diff --git a/pandas/core/frame.py b/pandas/core/frame.py
index 0f6fa43e020891..67360122ed0214 100644
--- a/pandas/core/frame.py
+++ b/pandas/core/frame.py
@@ -5279,24 +5279,17 @@ def _arith_op(left, right):
             new_data = dispatch_fill_zeros(func, this.values, other.values, res_values)
         return this._construct_result(new_data)
 
-    def _combine_match_index(self, other, func, level=None):
-        left, right = self.align(other, join="outer", axis=0, level=level, copy=False)
-        # at this point we have `left.index.equals(right.index)`
+    def _combine_match_index(self, other, func):
+        # at this point we have `self.index.equals(other.index)`
 
-        if left._is_mixed_type or right._is_mixed_type:
+        if self._is_mixed_type or other._is_mixed_type:
             # operate column-wise; avoid costly object-casting in `.values`
-            new_data = ops.dispatch_to_series(left, right, func)
+            new_data = ops.dispatch_to_series(self, other, func)
         else:
             # fastpath --> operate directly on values
             with np.errstate(all="ignore"):
-                new_data = func(left.values.T, right.values).T
-        return left._construct_result(new_data)
-
-    def _combine_match_columns(self, other: Series, func, level=None):
-        left, right = self.align(other, join="outer", axis=1, level=level, copy=False)
-        # at this point we have `left.columns.equals(right.index)`
-        new_data = ops.dispatch_to_series(left, right, func, axis="columns")
-        return left._construct_result(new_data)
+                new_data = func(self.values.T, other.values).T
+        return new_data
 
     def _construct_result(self, result) -> "DataFrame":
         """
diff --git a/pandas/core/ops/__init__.py b/pandas/core/ops/__init__.py
index 79272c56432817..c979b473ad09ac 100644
--- a/pandas/core/ops/__init__.py
+++ b/pandas/core/ops/__init__.py
@@ -384,7 +384,7 @@ def column_op(a, b):
             return {i: func(a.iloc[:, i], b.iloc[:, i]) for i in range(len(a.columns))}
 
     elif isinstance(right, ABCSeries) and axis == "columns":
-        # We only get here if called via left._combine_match_columns,
+        # We only get here if called via _combine_frame_series,
         # in which case we specifically want to operate row-by-row
         assert right.index.equals(left.columns)
 
@@ -613,15 +613,18 @@ def _combine_series_frame(self, other, func, fill_value=None, axis=None, level=N
             "fill_value {fill} not supported.".format(fill=fill_value)
         )
 
-    if axis is not None:
-        axis = self._get_axis_number(axis)
-        if axis == 0:
-            return self._combine_match_index(other, func, level=level)
-        else:
-            return self._combine_match_columns(other, func, level=level)
+    if axis is None:
+        # default axis is columns
+        axis = 1
+
+    axis = self._get_axis_number(axis)
+    left, right = self.align(other, join="outer", axis=axis, level=level, copy=False)
+    if axis == 0:
+        new_data = left._combine_match_index(right, func)
+    else:
+        new_data = dispatch_to_series(left, right, func, axis="columns")
 
-    # default axis is columns
-    return self._combine_match_columns(other, func, level=level)
+    return left._construct_result(new_data)
 
 
 def _align_method_FRAME(left, right, axis):