def main(team1, team2, num_days, num_samples, week, half_life):
league = get_league()
decay_rate = np.log(2) / half_life
print(
tabulate([["Team", "Manager"]] + [[t.name, t.manager_name]
for t in league.teams]))
if team1 is None:
team1 = league.current_team
else:
team1 = league.team_by_owner(team1)
if team2 is None:
team2 = league.get_matchup(team1, week=week)
else:
team2 = league.team_by_owner(team2)
pyfiglet.print_figlet("%s vs. %s" %
(team1.manager_name, team2.manager_name),
font='banner',
width=160)
if week:
pyfiglet.print_figlet("Week %u" % week, font='big')
print("Roster:")
print_roster(team1.roster(week=week))
print("Roster:")
print_roster(team2.roster(week=week))
projections = visualize_matchup([team1],
team2,
num_days=num_days,
num_samples=num_samples,
week=week,
decay_rate=decay_rate)
#print(projections[0][0].round(2).to_csv())
print("Projections")
print("=====================")
with pd.option_context('display.max_rows', None, 'display.max_columns',
None):
print(projections[0][0].round(2))
import numpy as np
import pandas as pd
import pyfiglet
import click
from tabulate import tabulate
import logging
logging.basicConfig()
logging.getLogger().setLevel(logging.INFO)
from nba_matchup import get_league, visualize_matchup, CURRENT_WEEK, print_roster
league = get_league()
@click.command()
@click.option('--team1', type=str, default=None)
@click.option('--team2', type=str, default=None)
@click.option('--num_days', type=int, default=30)
@click.option('--num_samples', type=int, default=50000)
@click.option('--week', type=int, default=CURRENT_WEEK)
@click.option('--half_life', type=float, default=14)
def main(team1, team2, num_days, num_samples, week, half_life):
league = get_league()
decay_rate = np.log(2) / half_life
print(
tabulate([["Team", "Manager"]] + [[t.name, t.manager_name]
for t in league.teams]))
if team1 is None:
team1 = league.current_team
else:
team1 = league.team_by_owner(team1)
if team2 is None:
team2 = league.get_matchup(team1, week=week)
def main(team1, team2, num_days, num_samples, week, num_fa, num_minimax,
num_iters, ignore_player, half_life, metric, ignore_injured):
league = get_league()
decay_rate = np.log(2) / half_life
if team1 is None:
team1 = league.current_team
else:
team1 = league.team_by_owner(team1)
if team2 is None:
team2 = league.get_matchup(team1, week=week)
else:
team2 = league.team_by_owner(team2)
pyfiglet.print_figlet("%s vs. %s" %
(team1.manager_name, team2.manager_name),
font='banner',
width=160)
pyfiglet.print_figlet("Week %u" % week, font='big')
if metric == 'ev':
metric_fn = ev
else:
metric_fn = winning_prob
old_team1_roster = team1.roster(week=week)
old_team2_roster = team2.roster(week=week)
def team1_score(roster):
cats, points, scores, _ = simulate_h2h(roster,
team2.roster(week=week),
num_days=num_days,
num_samples=num_samples,
week=week,
decay_rate=decay_rate)
return metric_fn(cats, points, scores, num_samples)
def team2_score(roster):
cats, points, scores, _ = simulate_h2h(roster,
team1.roster(week=week),
num_days=num_days,
num_samples=num_samples,
week=week,
decay_rate=decay_rate)
return metric_fn(cats, points, scores, num_samples)
print("%s's roster:" % team1.manager_name, team1_score(old_team1_roster))
print_roster(old_team1_roster)
print("%s's roster:" % team2.manager_name, team2_score(old_team2_roster))
print_roster(old_team2_roster)
print("Adding free agents:")
for agent in get_free_agents(num_fa):
print(agent.name)
old_team1_roster = old_team1_roster.add(agent, "BN")
# old_team2_roster = old_team2_roster.add(agent, "BN")
team1.set_roster(old_team1_roster)
team2.set_roster(old_team2_roster)
print("Ignoring players:", ", ".join(ignore_player))
for i in range(num_minimax):
for team, score_fn in zip([team2, team1], [team2_score, team1_score]):
roster = team.roster(week=week)
print("===========================================")
print("Minimax[%u]: %s" % (i + 1, team.manager_name))
for roster, score in simulated_annealing(
roster,
score_fn,
ignore_players={
roster.player_by_name(n)
for n in ignore_player
},
num_steps=num_iters,
ignore_injured=ignore_injured):
pass
print("%s's optimized roster:" % team.manager_name, score)
print(
tabulate([[position, player.name]
for player, position in roster.positions.items()
if position not in {"BN", "IL"}]))
team.set_roster(roster)
projections = visualize_matchup([team1],
team2,
num_days=num_days,
num_samples=100000,
week=week,
decay_rate=decay_rate,
show_plots=False)
with pd.option_context('display.max_rows', None, 'display.max_columns',
None, 'display.expand_frame_repr', False):
for i, team in enumerate([team1, team2]):
print("===========================================")
print("%s's projections:" % team.manager_name)
print(projections[0][i].round(2))
def main(team1, team2, num_days, num_samples, week, half_life, player1,
player2, eval_team):
player1_name, player2_name = team1, team2
decay_rate = np.log(2) / half_life
league = get_league()
print(
tabulate([["Team", "Manager"]] + [[t.name, t.manager_name]
for t in league.teams]))
if team1 is None:
team1 = league.current_team
else:
team1 = league.team_by_owner(team1)
if team2 is None:
team2 = league.get_matchup(team1, week=week)
else:
team2 = league.team_by_owner(team2)
base = START_DATE + datetime.timedelta(days=7 * (week - 1) + 7)
week_length = 7
team1_roster = team1.roster(week=week)
team2_roster = team2.roster(week=week)
old_team1_stats, _ = team1_roster.stats(num_days,
base_date=base,
week_length=week_length)
old_team1_average = old_team1_stats.mean(axis=0)
old_team1_average[
'FG%'] = old_team1_average["FGM"] / old_team1_average["FGA"]
old_team1_average[
'FT%'] = old_team1_average["FTM"] / old_team1_average["FTA"]
old_team2_stats, _ = team2_roster.stats(num_days,
base_date=base,
week_length=week_length)
old_team2_average = old_team2_stats.mean(axis=0)
old_team2_average[
'FG%'] = old_team2_average["FGM"] / old_team2_average["FGA"]
old_team2_average[
'FT%'] = old_team2_average["FTM"] / old_team2_average["FTA"]
print(f"{team1.manager_name}'s roster:")
print_roster(team1_roster)
print(f"{team2.manager_name}'s roster:")
print_roster(team2_roster)
new_team1_roster = team1_roster.copy()
new_team2_roster = team2_roster.copy()
player1 = set(player1)
player2 = set(player2)
for p in player1:
player = new_team1_roster.player_by_name(p)
new_team1_roster = new_team1_roster.remove(player)
new_team2_roster = new_team2_roster.add(player, 'BN')
for p in player2:
player = new_team2_roster.player_by_name(p)
new_team2_roster = new_team2_roster.remove(player)
new_team1_roster = new_team1_roster.add(player, 'BN')
team1.set_roster(new_team1_roster)
print_roster(new_team1_roster, include_bench=True, include_injured=True)
print_roster(new_team2_roster, include_bench=True, include_injured=True)
other_players = [
team.roster(week=week) for team in league.teams
if team.manager_name not in {player1_name, player2_name}
]
teams_to_eval = [league.team_by_owner(name) for name in eval_team]
print("Evaluating %s" % team1.manager_name)
old_team1_scores = score_team(team1_roster, teams_to_eval, num_days,
num_samples, week, decay_rate)
team1_scores = score_team(new_team1_roster, teams_to_eval, num_days,
num_samples, week, decay_rate)
improvements = [
team1_scores[k] - old_team1_scores[k] for k in old_team1_scores
]
print(
tabulate([[
k.manager_name, old_team1_scores[k], team1_scores[k],
team1_scores[k] - old_team1_scores[k]
] for k in old_team1_scores]))
print("Average improvement:", np.mean(improvements))
print("Evaluating %s" % team2.manager_name)
old_team2_scores = score_team(team2_roster, teams_to_eval, num_days,
num_samples, week, decay_rate)
team2_scores = score_team(new_team2_roster, teams_to_eval, num_days,
num_samples, week, decay_rate)
improvements = [
team2_scores[k] - old_team2_scores[k] for k in old_team2_scores
]
print(
tabulate([[
k.manager_name, old_team2_scores[k], team2_scores[k],
team2_scores[k] - old_team2_scores[k]
] for k in old_team2_scores]))
print("Average improvement:", np.mean(improvements))
def main(team1, team2, num_days, num_samples, week, num_fa, num_iters,
ignore_player, half_life, metric, ignore_injured):
league = get_league()
decay_rate = np.log(2) / half_life
# if week == 19: week = 18
# if week >= 19:
# week -= 1
if team1 is None:
team1 = league.current_team
else:
team1 = league.team_by_owner(team1)
if team2 is None:
team2 = league.get_matchup(team1, week=week)
else:
team2 = league.team_by_owner(team2)
pyfiglet.print_figlet("%s vs. %s" %
(team1.manager_name, team2.manager_name),
font='banner',
width=160)
if week:
pyfiglet.print_figlet("Week %u" % week, font='big')
if metric == 'ev':
metric_fn = ev
else:
metric_fn = winning_prob
def roster_score(roster):
cats, points, scores, _ = simulate_h2h(roster,
team2.roster(week=week),
num_days=num_days,
num_samples=num_samples,
week=week,
decay_rate=decay_rate)
return metric_fn(cats, points, scores, num_samples)
def reverse_roster_score(roster):
cats, points, scores, _ = simulate_h2h(roster,
team1.roster(week=week),
num_days=num_days,
num_samples=num_samples,
week=week,
decay_rate=decay_rate)
return metric_fn(cats, points, scores, num_samples)
print("%s's roster:" % team1.manager_name,
roster_score(team1.roster(week=week)))
print(
tabulate(
[[position, player.name]
for player, position in team1.roster(week=week).positions.items()
if position not in {"BN", "IL"}]))
print("%s's roster:" % team2.manager_name,
reverse_roster_score(team2.roster(week=week)))
print(
tabulate(
[[position, player.name]
for player, position in team2.roster(week=week).positions.items()
if position not in {"BN", "IL"}]))
print("Optimizing %s's lineup" % team1.manager_name)
print("===========================================")
roster = team1.roster(week=week)
old_roster = roster
print("Adding free agents:")
for agent in get_free_agents(num_fa):
print(agent.name)
roster = roster.add(agent, "BN")
team1.set_roster(roster)
print("Ignoring players:", ", ".join(ignore_player))
scores = []
for roster, score in simulated_annealing(
roster,
roster_score,
ignore_players={
team1.roster(week=week).player_by_name(n)
for n in ignore_player
},
num_steps=num_iters,
ignore_injured=ignore_injured):
scores.append(score)
# print(tabulate([
# [position, player.name] for player, position in
# roster.positions.items() if position not in {"BN", "IL"}
# ]))
print("%s's optimized roster:" % team1.manager_name, score)
print(
tabulate([[position, player.name]
for player, position in roster.positions.items()
if position not in {"BN", "IL"}]))
def team_generator():
for r in [old_roster, roster]:
team1.set_roster(r)
yield team1
projections = visualize_matchup(team_generator(),
team2,
num_days=num_days,
num_samples=100000,
week=week,
decay_rate=decay_rate,
show_plots=False)
with pd.option_context('display.max_rows', None, 'display.max_columns',
None, 'display.expand_frame_repr', False):
for i, team in enumerate([team1, team2]):
print("===========================================")
print("%s's projections:" % team.manager_name)
print(projections[1][i].round(2))
plt.figure()
plt.plot(scores)
plt.show()