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: matplotlib 3.11.0 | Python 3.13.14
Quality: 92/100 | Updated: 2026-06-21
"""
import os
import sys
# Prevent this script's filename from shadowing the installed matplotlib package
sys.path = [p for p in sys.path if os.path.abspath(p) != os.path.dirname(os.path.abspath(__file__))]
import matplotlib.patches as patches
import matplotlib.patheffects as pe
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.colors import LinearSegmentedColormap
from matplotlib.path import Path
# Theme tokens — Imprint palette, theme-adaptive chrome
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 mapping: made=green (good), missed=red (bad), FT=blue
C_MADE = "#009E73" # brand green — made shots (position 1)
C_MISSED = "#AE3030" # matte red — missed shots (semantic: bad/error, position 5)
C_FT = "#4467A3" # blue — free-throw distinct shot type (position 3)
# Data
np.random.seed(42)
n_ft = 25
n_field = 325
n_shots = n_field + n_ft
# Field goal shot locations in feet relative to basket center at (0, 0)
x_field = np.concatenate(
[
np.random.normal(0, 3, 55), # paint area shots
np.random.normal(0, 1.5, 25), # close to basket
np.random.uniform(-8, 8, 50), # mid-range middle
np.random.normal(-15, 3, 35), # left wing mid-range
np.random.normal(15, 3, 35), # right wing mid-range
np.random.normal(-22, 1.5, 25), # left corner three
np.random.normal(22, 1.5, 25), # right corner three
np.random.normal(0, 8, 40), # top of arc three
np.random.normal(-12, 4, 18), # left wing three
np.random.normal(12, 4, 17), # right wing three
]
)
y_field = np.concatenate(
[
np.random.uniform(0, 12, 55), # paint
np.random.uniform(0, 4, 25), # close
np.random.uniform(10, 18, 50), # mid-range
np.random.uniform(5, 15, 35), # left wing mid
np.random.uniform(5, 15, 35), # right wing mid
np.random.uniform(0, 8, 25), # left corner
np.random.uniform(0, 8, 25), # right corner
np.random.uniform(22, 30, 40), # top of arc
np.random.uniform(15, 25, 18), # left wing three
np.random.uniform(15, 25, 17), # right wing three
]
)
# Free-throw shots clustered at the free-throw line (15 ft from backboard)
x_ft = np.random.normal(0, 0.8, n_ft)
y_ft = np.random.normal(14.0, 0.6, n_ft)
x = np.clip(np.concatenate([x_field, x_ft]), -24.5, 24.5)
y = np.clip(np.concatenate([y_field, y_ft]), 0, 40)
# Shot outcome — closer shots have higher make rate; free throws ~75%
distance = np.sqrt(x**2 + y**2)
make_prob = np.clip(0.65 - distance * 0.012, 0.25, 0.70)
make_prob[-n_ft:] = 0.75
made = np.random.random(n_shots) < make_prob
# Shot type based on distance from basket
three_pt_dist = np.where(np.abs(x) >= 22, 22.0, 23.75)
shot_type = np.array(
["3-pointer" if d >= t else "2-pointer" for d, t in zip(distance, three_pt_dist, strict=False)], dtype=object
)
shot_type[-n_ft:] = "free-throw"
# Plot — square canvas (1:1 aspect for undistorted court)
fig, ax = plt.subplots(figsize=(6, 6), dpi=400, facecolor=PAGE_BG)
ax.set_facecolor(PAGE_BG)
lw = 2.0
# Court geometry — theme-adaptive line color
court_patches = [
patches.Rectangle((-25, -5.25), 50, 47, linewidth=lw, edgecolor=INK_SOFT, facecolor="none"),
patches.Circle((0, 0), 0.75, linewidth=lw, edgecolor="#BD8233", facecolor="none"),
patches.Rectangle((-8, -5.25), 16, 19.25, linewidth=lw, edgecolor=INK_SOFT, facecolor="none"),
patches.Arc((0, 14.0), 12, 12, angle=0, theta1=0, theta2=180, linewidth=lw, edgecolor=INK_SOFT),
patches.Arc((0, 14.0), 12, 12, angle=0, theta1=180, theta2=360, linewidth=lw, edgecolor=INK_SOFT, linestyle="--"),
patches.Arc((0, 0), 8, 8, angle=0, theta1=0, theta2=180, linewidth=lw, edgecolor=INK_SOFT),
patches.Arc((0, 41.75), 12, 12, angle=0, theta1=180, theta2=360, linewidth=lw, edgecolor=INK_SOFT),
]
for p in court_patches:
ax.add_patch(p)
# Backboard
ax.plot([-3, 3], [-1.0, -1.0], color=INK_SOFT, linewidth=3)
# Three-point line corners and arc
ax.plot([-22, -22], [-5.25, 8.75], color=INK_SOFT, linewidth=lw)
ax.plot([22, 22], [-5.25, 8.75], color=INK_SOFT, linewidth=lw)
three_arc_angle = np.degrees(np.arccos(22.0 / 23.75))
ax.add_patch(
patches.Arc(
(0, 0),
47.5,
47.5,
angle=90,
theta1=-90 + three_arc_angle,
theta2=90 - three_arc_angle,
linewidth=lw,
edgecolor=INK_SOFT,
)
)
# Half-court line
ax.plot([-25, 25], [41.75, 41.75], color=INK_SOFT, linewidth=lw)
# Imprint diverging colormap for efficiency underlay (centered near 50% FG)
midpoint = "#FAF8F1" if THEME == "light" else "#1A1A17"
imprint_div = LinearSegmentedColormap.from_list("imprint_div", [C_MISSED, midpoint, "#4467A3"])
ax.hexbin(
x,
y,
C=made.astype(float),
gridsize=15,
cmap=imprint_div,
reduce_C_function=np.mean,
alpha=0.14,
extent=[-25, 25, -5, 42],
mincnt=2,
zorder=2,
linewidths=0,
)
# Custom diamond marker for made field goals
diamond_verts = [(-0.5, 0), (0, 0.7), (0.5, 0), (0, -0.7), (-0.5, 0)]
diamond_codes = [Path.MOVETO, Path.LINETO, Path.LINETO, Path.LINETO, Path.CLOSEPOLY]
diamond_marker = Path(diamond_verts, diamond_codes)
# Shot masks
field_made = made & (shot_type != "free-throw")
field_missed = ~made & (shot_type != "free-throw")
ft_made = made & (shot_type == "free-throw")
ft_missed = ~made & (shot_type == "free-throw")
# Missed field goals — red X
ax.scatter(
x[field_missed],
y[field_missed],
s=55,
marker="x",
c=C_MISSED,
alpha=0.55,
linewidths=1.8,
zorder=4,
label="Missed FG",
)
# Made field goals — green diamond
ax.scatter(
x[field_made],
y[field_made],
s=60,
marker=diamond_marker,
c=C_MADE,
alpha=0.65,
edgecolors=PAGE_BG,
linewidth=0.5,
zorder=5,
label="Made FG",
)
# Made free throws — blue filled circle
ax.scatter(
x[ft_made],
y[ft_made],
s=60,
marker="o",
c=C_FT,
alpha=0.75,
edgecolors=PAGE_BG,
linewidth=0.5,
zorder=5,
label="Made FT",
)
# Missed free throws — blue open circle, clearly distinct from missed field goals
ax.scatter(
x[ft_missed],
y[ft_missed],
s=60,
marker="o",
c="none",
edgecolors=C_FT,
linewidths=1.8,
alpha=0.75,
zorder=4,
label="Missed FT",
)
# Style
ax.set_xlim(-27, 27)
ax.set_ylim(-7, 44)
ax.set_aspect("equal")
ax.axis("off")
title = "scatter-shot-chart · python · matplotlib · anyplot.ai"
ax.set_title(
title,
fontsize=12,
fontweight="medium",
color=INK,
pad=12,
path_effects=[pe.withStroke(linewidth=3, foreground=PAGE_BG)],
)
# Legend — 4 entries to distinguish all shot outcome × type combinations
legend = ax.legend(
loc="lower center",
ncol=4,
fontsize=8,
framealpha=0.85,
facecolor=ELEVATED_BG,
edgecolor=INK_SOFT,
bbox_to_anchor=(0.5, -0.03),
markerscale=1.6,
handletextpad=0.6,
)
plt.setp(legend.get_texts(), color=INK_SOFT)
# Shooting summary
total = n_shots
makes = int(made.sum())
fg_pct = makes / total * 100
twos = shot_type == "2-pointer"
threes = shot_type == "3-pointer"
fts = shot_type == "free-throw"
fg2 = made[twos].sum() / twos.sum() * 100 if twos.sum() > 0 else 0
fg3 = made[threes].sum() / threes.sum() * 100 if threes.sum() > 0 else 0
ft_pct = made[fts].sum() / fts.sum() * 100 if fts.sum() > 0 else 0
summary = f"FG: {makes}/{total} ({fg_pct:.1f}%) | 2PT: {fg2:.0f}% | 3PT: {fg3:.0f}% | FT: {ft_pct:.0f}%"
ax.text(
0,
43.0,
summary,
fontsize=8,
color=INK_MUTED,
ha="center",
va="top",
path_effects=[pe.withStroke(linewidth=2, foreground=PAGE_BG)],
)
fig.subplots_adjust(left=0.02, right=0.98, top=0.94, bottom=0.09)
# Save — no bbox_inches='tight' to preserve exact 2400×2400 canvas
plt.savefig(f"plot-{THEME}.png", dpi=400, facecolor=PAGE_BG)
Part of Basketball Shot Chart on anyplot.ai.