diff --git a/mesa/visualization/components/matplotlib.py b/mesa/visualization/components/matplotlib.py
index a80ef4c2832..11fa9d87e5c 100644
--- a/mesa/visualization/components/matplotlib.py
+++ b/mesa/visualization/components/matplotlib.py
@@ -11,7 +11,7 @@
 from matplotlib.figure import Figure
 
 import mesa
-from mesa.experimental.cell_space import VoronoiGrid
+from mesa.experimental.cell_space import Grid, VoronoiGrid
 from mesa.space import PropertyLayer
 from mesa.visualization.utils import update_counter
 
@@ -52,16 +52,20 @@ def SpaceMatplotlib(
     if space is None:
         space = getattr(model, "space", None)
 
-    if isinstance(space, mesa.space._Grid):
-        _draw_grid(space, space_ax, agent_portrayal, propertylayer_portrayal, model)
-    elif isinstance(space, mesa.space.ContinuousSpace):
-        _draw_continuous_space(space, space_ax, agent_portrayal, model)
-    elif isinstance(space, mesa.space.NetworkGrid):
-        _draw_network_grid(space, space_ax, agent_portrayal)
-    elif isinstance(space, VoronoiGrid):
-        _draw_voronoi(space, space_ax, agent_portrayal)
-    elif space is None and propertylayer_portrayal:
-        draw_property_layers(space_ax, space, propertylayer_portrayal, model)
+    # https://stackoverflow.com/questions/67524641/convert-multiple-isinstance-checks-to-structural-pattern-matching
+    match space:
+        case mesa.space._Grid():
+            _draw_continuous_space(space, space_ax, agent_portrayal, model)
+        case mesa.space.NetworkGrid():
+            _draw_network_grid(space, space_ax, agent_portrayal)
+        case VoronoiGrid():
+            _draw_voronoi(space, space_ax, agent_portrayal)
+        case Grid():  # matches OrthogonalMooreGrid, OrthogonalVonNeumannGrid, and Hexgrid
+            # fixme add a separate draw method for hexgrids in the future
+            _draw_discrete_space_grid(space, space_ax, agent_portrayal)
+        case None:
+            if propertylayer_portrayal:
+                draw_property_layers(space_ax, space, propertylayer_portrayal, model)
 
     solara.FigureMatplotlib(
         space_fig, format="png", bbox_inches="tight", dependencies=dependencies
@@ -291,6 +295,44 @@ def portray(g):
         space_ax.plot(*zip(*polygon), color="black")  # Plot polygon edges in black
 
 
+def _draw_discrete_space_grid(space: Grid, space_ax, agent_portrayal):
+    if space._ndims != 2:
+        raise ValueError("Space must be 2D")
+
+    def portray(g):
+        x = []
+        y = []
+        s = []  # size
+        c = []  # color
+
+        for cell in g.all_cells:
+            for agent in cell.agents:
+                data = agent_portrayal(agent)
+                x.append(cell.coordinate[0])
+                y.append(cell.coordinate[1])
+                if "size" in data:
+                    s.append(data["size"])
+                if "color" in data:
+                    c.append(data["color"])
+        out = {"x": x, "y": y}
+        out["s"] = s
+        if len(c) > 0:
+            out["c"] = c
+
+        return out
+
+    space_ax.set_xlim(0, space.width)
+    space_ax.set_ylim(0, space.height)
+
+    # Draw grid lines
+    for x in range(space.width + 1):
+        space_ax.axvline(x, color="gray", linestyle=":")
+    for y in range(space.height + 1):
+        space_ax.axhline(y, color="gray", linestyle=":")
+
+    space_ax.scatter(**portray(space))
+
+
 def make_plot_measure(measure: str | dict[str, str] | list[str] | tuple[str]):
     """Create a plotting function for a specified measure.