"""
EuroLeague basketball
=====================

This example shows EuroLeagueStats, the free statistics from the EuroLeague's own API.
"""

# Author: Georgios Douzas <gdouzas@icloud.com>
# Licence: MIT

import matplotlib.pyplot as plt

from sportsbet.dataloaders import DataLoader
from sportsbet.sources import EuroLeagueStats

# %%
# A different sport, the same dataloader
# --------------------------------------
#
# The sport is a property of the source, not of the dataloader. There is one dataloader. It handles basketball here
# because this source is basketball.

stats = EuroLeagueStats()
stats.name, stats.kind, stats.sport

# %%
# These are the seasons it publishes. A whole season arrives in a single request. It needs no key.

params = stats.list_available_params()
sorted({param['year'] for param in params})[-5:]

# %%
# Extracting the features
# -----------------------
#
# There is no free basketball odds feed, so you have to buy the odds. See [`OddsApi`](plot_odds_api.md). Without odds
# there are no markets and nothing to predict, so `extract_train_data` stops and says so. The features are still
# useful, so `extract_exploration_data` returns them on their own.

dataloader = DataLoader(param_grid={'league': ['Euroleague'], 'year': [2024]}, stats=stats)
X = dataloader.extract_exploration_data()

# %%
# The features, with no targets and no odds:
X

# %%
# The data settles two things for you, without configuration. There is no draw, because a tie goes to overtime, so the
# outcome is two-way. There is no totals market, because a bookmaker sets a different line for every game, and a market
# whose line moves is not a column.

# %%
# A picture of it
# ---------------
#
# This shows the form of the two sides, side by side. The home teams sit a little to the right of the away teams. That
# gap is the home advantage, and it comes from the data rather than from any setting.

fig, ax = plt.subplots()
ax.hist(X['home_points_for_avg'].dropna(), bins=25, alpha=0.6, label='home team')
ax.hist(X['away_points_for_avg'].dropna(), bins=25, alpha=0.6, label='away team')
ax.set_title('EuroLeague: scoring form the two sides bring, before tip-off')
ax.set_xlabel('points per game')
ax.set_ylabel('games')
ax.legend()