Value distribution: box plot

Exact quartiles, median, and outlier points per set-piece type – plot_value_distribution()’s violins show the smoothed shape of this same data, and plot_value_ridgeline()’s KDE curves show it again a third way. Reach for the box plot when the specific numbers (median, IQR, which points are outliers) matter more than the overall shape – a corner delivery costing -0.019 xT stands out here as a labeled outlier point, not just a wide tail on a curve.

from pathlib import Path

from wa_setpieces import load_matches
from wa_setpieces.core.xt import XTModel
from wa_setpieces.viz.plots import plot_value_boxplot

try:
    _here = Path(__file__).resolve().parent
except NameError:
    _here = Path.cwd()
DATA = _here.parent / "tests" / "data" / "sample_match.json"

events = load_matches(DATA)
model = XTModel.fit(events, x_bins=8, y_bins=6)

fig, ax = plot_value_boxplot(events, model, title="Added value by set-piece type")