A basketball shot chart overlays shooting data on a half-court diagram, plotting each shot attempt as a point colored by outcome (made or missed). The court drawing includes the three-point arc, free-throw line, paint/key area, and basket, providing spatial context for analyzing shooting patterns and efficiency. Essential for basketball analytics and player evaluation.
""" anyplot.ai
scatter-shot-chart: Basketball Shot Chart
Library: bokeh 3.9.1 | Python 3.13.14
Quality: 86/100 | Updated: 2026-06-21
"""
import os
import sys
# Prevent self-import: this file is named bokeh.py, which shadows the installed
# bokeh package when its directory sits at the front of sys.path.
_this_dir = os.path.dirname(os.path.abspath(__file__))
sys.path = [p for p in sys.path if os.path.abspath(p or ".") != _this_dir]
import time
from pathlib import Path
import numpy as np
from bokeh.io import output_file, save
from bokeh.models import ColumnDataSource, HoverTool, Label, Legend, LegendItem, Range1d
from bokeh.plotting import figure
from bokeh.resources import CDN
from selenium import webdriver
from selenium.webdriver.chrome.options import Options
# Theme tokens — Imprint palette / anyplot style guide
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
INK_MUTED = "#6B6A63" if THEME == "light" else "#A8A79F"
# Imprint palette — semantic exception: made=good/pass→green, missed=bad/fail→red
MADE_COLOR = "#009E73" # Imprint position 1 (brand green, semantic: good/pass)
MISSED_COLOR = "#AE3030" # Imprint position 5 (matte red, semantic: bad/fail)
# Court surface — distinct from page background for both themes
COURT_FLOOR = "#EDE8DC" if THEME == "light" else "#242420"
COURT_LINE = INK_SOFT # theme-adaptive court lines
# Data
np.random.seed(42)
n_shots = 350
x = np.zeros(n_shots)
y = np.zeros(n_shots)
made = np.zeros(n_shots, dtype=bool)
shot_type = []
zone_label = []
for i in range(n_shots):
zone = np.random.choice(["paint", "midrange", "three", "corner3", "ft"], p=[0.25, 0.20, 0.30, 0.10, 0.15])
if zone == "paint":
x[i] = np.random.uniform(-8, 8)
y[i] = np.random.uniform(0, 12)
made[i] = np.random.random() < 0.55
shot_type.append("2-pointer")
zone_label.append("Paint")
elif zone == "midrange":
x[i] = np.random.uniform(-16, 16)
y[i] = np.random.uniform(5, 20)
dist = np.sqrt(x[i] ** 2 + y[i] ** 2)
while dist > 23.0 or dist < 5:
x[i] = np.random.uniform(-16, 16)
y[i] = np.random.uniform(5, 20)
dist = np.sqrt(x[i] ** 2 + y[i] ** 2)
made[i] = np.random.random() < 0.42
shot_type.append("2-pointer")
zone_label.append("Mid-Range")
elif zone == "three":
angle = np.random.uniform(0.25, np.pi - 0.25)
r = np.random.uniform(24, 28)
x[i] = r * np.cos(angle)
y[i] = r * np.sin(angle)
x[i] = np.clip(x[i], -24, 24)
y[i] = np.clip(y[i], 10, 33)
made[i] = np.random.random() < 0.36
shot_type.append("3-pointer")
zone_label.append("Three-Point")
elif zone == "corner3":
side = np.random.choice([-1, 1])
x[i] = side * np.random.uniform(21.5, 23)
y[i] = np.random.uniform(0, 10)
made[i] = np.random.random() < 0.39
shot_type.append("3-pointer")
zone_label.append("Corner 3")
else:
x[i] = np.random.uniform(-1.5, 1.5)
y[i] = np.random.uniform(13.5, 16.5)
made[i] = np.random.random() < 0.78
shot_type.append("free-throw")
zone_label.append("Free Throw")
shot_type = np.array(shot_type)
zone_label = np.array(zone_label)
# Zone efficiency stats for data storytelling
zones = ["Paint", "Mid-Range", "Three-Point", "Corner 3", "Free Throw"]
zone_stats = {}
for z in zones:
mask = zone_label == z
z_made = int(np.sum(made[mask]))
z_total = int(np.sum(mask))
z_pct = z_made / z_total * 100 if z_total > 0 else 0
zone_stats[z] = (z_made, z_total, z_pct)
# Canvas — 2400×2400 (square, canonical for symmetric shot chart).
# y_range (-12, 42) = 54 units, matching x_range = 54 units so match_aspect=True
# fills the square canvas uniformly. min_border_top trimmed to reduce chrome overhead.
title = "scatter-shot-chart · python · bokeh · anyplot.ai"
p = figure(
width=2400,
height=2400,
title=title,
x_range=Range1d(-27, 27),
y_range=Range1d(-12, 42),
toolbar_location=None,
match_aspect=True,
min_border_bottom=50,
min_border_left=60,
min_border_top=100,
min_border_right=60,
)
# Court floor — covers the full visible data range
p.rect(x=0, y=15, width=60, height=60, fill_color=COURT_FLOOR, line_color=None)
# Baseline and sidelines (half-court)
p.line([-25, 25], [0, 0], line_color=COURT_LINE, line_width=5)
p.line([-25, -25], [0, 35], line_color=COURT_LINE, line_width=3)
p.line([25, 25], [0, 35], line_color=COURT_LINE, line_width=3)
# Paint / key area (16 ft wide, 19 ft deep from baseline)
p.line([-8, -8, 8, 8], [0, 19, 19, 0], line_color=COURT_LINE, line_width=3)
# Free-throw circle (solid top half, dashed bottom half)
theta_top = np.linspace(0, np.pi, 100)
theta_bot = np.linspace(np.pi, 2 * np.pi, 100)
p.line(6 * np.cos(theta_top), 19 + 6 * np.sin(theta_top), line_color=COURT_LINE, line_width=3)
p.line(6 * np.cos(theta_bot), 19 + 6 * np.sin(theta_bot), line_color=COURT_LINE, line_width=2, line_dash="dashed")
# Restricted area arc (4 ft radius from basket)
theta_ra = np.linspace(0, np.pi, 100)
p.line(4 * np.cos(theta_ra), 4 * np.sin(theta_ra), line_color=COURT_LINE, line_width=2)
# Three-point arc (23.75 ft at top, 22 ft in corners)
theta_3pt = np.linspace(np.arccos(22.0 / 23.75), np.pi - np.arccos(22.0 / 23.75), 200)
p.line(23.75 * np.cos(theta_3pt), 23.75 * np.sin(theta_3pt), line_color=COURT_LINE, line_width=3)
# Corner three-point lines (22 ft from basket, straight to baseline)
corner_y = 23.75 * np.sin(np.arccos(22.0 / 23.75))
p.line([-22, -22], [0, corner_y], line_color=COURT_LINE, line_width=3)
p.line([22, 22], [0, corner_y], line_color=COURT_LINE, line_width=3)
# Basket (hoop at ~1.5 ft from backboard)
hoop_theta = np.linspace(0, 2 * np.pi, 50)
p.line(0.75 * np.cos(hoop_theta), 0.75 * np.sin(hoop_theta) + 1.5, line_color="#C44E2B", line_width=5)
p.line([-3, 3], [0, 0], line_color=INK_SOFT, line_width=6)
# Shot data sources
made_mask = made
missed_mask = ~made
result_label = np.where(made, "Made", "Missed")
distance = np.round(np.sqrt(x**2 + y**2), 1)
source_made = ColumnDataSource(
data={
"x": x[made_mask],
"y": y[made_mask],
"result": result_label[made_mask],
"zone": zone_label[made_mask],
"shot_type": shot_type[made_mask],
"distance": distance[made_mask],
}
)
source_missed = ColumnDataSource(
data={
"x": x[missed_mask],
"y": y[missed_mask],
"result": result_label[missed_mask],
"zone": zone_label[missed_mask],
"shot_type": shot_type[missed_mask],
"distance": distance[missed_mask],
}
)
r_made = p.scatter(
x="x",
y="y",
source=source_made,
size=16,
fill_color=MADE_COLOR,
fill_alpha=0.60,
line_color=PAGE_BG,
line_width=1.2,
marker="circle",
)
r_missed = p.scatter(
x="x",
y="y",
source=source_missed,
size=16,
fill_color=None,
fill_alpha=0,
line_color=MISSED_COLOR,
line_width=3.5,
marker="x",
)
# HoverTool — Bokeh's signature interactive feature
hover = HoverTool(
renderers=[r_made, r_missed],
tooltips=[("Result", "@result"), ("Zone", "@zone"), ("Shot Type", "@shot_type"), ("Distance", "@distance ft")],
point_policy="snap_to_data",
)
p.add_tools(hover)
# Legend (horizontal, above the plot area)
n_made = int(np.sum(made))
n_missed = int(np.sum(~made))
legend = Legend(
items=[
LegendItem(label=f"Made ({n_made})", renderers=[r_made]),
LegendItem(label=f"Missed ({n_missed})", renderers=[r_missed]),
],
location="top_center",
orientation="horizontal",
)
p.add_layout(legend, "above")
p.legend.label_text_font_size = "28pt"
p.legend.label_text_color = INK_SOFT
p.legend.glyph_width = 40
p.legend.glyph_height = 40
p.legend.spacing = 50
p.legend.padding = 20
p.legend.background_fill_alpha = 0.0
p.legend.border_line_color = None
# FG% summary — placed above the three-point arc in the open court floor area
fg_pct = n_made / n_shots * 100
p.add_layout(
Label(
x=0,
y=32,
text=f"FG: {fg_pct:.1f}% · {n_shots} attempts",
text_font_size="24pt",
text_color=INK_MUTED,
text_align="center",
text_font_style="bold",
)
)
# Zone efficiency overlays with made/total counts
zone_positions = {
"Paint": [(3, 6)],
"Mid-Range": [(15, 14)],
"Three-Point": [(0, 27)],
"Corner 3": [(-21, 4), (21, 4)],
"Free Throw": [(18, 16)],
}
for z, positions in zone_positions.items():
z_made, z_total, z_pct = zone_stats[z]
for zx, zy in positions:
p.add_layout(
Label(
x=zx,
y=zy,
text=f"{z_pct:.0f}%",
text_font_size="22pt",
text_color=INK,
text_align="center",
text_font_style="bold",
background_fill_color=ELEVATED_BG,
background_fill_alpha=0.85,
)
)
p.add_layout(
Label(
x=zx,
y=zy - 2.0,
text=f"{z_made}/{z_total}",
text_font_size="18pt",
text_color=INK_SOFT,
text_align="center",
background_fill_color=ELEVATED_BG,
background_fill_alpha=0.85,
)
)
# Chrome — theme-adaptive
p.title.text_font_size = "50pt"
p.title.text_color = INK
p.title.text_font_style = "bold"
p.title.align = "center"
p.xaxis.visible = False
p.yaxis.visible = False
p.xgrid.grid_line_color = None
p.ygrid.grid_line_color = None
p.background_fill_color = PAGE_BG
p.border_fill_color = PAGE_BG
p.outline_line_color = None
# Save — interactive HTML, then PNG via Selenium headless Chrome
output_file(f"plot-{THEME}.html")
save(p, resources=CDN)
W, H = 2400, 2400
opts = Options()
for arg in (
"--headless=new",
"--no-sandbox",
"--disable-dev-shm-usage",
"--disable-gpu",
f"--window-size={W},{H}",
"--hide-scrollbars",
):
opts.add_argument(arg)
driver = webdriver.Chrome(options=opts)
# CDP override forces exact W×H viewport regardless of browser chrome
driver.execute_cdp_cmd(
"Emulation.setDeviceMetricsOverride", {"width": W, "height": H, "deviceScaleFactor": 1, "mobile": False}
)
driver.get(f"file://{Path(f'plot-{THEME}.html').resolve()}")
time.sleep(3)
driver.save_screenshot(f"plot-{THEME}.png")
driver.quit()
Part of Basketball Shot Chart on anyplot.ai.