV does not need to contain all `48` as raw columns
+- but a richer CSV helps the wrapper build a stronger feature row
+
 ## Will I get the exact same answers as your internal environment?
 Not necessarily.