Value distribution: ridgeline

A joyplot of per-delivery added value: one smooth density curve per set-piece type instead of plot_value_distribution()’s violins. A KDE curve makes a multi-modal shape (two distinct clusters of outcomes, not just one messy spread) easier to spot than a violin’s mirrored outline does – at the cost of needing more data to trust: each type needs at least 3 deliveries with non-identical values, or it’s silently left out.

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_ridgeline

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_ridgeline(events, model, title="Added value distribution shape")