def show_example():
batter_list = [
'Mookie Betts', 'Cody Bellinger', 'Corey Seager', 'Manny Machado'
]
pitcher_list = ['Chris Paddack', 'Clayton Kershaw']
candidate_batters = [
sing.get_players(name=player_name)[0] for player_name in batter_list
]
candidate_pitchers = [
sing.get_players(name=player_name)[0] for player_name in pitcher_list
]
venue = sing.get_venues(stadium_name="Dodger Stadium")[0]
game_state = State(on_1b=False,
on_2b=True,
on_3b=False,
inning=4,
outs=0,
top=True,
bat_score=3,
fld_score=5,
pitch_number=50)
atmosph = Atmosphere(venue,
temperature=70,
home_team=sing.get_teams(name="Dodgers")[0])
matchups = ([
Matchup(batter=m, pitcher=p, state=game_state, atmosphere=atmosph)
for m in candidate_batters for p in candidate_pitchers
])
results = pd.DataFrame(sing.get_pa_sim(matchups))
print(f'\nResults')
print(results.sort_values(by=["woba_exp"], ascending=False))
def show_example():
batter = sing.get_players(name="Aaron Judge")[0]
pitching_team = "Rays"
candidate_pitchers = sing.get_players(team_name=pitching_team,
position=["P"],
active=True,
on_40=True)
atmosph = Atmosphere(sing.get_venues(stadium_name="Yankee Stadium")[0],
temperature=70,
home_team=sing.get_teams(name="Yankees")[0])
state = State(inning=9,
top=False,
bat_score=3,
fld_score=3,
on_1b=True,
on_2b=True,
on_3b=True,
outs=2)
matchups = [
Matchup(batter=batter, pitcher=p, atmosphere=atmosph, state=state)
for p in candidate_pitchers
]
results = pd.DataFrame(sing.get_pa_sim(matchups))
print(f'\nBest pitcher to face Aaron Judge with the game on the line')
pprint(results.sort_values(by=["obp_exp"]))
def get_predictions(args):
batter_list = [
sing.get_players(name=b.strip())[0] for b in args.batters.split(',')
]
pitcher_list = [
sing.get_players(name=p.strip())[0] for p in args.pitchers.split(',')
]
state = State(inning=args.inning,
on_1b=args.on1b,
on_2b=args.on2b,
on_3b=args.on3b,
outs=args.outs,
top=not (args.bottom),
bat_score=args.batscore,
fld_score=args.fieldscore,
pitch_number=args.pitchnumber)
venue = sing.get_venues(stadium_name=args.venue)[0]
atmosphere = Atmosphere(venue=venue,
home_team=sing.get_teams(name=args.hometeam)[0],
temperature=args.temperature)
matchups = [
Matchup(batter=m,
pitcher=p,
atmosphere=atmosphere,
state=state,
date=args.date) for m in batter_list for p in pitcher_list
]
results = pd.DataFrame(
sing.get_pa_sim(matchups,
return_features=args.showinputs,
model_name=args.predictiontype))
return results
def show_example():
batter_list = ['Mookie Betts']
pitcher_list = ['Chris Paddack']
candidate_batters = [
sing.get_players(name=player_name)[0] for player_name in batter_list
]
candidate_pitchers = [
sing.get_players(name=player_name)[0] for player_name in pitcher_list
]
venue = sing.get_venues(stadium_name="Dodger Stadium")[0]
atmosph = Atmosphere(venue,
temperature=70,
home_team=sing.get_teams(name="Dodgers")[0])
state = State(on_1b=False,
on_2b=True,
on_3b=False,
pitch_number=79,
inning=4,
top=False,
bat_score=3,
fld_score=5)
matchups = ([
Matchup(batter=m, pitcher=p, atmosphere=atmosph, state=state)
for m in candidate_batters for p in candidate_pitchers
])
results = pd.DataFrame(sing.get_pa_sim(matchups, return_features=True))
print(f'\nResults')
print(results.sort_values(by=["woba_exp"], ascending=False))
def show_example():
candidate_batters = (sing.get_players(position=["1B", "DH"],
bat_side=["R"],
age_min=32,
active=True))
candidate_pitchers = [
sing.get_players(name=p)[0]
for p in ['J.A. Happ', 'James Paxton', 'Jordan Montgomery']
]
venue = sing.get_venues(stadium_name="Yankee Stadium")[0]
atmosph = Atmosphere(venue,
temperature=70,
home_team=sing.get_teams(name="Yankee")[0])
matchups = ([
Matchup(batter=m, pitcher=p, atmosphere=atmosph, state=State())
for m in candidate_batters for p in candidate_pitchers
])
results = pd.DataFrame(sing.get_pa_sim(matchups))
print(results.sort_values(by=["woba_exp"], ascending=False))
##########################################
# Simple batter vs. pitcher plate appearance prediction using defaults
##########################################
from common import sing
from pprint import pprint
from singlearity import State, Player, Team, Venue, Atmosphere, Matchup, ApiException
from singlearity.rest import ApiException
import pandas as pd
batter_list = ['Mookie Betts', 'Cody Bellinger', 'Gavin Lux']
pitcher_list = ['Chris Paddack']
candidate_batters = [sing.get_players(name = player_name)[0] for player_name in batter_list]
candidate_pitchers = [sing.get_players(name = player_name)[0] for player_name in pitcher_list]
venue = sing.get_venues(stadium_name = "Dodger Stadium")[0]
atmosph = Atmosphere(venue, temperature = 70, home_team = sing.get_teams(name = "Dodgers")[0])
matchups = ([Matchup(batter = m, pitcher = p,
atmosphere = atmosph, state=State()) for m in candidate_batters for p in candidate_pitchers])
results = pd.DataFrame(sing.get_pa_sim(matchups))
#just get some interesting stats. comment below line out to see all predictions
results = results[['batter_name', 'pitcher_name', 'hr_exp', 'so_exp', 'ba_exp', 'ops_exp', 'woba_exp']]
print(f'Results:\n{results}')