diff --git a/examples/plot_season_summary.py b/examples/plot_season_summary.py
new file mode 100644
index 00000000..0422d492
--- /dev/null
+++ b/examples/plot_season_summary.py
@@ -0,0 +1,196 @@
+"""
+Season Summary Visualization
+==================================
+
+This example demonstrates how to summarize the season by visualizing
+race results, points progression, and other key statistics.
+
+.. codeauthor:: Vandana
+"""
+
+import logging
+
+import numpy as np
+import pandas as pd
+import plotly.graph_objects as go
+from plotly.io import show
+from plotly.subplots import make_subplots
+
+import fastf1
+
+
+logging.basicConfig(filename="debug.log", level=logging.WARNING)
+fastf1.logger.set_log_level(logging.WARNING)
+
+# Enable FastF1 cache
+fastf1.Cache.enable_cache("../cache")
+
+# Define sprint points allocation
+SPRINT_POINTS = {1: 8, 2: 7, 3: 6, 4: 5, 5: 4, 6: 3, 7: 2, 8: 1}
+
+# Load the event schedule and filter out testing events
+schedules = fastf1.get_event_schedule(2022)
+races = schedules[schedules["EventName"].str.contains("Grand Prix", na=False)]
+
+# Prepare standings data
+standings = []
+
+for _, race in races.iterrows():  # Iterate over the filtered races
+    race_name = race["OfficialEventName"]
+    round_number = race["RoundNumber"]
+
+    # Fetch the race session
+    session = fastf1.get_session(2022, round_number, "R")  # Race session
+    session.load()
+
+    # Check for a sprint session (if exists)
+    sprint_session = None
+
+    try:
+        sprint_session = fastf1.get_session(2022, round_number, "Sprint")
+        sprint_session.load()
+    except Exception:
+        pass
+
+    # Fetch race data
+    race_results = session.results
+    for driver in race_results["Abbreviation"]:
+        driver_result = race_results[race_results["Abbreviation"] == driver]
+        points = driver_result["Points"].iloc[0]  # Race points
+        position = driver_result["Position"].iloc[0]
+
+        # Add sprint race points if applicable
+        if sprint_session is not None:
+            sprint_results = sprint_session.results
+            if driver in sprint_results["Abbreviation"].values:
+                sprint_position = sprint_results[
+                    sprint_results["Abbreviation"] == driver
+                ]["Position"].iloc[0]
+                sprint_points = SPRINT_POINTS.get(sprint_position, 0)
+            else:
+                sprint_points = 0
+        else:
+            sprint_points = 0
+
+        standings.append(
+            {
+                "Race": race_name,
+                "RoundNumber": round_number,
+                "Driver": driver,
+                "Points": points + sprint_points,  # Ignore fastest lap points
+                "Position": position,
+            }
+        )
+
+df = pd.DataFrame(standings)
+
+# Prepare heatmap data
+heatmap_data = df.pivot(
+    index="Driver", columns="RoundNumber", values="Points"
+).fillna(0)
+heatmap_data["Total Points"] = heatmap_data.sum(axis=1)
+heatmap_data = heatmap_data.sort_values(by="Total Points", ascending=True)
+
+# Prepare position data
+position_data = df.pivot(
+    index="Driver", columns="RoundNumber", values="Position"
+).fillna("N/A")
+
+# Map race names
+race_name_mapping = dict(zip(schedules["RoundNumber"], schedules["EventName"]))
+
+# Simplify x-axis labels
+heatmap_data_rounds = heatmap_data.iloc[:, :-1]
+x_labels_rounds = [str(race) for race in heatmap_data.columns[:-1]]
+x_labels_total = ["Total Points"]
+
+# Custom colorscales
+colorscale_rounds = [[0, "#aee2fb"], [0.433, "#69bce8"], [1, "#3085be"]]
+colorscale_total = [[0, "#ffcccc"], [0.433, "#ff6666"], [1, "#cc0000"]]
+
+# Prepare custom_data for hover information (only for rounds)
+custom_data = np.array(
+    [
+        [
+            {
+                "position": position_data.at[driver, race]
+                if race in position_data.columns
+                else "N/A",
+                "race_name": race_name_mapping.get(race, "Unknown"),
+            }
+            for race in heatmap_data.columns[:-1]
+        ]
+        for driver in heatmap_data.index
+    ]
+)
+
+custom_data_rounds = custom_data[:, :-1]
+
+# Get max values for normalization
+max_points_rounds = heatmap_data_rounds.values.max()
+max_points_total = heatmap_data.iloc[:, -1:].values.max()
+
+# Create subplots for two heatmaps
+fig = make_subplots(
+    rows=1,
+    cols=2,
+    column_widths=[0.85, 0.15],
+    horizontal_spacing=0.05,
+    subplot_titles=("F1 2022 Season Rounds", "Total Points"),
+)
+
+# Heatmap for individual rounds
+fig.add_trace(
+    go.Heatmap(
+        z=heatmap_data_rounds.values,
+        x=x_labels_rounds,
+        y=heatmap_data_rounds.index,
+        customdata=custom_data,
+        text=heatmap_data_rounds.values,
+        texttemplate="%{text}",
+        textfont={"size": 12},
+        colorscale=colorscale_rounds,
+        showscale=False,
+        zmin=0,
+        zmax=max_points_rounds,
+        hovertemplate=(
+            "Driver: %{y}<br>"
+            "Round: %{x}<br>"
+            "Race Name: %{customdata.race_name}<br>"
+            "Points: %{z}<br>"
+            "Position: %{customdata.position}<extra></extra>"
+        ),
+    ),
+    row=1,
+    col=1,
+)
+
+# Heatmap for total points
+fig.add_trace(
+    go.Heatmap(
+        z=heatmap_data.iloc[:, -1:].values,
+        x=x_labels_total,
+        y=heatmap_data.index,
+        text=heatmap_data.iloc[:, -1:].values,
+        texttemplate="%{text}",
+        textfont={"size": 12},
+        colorscale=colorscale_total,
+        showscale=False,
+        hoverinfo="none",
+        zmin=0,
+        zmax=max_points_total,
+    ),
+    row=1,
+    col=2,
+)
+
+# Update layout
+fig.update_xaxes(title_text="Rounds", row=1, col=1)
+fig.update_yaxes(title_text="Drivers", row=1, col=1)
+fig.update_layout(title="F1 Results Tracker Heatmap")
+
+# Plot the updated heatmap
+show(fig)
+fig.write_image(
+    "../docs/_build/html/gen_modules/examples_gallery/temp-plot.png"
+)