diff --git a/reccmp/tools/asmcmp.py b/reccmp/tools/asmcmp.py
index f40afb6a..90ee71bf 100755
--- a/reccmp/tools/asmcmp.py
+++ b/reccmp/tools/asmcmp.py
@@ -264,6 +264,10 @@ def main():
 
     ### Compare everything.
 
+    # Count how many functions have the same virtual address in orig and recomp.
+    functions_aligned_count = 0
+
+    # Number of functions compared (i.e. excluding stubs)
     function_count = 0
     total_accuracy = 0
     total_effective_accuracy = 0
@@ -275,6 +279,12 @@ def main():
                 match, show_both_addrs=args.print_rec_addr, is_plain=args.no_color
             )
 
+        if (
+            match.match_type == SymbolType.FUNCTION
+            and match.orig_addr == match.recomp_addr
+        ):
+            functions_aligned_count += 1
+
         if match.match_type == SymbolType.FUNCTION and not match.is_stub:
             function_count += 1
             total_accuracy += match.ratio
@@ -322,15 +332,22 @@ def main():
 
     implemented_funcs = function_count
 
+    # If we know how many functions are in the file (via analysis with Ghidra or other tools)
+    # we can substitute an alternate value to use when calculating the percentages below.
     if args.total:
-        function_count = int(args.total)
+        # Use the alternate value if it exceeds the number of annotated functions
+        function_count = max(function_count, int(args.total))
 
     if function_count > 0:
         effective_accuracy = total_effective_accuracy / function_count * 100
         actual_accuracy = total_accuracy / function_count * 100
+        alignment_percentage = functions_aligned_count / function_count * 100
         print(
             f"\nTotal effective accuracy {effective_accuracy:.2f}% across {function_count} functions ({actual_accuracy:.2f}% actual accuracy)"
         )
+        print(
+            f"{functions_aligned_count} functions are aligned ({alignment_percentage:.2f}%)"
+        )
 
         if args.svg is not None:
             gen_svg(