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from dataclasses import dataclass
import pandas as pd
from domain.playoffs import PLAYOFF_TEAM_DEF_PLAYER
from queries.nflverse.github_data import get_player_kicking_stats, get_player_stats, get_team_defense_stats
@dataclass
class StatType:
key: str
score: float
RUSH_TD = StatType(key="RUSH TD", score=6.0)
REC_TD = StatType(key="REC TD", score=6.0)
OFF_FUM_TD = StatType(key="OFF FUM TD", score=6.0)
PASS_TD = StatType(key="PASS TD", score=4.0)
FG_0_49 = StatType(key="FG 0-49", score=3.0)
FG_50_ = StatType(key="FG 50+", score=5.0)
TWO_PT = StatType(key="2 PT", score=2.0)
RECEPTION = StatType(key="REC", score=1.0)
RUSH_YD = StatType(key="RUSH YD", score=0.1)
REC_YD = StatType(key="REC YD", score=0.1)
PASS_YD = StatType(key="PASS YD", score=0.04)
XP = StatType(key="XP", score=1.0)
FUM_LOST = StatType(key="FUM LOST", score=-2.0)
PASS_INT = StatType(key="PASS INT", score=-2.0)
RET_TD = StatType(key="RET TD", score=6.0)
DEF_TD = StatType(key="DEF TD", score=6.0)
DEF_INT = StatType(key="DEF INT", score=2.0)
FUM_REC = StatType(key="FUM REC", score=2.0)
SAFETY = StatType(key="SAFETY", score=2.0)
SACK = StatType(key="SACK", score=1.0)
PTS_ALLOW_0 = StatType(key="PTS ALLOW 0", score=10.0)
PTS_ALLOW_1_6 = StatType(key="PTS ALLOW 1-6", score=7.0)
PTS_ALLOW_7_13 = StatType(key="PTS ALLOW 7-13", score=4.0)
PTS_ALLOW_14_20 = StatType(key="PTS ALLOW 14-20", score=1.0)
PTS_ALLOW_21_27 = StatType(key="PTS ALLOW 21-27", score=0.0)
PTS_ALLOW_28_34 = StatType(key="PTS ALLOW 28-34", score=-1.0)
PTS_ALLOW_35_ = StatType(key="PTS ALLOW 35+", score=-4.0)
TEAM_WIN = StatType(key="TEAM WIN", score=5.0)
ST_TD = StatType(key="ST TD", score=6.0)
NFLVERSE_STAT_COL_TO_ID: dict[str, str] = {
"passing_tds": PASS_TD.key,
"pasing_yards": PASS_YD.key,
"passing_2pt_conversions": TWO_PT.key,
"sack_fumbles_lost": FUM_LOST.key,
"interceptions": PASS_INT.key,
"rushing_tds": RUSH_TD.key,
"rushing_yards": RUSH_YD.key,
"rushing_2pt_conversions": TWO_PT.key,
"rushing_fumbles_lost": FUM_LOST.key,
"receptions": RECEPTION.key,
"receiving_tds": REC_TD.key,
"receiving_yards": REC_YD.key,
"receiving_2pt_conversions": TWO_PT.key,
"receiving_fumbles_lost": FUM_LOST.key,
"special_teams_tds": ST_TD.key,
"pat_made": XP.key,
"fg_made_0_19": FG_0_49.key,
"fg_made_20_29": FG_0_49.key,
"fg_made_30_39": FG_0_49.key,
"fg_made_40_49": FG_0_49.key,
"fg_made_50_59": FG_50_.key,
"fg_made_60_": FG_50_.key,
"def_sacks": SACK.key,
"def_interceptions": DEF_INT.key,
"def_tds": DEF_TD.key,
"def_fumble_recovery_opp": FUM_REC.key,
"def_safety": SAFETY.key,
}
NFLVERSE_STAT_WEEK_TO_PLAYOFF_WEEK = {
19: 1,
20: 2,
21: 3,
22: 4,
}
def add_stats_from_player_df_to_stat_map(df: pd.DataFrame, stat_map):
df_playoffs = df[df.week.isin(NFLVERSE_STAT_WEEK_TO_PLAYOFF_WEEK.keys())]
df_playoffs.week = df_playoffs.week.apply(lambda x: NFLVERSE_STAT_WEEK_TO_PLAYOFF_WEEK[x])
for week_player_id_tuple, row in df_playoffs.set_index(["week", "player_id"]).iterrows():
if isinstance(week_player_id_tuple, tuple):
week, player_id = week_player_id_tuple
else:
# this won't happen but makes mypy happy
continue
player_stats: dict[str, float] = {}
for k, v in row.to_dict().items():
if k in NFLVERSE_STAT_COL_TO_ID:
if (mapped_k := NFLVERSE_STAT_COL_TO_ID[k]) in player_stats:
player_stats[mapped_k] += v
else:
player_stats[mapped_k] = v
if player_id not in stat_map[week]:
stat_map[week][player_id] = player_stats
else:
stat_map[week][player_id].update(player_stats)
def add_stats_from_team_def_df_to_stat_map(df: pd.DataFrame, stat_map):
short_team_names_to_player_id = {t.rosters_short_name: p for t, p in PLAYOFF_TEAM_DEF_PLAYER}
df_playoffs = df[
(df.week.isin(NFLVERSE_STAT_WEEK_TO_PLAYOFF_WEEK.keys()) & df.team.isin(short_team_names_to_player_id.keys()))
]
df_playoffs.week = df_playoffs.week.apply(lambda x: NFLVERSE_STAT_WEEK_TO_PLAYOFF_WEEK[x])
for week_team_tuple, row in df_playoffs.set_index(["week", "team"]).iterrows():
if isinstance(week_team_tuple, tuple):
week, team = week_team_tuple
else:
# this won't happen but makes mypy happy
continue
player_stats: dict[str, float] = {}
player_id = short_team_names_to_player_id[team]
for k, v in row.to_dict().items():
if k in NFLVERSE_STAT_COL_TO_ID:
if (mapped_k := NFLVERSE_STAT_COL_TO_ID[k]) in player_stats:
player_stats[mapped_k] += v
else:
player_stats[mapped_k] = v
if player_id not in stat_map[week]:
stat_map[week][player_id] = player_stats
else:
stat_map[week][player_id].update(player_stats)
def assemble_nflverse_stats() -> dict[int, dict[str, dict[str, float]]]:
# map week -> player_id -> stat_key -> stat value
stat_map: dict[int, dict[str, dict[str, float]]] = {w: {} for w in NFLVERSE_STAT_WEEK_TO_PLAYOFF_WEEK.values()}
df_player_stats = get_player_stats()
df_kicking_stats = get_player_kicking_stats()
df_def_stats = get_team_defense_stats()
add_stats_from_player_df_to_stat_map(df_player_stats, stat_map)
add_stats_from_player_df_to_stat_map(df_kicking_stats, stat_map)
add_stats_from_team_def_df_to_stat_map(df_def_stats, stat_map)
return stat_map
if __name__ == "__main__":
from queries.nflverse.github_data import load_assets
load_assets()
assemble_nflverse_stats()
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