2.1 : New
This commit is contained in:
@@ -2,6 +2,7 @@ from web.database import query_db, get_db, execute_db
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import sqlite3
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import pandas as pd
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import numpy as np
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from web.services.weapon_service import get_weapon_info
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class FeatureService:
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@staticmethod
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@@ -357,6 +358,46 @@ class FeatureService:
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valid_ids = tuple(df['steam_id_64'].tolist())
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placeholders = ','.join(['?'] * len(valid_ids))
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try:
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query_weapon_kills = f"""
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SELECT attacker_steam_id as steam_id_64,
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SUM(CASE WHEN lower(weapon) LIKE '%knife%' OR lower(weapon) LIKE '%bayonet%' THEN 1 ELSE 0 END) as knife_kills,
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SUM(CASE WHEN lower(weapon) LIKE '%taser%' OR lower(weapon) LIKE '%zeus%' THEN 1 ELSE 0 END) as zeus_kills
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FROM fact_round_events
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WHERE event_type = 'kill'
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AND attacker_steam_id IN ({placeholders})
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GROUP BY attacker_steam_id
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"""
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df_weapon_kills = pd.read_sql_query(query_weapon_kills, conn, params=valid_ids)
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if not df_weapon_kills.empty:
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df = df.merge(df_weapon_kills, on='steam_id_64', how='left')
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else:
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df['knife_kills'] = 0
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df['zeus_kills'] = 0
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except Exception:
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df['knife_kills'] = 0
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df['zeus_kills'] = 0
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df['basic_avg_knife_kill'] = df['knife_kills'].fillna(0) / df['matches_played'].replace(0, 1)
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df['basic_avg_zeus_kill'] = df['zeus_kills'].fillna(0) / df['matches_played'].replace(0, 1)
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try:
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query_zeus_pick = f"""
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SELECT steam_id_64,
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AVG(CASE WHEN has_zeus = 1 THEN 1.0 ELSE 0.0 END) as basic_zeus_pick_rate
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FROM fact_round_player_economy
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WHERE steam_id_64 IN ({placeholders})
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GROUP BY steam_id_64
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"""
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df_zeus_pick = pd.read_sql_query(query_zeus_pick, conn, params=valid_ids)
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if not df_zeus_pick.empty:
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df = df.merge(df_zeus_pick, on='steam_id_64', how='left')
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except Exception:
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df['basic_zeus_pick_rate'] = 0.0
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df['basic_zeus_pick_rate'] = df.get('basic_zeus_pick_rate', 0.0)
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df['basic_zeus_pick_rate'] = pd.to_numeric(df['basic_zeus_pick_rate'], errors='coerce').fillna(0.0)
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# 2. STA (Detailed)
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query_sta = f"""
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@@ -481,12 +522,18 @@ class FeatureService:
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break
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df_fh_sides = pd.DataFrame(fh_rows)
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if not df_fh_sides.empty:
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if df_fh_sides.empty:
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df_fh_sides = pd.DataFrame(columns=['match_id', 'steam_id_64', 'fh_side', 'halftime_round'])
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else:
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df_fh_sides = df_fh_sides.merge(df_meta[['match_id', 'halftime_round']], on='match_id', how='left')
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if 'halftime_round' not in df_fh_sides.columns:
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df_fh_sides['halftime_round'] = 15
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df_fh_sides['halftime_round'] = df_fh_sides['halftime_round'].fillna(15).astype(int)
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# B. Get Kill Events
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query_events = f"""
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SELECT match_id, round_num, attacker_steam_id, victim_steam_id, event_type, is_headshot, event_time
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SELECT match_id, round_num, attacker_steam_id, victim_steam_id, event_type, is_headshot, event_time,
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weapon, trade_killer_steam_id, flash_assist_steam_id
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FROM fact_round_events
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WHERE event_type='kill'
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AND (attacker_steam_id IN ({placeholders}) OR victim_steam_id IN ({placeholders}))
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@@ -495,7 +542,7 @@ class FeatureService:
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# C. Get Round Scores
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query_rounds = f"""
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SELECT match_id, round_num, ct_score, t_score, winner_side
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SELECT match_id, round_num, ct_score, t_score, winner_side, duration
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FROM fact_rounds
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WHERE match_id IN (SELECT match_id FROM fact_match_players WHERE steam_id_64 IN ({placeholders}))
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"""
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@@ -982,7 +1029,7 @@ class FeatureService:
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# Fetch Base Data for Calculation
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q_new_feats = f"""
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SELECT mp.steam_id_64, mp.match_id, mp.match_team_id, mp.team_id,
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mp.rating, mp.adr, mp.is_win
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mp.rating, mp.adr, mp.is_win, mp.map as map_name
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FROM fact_match_players mp
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WHERE mp.steam_id_64 IN ({placeholders})
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"""
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@@ -1139,10 +1186,448 @@ class FeatureService:
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if df_pace is not None:
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df = df.merge(df_pace, on='steam_id_64', how='left')
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if not df_base.empty:
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player_mean = df_base.groupby('steam_id_64', as_index=False)['rating'].mean().rename(columns={'rating': 'player_mean_rating'})
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map_mean = df_base.groupby(['steam_id_64', 'map_name'], as_index=False)['rating'].mean().rename(columns={'rating': 'map_mean_rating'})
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map_dev = map_mean.merge(player_mean, on='steam_id_64', how='left')
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map_dev['abs_dev'] = (map_dev['map_mean_rating'] - map_dev['player_mean_rating']).abs()
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map_coef = map_dev.groupby('steam_id_64', as_index=False)['abs_dev'].mean().rename(columns={'abs_dev': 'map_stability_coef'})
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df = df.merge(map_coef, on='steam_id_64', how='left')
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import json
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df['rd_phase_kill_early_share'] = 0.0
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df['rd_phase_kill_mid_share'] = 0.0
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df['rd_phase_kill_late_share'] = 0.0
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df['rd_phase_death_early_share'] = 0.0
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df['rd_phase_death_mid_share'] = 0.0
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df['rd_phase_death_late_share'] = 0.0
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df['rd_firstdeath_team_first_death_rounds'] = 0
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df['rd_firstdeath_team_first_death_win_rate'] = 0.0
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df['rd_invalid_death_rounds'] = 0
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df['rd_invalid_death_rate'] = 0.0
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df['rd_pressure_kpr_ratio'] = 0.0
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df['rd_pressure_perf_ratio'] = 0.0
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df['rd_pressure_rounds_down3'] = 0
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df['rd_pressure_rounds_normal'] = 0
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df['rd_matchpoint_kpr_ratio'] = 0.0
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df['rd_matchpoint_perf_ratio'] = 0.0
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df['rd_matchpoint_rounds'] = 0
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df['rd_comeback_kill_share'] = 0.0
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df['rd_comeback_rounds'] = 0
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df['rd_trade_response_10s_rate'] = 0.0
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df['rd_weapon_top_json'] = "[]"
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df['rd_roundtype_split_json'] = "{}"
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if not df_events.empty:
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df_events['event_time'] = pd.to_numeric(df_events['event_time'], errors='coerce').fillna(0).astype(int)
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df_events['phase_bucket'] = pd.cut(
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df_events['event_time'],
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bins=[-1, 30, 60, float('inf')],
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labels=['early', 'mid', 'late']
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)
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k_cnt = df_events.groupby(['attacker_steam_id', 'phase_bucket']).size().unstack(fill_value=0)
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k_tot = k_cnt.sum(axis=1).replace(0, 1)
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k_share = k_cnt.div(k_tot, axis=0)
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k_share.index.name = 'steam_id_64'
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k_share = k_share.reset_index().rename(columns={
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'early': 'rd_phase_kill_early_share',
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'mid': 'rd_phase_kill_mid_share',
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'late': 'rd_phase_kill_late_share'
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})
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df = df.merge(
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k_share[['steam_id_64', 'rd_phase_kill_early_share', 'rd_phase_kill_mid_share', 'rd_phase_kill_late_share']],
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on='steam_id_64',
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how='left',
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suffixes=('', '_calc')
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)
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for c in ['rd_phase_kill_early_share', 'rd_phase_kill_mid_share', 'rd_phase_kill_late_share']:
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if f'{c}_calc' in df.columns:
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df[c] = df[f'{c}_calc'].fillna(df[c])
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df.drop(columns=[f'{c}_calc'], inplace=True)
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d_cnt = df_events.groupby(['victim_steam_id', 'phase_bucket']).size().unstack(fill_value=0)
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d_tot = d_cnt.sum(axis=1).replace(0, 1)
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d_share = d_cnt.div(d_tot, axis=0)
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d_share.index.name = 'steam_id_64'
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d_share = d_share.reset_index().rename(columns={
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'early': 'rd_phase_death_early_share',
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'mid': 'rd_phase_death_mid_share',
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'late': 'rd_phase_death_late_share'
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})
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df = df.merge(
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d_share[['steam_id_64', 'rd_phase_death_early_share', 'rd_phase_death_mid_share', 'rd_phase_death_late_share']],
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on='steam_id_64',
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how='left',
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suffixes=('', '_calc')
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)
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for c in ['rd_phase_death_early_share', 'rd_phase_death_mid_share', 'rd_phase_death_late_share']:
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if f'{c}_calc' in df.columns:
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df[c] = df[f'{c}_calc'].fillna(df[c])
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df.drop(columns=[f'{c}_calc'], inplace=True)
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if 'victim_side' in df_events.columns and 'winner_side' in df_events.columns:
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death_rows = df_events[['match_id', 'round_num', 'event_time', 'victim_steam_id', 'victim_side', 'winner_side']].copy()
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death_rows = death_rows[death_rows['victim_side'].isin(['CT', 'T']) & death_rows['winner_side'].isin(['CT', 'T'])]
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if not death_rows.empty:
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min_death = death_rows.groupby(['match_id', 'round_num', 'victim_side'], as_index=False)['event_time'].min().rename(columns={'event_time': 'min_time'})
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first_deaths = death_rows.merge(min_death, on=['match_id', 'round_num', 'victim_side'], how='inner')
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first_deaths = first_deaths[first_deaths['event_time'] == first_deaths['min_time']]
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first_deaths['is_win'] = (first_deaths['victim_side'] == first_deaths['winner_side']).astype(int)
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fd_agg = first_deaths.groupby('victim_steam_id')['is_win'].agg(['count', 'mean']).reset_index()
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fd_agg.rename(columns={
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'victim_steam_id': 'steam_id_64',
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'count': 'rd_firstdeath_team_first_death_rounds',
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'mean': 'rd_firstdeath_team_first_death_win_rate'
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}, inplace=True)
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df = df.merge(fd_agg, on='steam_id_64', how='left', suffixes=('', '_calc'))
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for c in ['rd_firstdeath_team_first_death_rounds', 'rd_firstdeath_team_first_death_win_rate']:
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if f'{c}_calc' in df.columns:
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df[c] = df[f'{c}_calc'].fillna(df[c])
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df.drop(columns=[f'{c}_calc'], inplace=True)
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kills_per_round = df_events.groupby(['match_id', 'round_num', 'attacker_steam_id']).size().reset_index(name='kills')
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flash_round = df_events[df_events['flash_assist_steam_id'].notna() & (df_events['flash_assist_steam_id'] != '')] \
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.groupby(['match_id', 'round_num', 'flash_assist_steam_id']).size().reset_index(name='flash_assists')
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death_round = df_events.groupby(['match_id', 'round_num', 'victim_steam_id']).size().reset_index(name='deaths')
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death_eval = death_round.rename(columns={'victim_steam_id': 'steam_id_64'}).merge(
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kills_per_round.rename(columns={'attacker_steam_id': 'steam_id_64'})[['match_id', 'round_num', 'steam_id_64', 'kills']],
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on=['match_id', 'round_num', 'steam_id_64'],
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how='left'
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).merge(
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flash_round.rename(columns={'flash_assist_steam_id': 'steam_id_64'})[['match_id', 'round_num', 'steam_id_64', 'flash_assists']],
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on=['match_id', 'round_num', 'steam_id_64'],
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how='left'
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).fillna({'kills': 0, 'flash_assists': 0})
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death_eval['is_invalid'] = ((death_eval['kills'] <= 0) & (death_eval['flash_assists'] <= 0)).astype(int)
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invalid_agg = death_eval.groupby('steam_id_64')['is_invalid'].agg(['sum', 'count']).reset_index()
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invalid_agg.rename(columns={'sum': 'rd_invalid_death_rounds', 'count': 'death_rounds'}, inplace=True)
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invalid_agg['rd_invalid_death_rate'] = invalid_agg['rd_invalid_death_rounds'] / invalid_agg['death_rounds'].replace(0, 1)
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df = df.merge(
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invalid_agg[['steam_id_64', 'rd_invalid_death_rounds', 'rd_invalid_death_rate']],
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on='steam_id_64',
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how='left',
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suffixes=('', '_calc')
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)
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for c in ['rd_invalid_death_rounds', 'rd_invalid_death_rate']:
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if f'{c}_calc' in df.columns:
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df[c] = df[f'{c}_calc'].fillna(df[c])
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df.drop(columns=[f'{c}_calc'], inplace=True)
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if 'weapon' in df_events.columns:
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w = df_events.copy()
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w['weapon'] = w['weapon'].fillna('').astype(str)
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w = w[w['weapon'] != '']
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if not w.empty:
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w_agg = w.groupby(['attacker_steam_id', 'weapon']).agg(
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kills=('weapon', 'size'),
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hs=('is_headshot', 'sum'),
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).reset_index()
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top_json = {}
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for pid, g in w_agg.groupby('attacker_steam_id'):
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g = g.sort_values('kills', ascending=False)
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total = float(g['kills'].sum()) if g['kills'].sum() else 1.0
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top = g.head(5)
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items = []
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for _, r in top.iterrows():
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k = float(r['kills'])
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hs = float(r['hs'])
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wi = get_weapon_info(r['weapon'])
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items.append({
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'weapon': r['weapon'],
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'kills': int(k),
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'share': k / total,
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'hs_rate': hs / k if k else 0.0,
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'price': wi.price if wi else None,
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'side': wi.side if wi else None,
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'category': wi.category if wi else None,
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})
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top_json[str(pid)] = json.dumps(items, ensure_ascii=False)
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if top_json:
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df['rd_weapon_top_json'] = df['steam_id_64'].map(top_json).fillna("[]")
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if not df_rounds.empty and not df_fh_sides.empty and not df_events.empty:
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df_rounds2 = df_rounds.copy()
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if not df_meta.empty:
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df_rounds2 = df_rounds2.merge(df_meta[['match_id', 'halftime_round']], on='match_id', how='left')
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df_rounds2 = df_rounds2.sort_values(['match_id', 'round_num'])
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df_rounds2['prev_ct'] = df_rounds2.groupby('match_id')['ct_score'].shift(1).fillna(0)
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df_rounds2['prev_t'] = df_rounds2.groupby('match_id')['t_score'].shift(1).fillna(0)
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df_rounds2['ct_deficit'] = df_rounds2['prev_t'] - df_rounds2['prev_ct']
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df_rounds2['t_deficit'] = df_rounds2['prev_ct'] - df_rounds2['prev_t']
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df_rounds2['mp_score'] = df_rounds2['halftime_round'].fillna(15)
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df_rounds2['is_match_point_round'] = (df_rounds2['prev_ct'] == df_rounds2['mp_score']) | (df_rounds2['prev_t'] == df_rounds2['mp_score'])
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df_rounds2['reg_rounds'] = (df_rounds2['halftime_round'].fillna(15) * 2).astype(int)
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df_rounds2['is_overtime_round'] = df_rounds2['round_num'] > df_rounds2['reg_rounds']
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all_rounds = df_rounds2[['match_id', 'round_num']].drop_duplicates()
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df_player_rounds = all_rounds.merge(df_fh_sides, on='match_id', how='inner')
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if 'halftime_round' not in df_player_rounds.columns:
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df_player_rounds['halftime_round'] = 15
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df_player_rounds['halftime_round'] = pd.to_numeric(df_player_rounds['halftime_round'], errors='coerce').fillna(15).astype(int)
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mask_fh = df_player_rounds['round_num'] <= df_player_rounds['halftime_round']
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df_player_rounds['side'] = np.where(mask_fh, df_player_rounds['fh_side'], np.where(df_player_rounds['fh_side'] == 'CT', 'T', 'CT'))
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df_player_rounds = df_player_rounds.merge(
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df_rounds2[['match_id', 'round_num', 'ct_deficit', 't_deficit', 'is_match_point_round', 'is_overtime_round', 'reg_rounds']],
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on=['match_id', 'round_num'],
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how='left'
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)
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df_player_rounds['deficit'] = np.where(
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df_player_rounds['side'] == 'CT',
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df_player_rounds['ct_deficit'],
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np.where(df_player_rounds['side'] == 'T', df_player_rounds['t_deficit'], 0)
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)
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df_player_rounds['is_pressure_round'] = (df_player_rounds['deficit'] >= 3).astype(int)
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df_player_rounds['is_pistol_round'] = (
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(df_player_rounds['round_num'] == 1) |
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(df_player_rounds['round_num'] == df_player_rounds['halftime_round'] + 1)
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).astype(int)
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kills_per_round = df_events.groupby(['match_id', 'round_num', 'attacker_steam_id']).size().reset_index(name='kills')
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df_player_rounds = df_player_rounds.merge(
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kills_per_round.rename(columns={'attacker_steam_id': 'steam_id_64'}),
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on=['match_id', 'round_num', 'steam_id_64'],
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how='left'
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)
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df_player_rounds['kills'] = df_player_rounds['kills'].fillna(0)
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grp = df_player_rounds.groupby(['steam_id_64', 'is_pressure_round'])['kills'].agg(['mean', 'count']).reset_index()
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pressure = grp.pivot(index='steam_id_64', columns='is_pressure_round').fillna(0)
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if ('mean', 1) in pressure.columns and ('mean', 0) in pressure.columns:
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pressure_kpr_ratio = (pressure[('mean', 1)] / pressure[('mean', 0)].replace(0, 1)).reset_index()
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pressure_kpr_ratio.columns = ['steam_id_64', 'rd_pressure_kpr_ratio']
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df = df.merge(pressure_kpr_ratio, on='steam_id_64', how='left', suffixes=('', '_calc'))
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if 'rd_pressure_kpr_ratio_calc' in df.columns:
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df['rd_pressure_kpr_ratio'] = df['rd_pressure_kpr_ratio_calc'].fillna(df['rd_pressure_kpr_ratio'])
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df.drop(columns=['rd_pressure_kpr_ratio_calc'], inplace=True)
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if ('count', 1) in pressure.columns:
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pr_cnt = pressure[('count', 1)].reset_index()
|
||||
pr_cnt.columns = ['steam_id_64', 'rd_pressure_rounds_down3']
|
||||
df = df.merge(pr_cnt, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_pressure_rounds_down3_calc' in df.columns:
|
||||
df['rd_pressure_rounds_down3'] = df['rd_pressure_rounds_down3_calc'].fillna(df['rd_pressure_rounds_down3'])
|
||||
df.drop(columns=['rd_pressure_rounds_down3_calc'], inplace=True)
|
||||
if ('count', 0) in pressure.columns:
|
||||
nr_cnt = pressure[('count', 0)].reset_index()
|
||||
nr_cnt.columns = ['steam_id_64', 'rd_pressure_rounds_normal']
|
||||
df = df.merge(nr_cnt, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_pressure_rounds_normal_calc' in df.columns:
|
||||
df['rd_pressure_rounds_normal'] = df['rd_pressure_rounds_normal_calc'].fillna(df['rd_pressure_rounds_normal'])
|
||||
df.drop(columns=['rd_pressure_rounds_normal_calc'], inplace=True)
|
||||
|
||||
mp_grp = df_player_rounds.groupby(['steam_id_64', 'is_match_point_round'])['kills'].agg(['mean', 'count']).reset_index()
|
||||
mp = mp_grp.pivot(index='steam_id_64', columns='is_match_point_round').fillna(0)
|
||||
if ('mean', 1) in mp.columns and ('mean', 0) in mp.columns:
|
||||
mp_ratio = (mp[('mean', 1)] / mp[('mean', 0)].replace(0, 1)).reset_index()
|
||||
mp_ratio.columns = ['steam_id_64', 'rd_matchpoint_kpr_ratio']
|
||||
df = df.merge(mp_ratio, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_matchpoint_kpr_ratio_calc' in df.columns:
|
||||
df['rd_matchpoint_kpr_ratio'] = df['rd_matchpoint_kpr_ratio_calc'].fillna(df['rd_matchpoint_kpr_ratio'])
|
||||
df.drop(columns=['rd_matchpoint_kpr_ratio_calc'], inplace=True)
|
||||
if ('count', 1) in mp.columns:
|
||||
mp_cnt = mp[('count', 1)].reset_index()
|
||||
mp_cnt.columns = ['steam_id_64', 'rd_matchpoint_rounds']
|
||||
df = df.merge(mp_cnt, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_matchpoint_rounds_calc' in df.columns:
|
||||
df['rd_matchpoint_rounds'] = df['rd_matchpoint_rounds_calc'].fillna(df['rd_matchpoint_rounds'])
|
||||
df.drop(columns=['rd_matchpoint_rounds_calc'], inplace=True)
|
||||
|
||||
try:
|
||||
q_player_team = f"SELECT match_id, steam_id_64, team_id FROM fact_match_players WHERE steam_id_64 IN ({placeholders})"
|
||||
df_player_team = pd.read_sql_query(q_player_team, conn, params=valid_ids)
|
||||
except Exception:
|
||||
df_player_team = pd.DataFrame()
|
||||
|
||||
if not df_player_team.empty:
|
||||
try:
|
||||
q_team_roles = f"""
|
||||
SELECT match_id, group_id as team_id, group_fh_role
|
||||
FROM fact_match_teams
|
||||
WHERE match_id IN (SELECT match_id FROM fact_match_players WHERE steam_id_64 IN ({placeholders}))
|
||||
"""
|
||||
df_team_roles = pd.read_sql_query(q_team_roles, conn, params=valid_ids)
|
||||
except Exception:
|
||||
df_team_roles = pd.DataFrame()
|
||||
|
||||
if not df_team_roles.empty:
|
||||
team_round = df_rounds2[['match_id', 'round_num', 'ct_score', 't_score', 'prev_ct', 'prev_t', 'halftime_round']].merge(df_team_roles, on='match_id', how='inner')
|
||||
fh_ct = team_round['group_fh_role'] == 1
|
||||
mask_fh = team_round['round_num'] <= team_round['halftime_round']
|
||||
team_round['team_side'] = np.where(mask_fh, np.where(fh_ct, 'CT', 'T'), np.where(fh_ct, 'T', 'CT'))
|
||||
team_round['team_prev_score'] = np.where(team_round['team_side'] == 'CT', team_round['prev_ct'], team_round['prev_t'])
|
||||
team_round['team_score_after'] = np.where(team_round['team_side'] == 'CT', team_round['ct_score'], team_round['t_score'])
|
||||
team_round['opp_prev_score'] = np.where(team_round['team_side'] == 'CT', team_round['prev_t'], team_round['prev_ct'])
|
||||
team_round['opp_score_after'] = np.where(team_round['team_side'] == 'CT', team_round['t_score'], team_round['ct_score'])
|
||||
team_round['deficit_before'] = team_round['opp_prev_score'] - team_round['team_prev_score']
|
||||
team_round['deficit_after'] = team_round['opp_score_after'] - team_round['team_score_after']
|
||||
team_round['is_comeback_round'] = ((team_round['deficit_before'] > 0) & (team_round['deficit_after'] < team_round['deficit_before'])).astype(int)
|
||||
comeback_keys = team_round[team_round['is_comeback_round'] == 1][['match_id', 'round_num', 'team_id']].drop_duplicates()
|
||||
|
||||
if not comeback_keys.empty:
|
||||
ev_att = df_events[['match_id', 'round_num', 'attacker_steam_id', 'event_time']].merge(
|
||||
df_player_team.rename(columns={'steam_id_64': 'attacker_steam_id', 'team_id': 'att_team_id'}),
|
||||
on=['match_id', 'attacker_steam_id'],
|
||||
how='left'
|
||||
)
|
||||
team_kills = ev_att[ev_att['att_team_id'].notna()].groupby(['match_id', 'round_num', 'att_team_id']).size().reset_index(name='team_kills')
|
||||
player_kills = ev_att.groupby(['match_id', 'round_num', 'attacker_steam_id', 'att_team_id']).size().reset_index(name='player_kills')
|
||||
|
||||
player_kills = player_kills.merge(
|
||||
comeback_keys.rename(columns={'team_id': 'att_team_id'}),
|
||||
on=['match_id', 'round_num', 'att_team_id'],
|
||||
how='inner'
|
||||
)
|
||||
if not player_kills.empty:
|
||||
player_kills = player_kills.merge(team_kills, on=['match_id', 'round_num', 'att_team_id'], how='left').fillna({'team_kills': 0})
|
||||
player_kills['share'] = player_kills['player_kills'] / player_kills['team_kills'].replace(0, 1)
|
||||
cb_share = player_kills.groupby('attacker_steam_id')['share'].mean().reset_index()
|
||||
cb_share.rename(columns={'attacker_steam_id': 'steam_id_64', 'share': 'rd_comeback_kill_share'}, inplace=True)
|
||||
df = df.merge(cb_share, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_comeback_kill_share_calc' in df.columns:
|
||||
df['rd_comeback_kill_share'] = df['rd_comeback_kill_share_calc'].fillna(df['rd_comeback_kill_share'])
|
||||
df.drop(columns=['rd_comeback_kill_share_calc'], inplace=True)
|
||||
|
||||
cb_rounds = comeback_keys.merge(df_player_team, left_on=['match_id', 'team_id'], right_on=['match_id', 'team_id'], how='inner')
|
||||
cb_cnt = cb_rounds.groupby('steam_id_64').size().reset_index(name='rd_comeback_rounds')
|
||||
df = df.merge(cb_cnt, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_comeback_rounds_calc' in df.columns:
|
||||
df['rd_comeback_rounds'] = df['rd_comeback_rounds_calc'].fillna(df['rd_comeback_rounds'])
|
||||
df.drop(columns=['rd_comeback_rounds_calc'], inplace=True)
|
||||
|
||||
death_team = df_events[['match_id', 'round_num', 'event_time', 'victim_steam_id']].merge(
|
||||
df_player_team.rename(columns={'steam_id_64': 'victim_steam_id', 'team_id': 'team_id'}),
|
||||
on=['match_id', 'victim_steam_id'],
|
||||
how='left'
|
||||
)
|
||||
death_team = death_team[death_team['team_id'].notna()]
|
||||
if not death_team.empty:
|
||||
roster = df_player_team.rename(columns={'steam_id_64': 'steam_id_64', 'team_id': 'team_id'})[['match_id', 'team_id', 'steam_id_64']].drop_duplicates()
|
||||
opp = death_team.merge(roster, on=['match_id', 'team_id'], how='inner', suffixes=('', '_teammate'))
|
||||
opp = opp[opp['steam_id_64'] != opp['victim_steam_id']]
|
||||
opp_time = opp.groupby(['match_id', 'round_num', 'steam_id_64'], as_index=False)['event_time'].min().rename(columns={'event_time': 'teammate_death_time'})
|
||||
|
||||
kills_time = df_events[['match_id', 'round_num', 'event_time', 'attacker_steam_id']].rename(columns={'attacker_steam_id': 'steam_id_64', 'event_time': 'kill_time'})
|
||||
m = opp_time.merge(kills_time, on=['match_id', 'round_num', 'steam_id_64'], how='left')
|
||||
m['in_window'] = ((m['kill_time'] >= m['teammate_death_time']) & (m['kill_time'] <= m['teammate_death_time'] + 10)).astype(int)
|
||||
success = m.groupby(['match_id', 'round_num', 'steam_id_64'], as_index=False)['in_window'].max()
|
||||
rate = success.groupby('steam_id_64')['in_window'].mean().reset_index()
|
||||
rate.rename(columns={'in_window': 'rd_trade_response_10s_rate'}, inplace=True)
|
||||
df = df.merge(rate, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_trade_response_10s_rate_calc' in df.columns:
|
||||
df['rd_trade_response_10s_rate'] = df['rd_trade_response_10s_rate_calc'].fillna(df['rd_trade_response_10s_rate'])
|
||||
df.drop(columns=['rd_trade_response_10s_rate_calc'], inplace=True)
|
||||
|
||||
eco_rows = []
|
||||
try:
|
||||
q_econ = f"""
|
||||
SELECT match_id, round_num, steam_id_64, equipment_value, round_performance_score
|
||||
FROM fact_round_player_economy
|
||||
WHERE steam_id_64 IN ({placeholders})
|
||||
"""
|
||||
df_econ = pd.read_sql_query(q_econ, conn, params=valid_ids)
|
||||
except Exception:
|
||||
df_econ = pd.DataFrame()
|
||||
|
||||
if not df_econ.empty:
|
||||
df_econ['equipment_value'] = pd.to_numeric(df_econ['equipment_value'], errors='coerce').fillna(0).astype(int)
|
||||
df_econ['round_performance_score'] = pd.to_numeric(df_econ['round_performance_score'], errors='coerce').fillna(0.0)
|
||||
df_econ = df_econ.merge(df_rounds2[['match_id', 'round_num', 'is_overtime_round', 'is_match_point_round', 'ct_deficit', 't_deficit', 'prev_ct', 'prev_t']], on=['match_id', 'round_num'], how='left')
|
||||
df_econ = df_econ.merge(df_fh_sides[['match_id', 'steam_id_64', 'fh_side', 'halftime_round']], on=['match_id', 'steam_id_64'], how='left')
|
||||
mask_fh = df_econ['round_num'] <= df_econ['halftime_round']
|
||||
df_econ['side'] = np.where(mask_fh, df_econ['fh_side'], np.where(df_econ['fh_side'] == 'CT', 'T', 'CT'))
|
||||
df_econ['deficit'] = np.where(df_econ['side'] == 'CT', df_econ['ct_deficit'], df_econ['t_deficit'])
|
||||
df_econ['is_pressure_round'] = (df_econ['deficit'] >= 3).astype(int)
|
||||
|
||||
perf_grp = df_econ.groupby(['steam_id_64', 'is_pressure_round'])['round_performance_score'].agg(['mean', 'count']).reset_index()
|
||||
perf = perf_grp.pivot(index='steam_id_64', columns='is_pressure_round').fillna(0)
|
||||
if ('mean', 1) in perf.columns and ('mean', 0) in perf.columns:
|
||||
perf_ratio = (perf[('mean', 1)] / perf[('mean', 0)].replace(0, 1)).reset_index()
|
||||
perf_ratio.columns = ['steam_id_64', 'rd_pressure_perf_ratio']
|
||||
df = df.merge(perf_ratio, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_pressure_perf_ratio_calc' in df.columns:
|
||||
df['rd_pressure_perf_ratio'] = df['rd_pressure_perf_ratio_calc'].fillna(df['rd_pressure_perf_ratio'])
|
||||
df.drop(columns=['rd_pressure_perf_ratio_calc'], inplace=True)
|
||||
|
||||
mp_perf_grp = df_econ.groupby(['steam_id_64', 'is_match_point_round'])['round_performance_score'].agg(['mean', 'count']).reset_index()
|
||||
mp_perf = mp_perf_grp.pivot(index='steam_id_64', columns='is_match_point_round').fillna(0)
|
||||
if ('mean', 1) in mp_perf.columns and ('mean', 0) in mp_perf.columns:
|
||||
mp_perf_ratio = (mp_perf[('mean', 1)] / mp_perf[('mean', 0)].replace(0, 1)).reset_index()
|
||||
mp_perf_ratio.columns = ['steam_id_64', 'rd_matchpoint_perf_ratio']
|
||||
df = df.merge(mp_perf_ratio, on='steam_id_64', how='left', suffixes=('', '_calc'))
|
||||
if 'rd_matchpoint_perf_ratio_calc' in df.columns:
|
||||
df['rd_matchpoint_perf_ratio'] = df['rd_matchpoint_perf_ratio_calc'].fillna(df['rd_matchpoint_perf_ratio'])
|
||||
df.drop(columns=['rd_matchpoint_perf_ratio_calc'], inplace=True)
|
||||
|
||||
eco = df_econ.copy()
|
||||
eco['round_type'] = np.select(
|
||||
[
|
||||
eco['is_overtime_round'] == 1,
|
||||
eco['equipment_value'] < 2000,
|
||||
eco['equipment_value'] >= 4000,
|
||||
],
|
||||
[
|
||||
'overtime',
|
||||
'eco',
|
||||
'fullbuy',
|
||||
],
|
||||
default='rifle'
|
||||
)
|
||||
eco_rounds = eco.groupby(['steam_id_64', 'round_type']).size().reset_index(name='rounds')
|
||||
perf_mean = eco.groupby(['steam_id_64', 'round_type'])['round_performance_score'].mean().reset_index(name='perf')
|
||||
eco_rows = eco_rounds.merge(perf_mean, on=['steam_id_64', 'round_type'], how='left')
|
||||
|
||||
if eco_rows is not None and len(eco_rows) > 0:
|
||||
kpr_rounds = df_player_rounds[['match_id', 'round_num', 'steam_id_64', 'kills', 'is_pistol_round', 'is_overtime_round']].copy()
|
||||
kpr_rounds['round_type'] = np.select(
|
||||
[
|
||||
kpr_rounds['is_overtime_round'] == 1,
|
||||
kpr_rounds['is_pistol_round'] == 1,
|
||||
],
|
||||
[
|
||||
'overtime',
|
||||
'pistol',
|
||||
],
|
||||
default='reg'
|
||||
)
|
||||
kpr = kpr_rounds.groupby(['steam_id_64', 'round_type']).agg(kpr=('kills', 'mean'), rounds=('kills', 'size')).reset_index()
|
||||
kpr_dict = {}
|
||||
for pid, g in kpr.groupby('steam_id_64'):
|
||||
d = {}
|
||||
for _, r in g.iterrows():
|
||||
d[r['round_type']] = {'kpr': float(r['kpr']), 'rounds': int(r['rounds'])}
|
||||
kpr_dict[str(pid)] = d
|
||||
|
||||
econ_dict = {}
|
||||
if isinstance(eco_rows, pd.DataFrame) and not eco_rows.empty:
|
||||
for pid, g in eco_rows.groupby('steam_id_64'):
|
||||
d = {}
|
||||
for _, r in g.iterrows():
|
||||
d[r['round_type']] = {'perf': float(r['perf']) if r['perf'] is not None else 0.0, 'rounds': int(r['rounds'])}
|
||||
econ_dict[str(pid)] = d
|
||||
|
||||
out = {}
|
||||
for pid in df['steam_id_64'].astype(str).tolist():
|
||||
merged = {}
|
||||
if pid in kpr_dict:
|
||||
merged.update(kpr_dict[pid])
|
||||
if pid in econ_dict:
|
||||
for k, v in econ_dict[pid].items():
|
||||
merged.setdefault(k, {}).update(v)
|
||||
out[pid] = json.dumps(merged, ensure_ascii=False)
|
||||
df['rd_roundtype_split_json'] = df['steam_id_64'].astype(str).map(out).fillna("{}")
|
||||
|
||||
# Final Mappings
|
||||
df['total_matches'] = df['matches_played']
|
||||
|
||||
return df.fillna(0)
|
||||
for c in df.columns:
|
||||
if df[c].dtype.kind in "biufc":
|
||||
df[c] = df[c].fillna(0)
|
||||
else:
|
||||
df[c] = df[c].fillna("")
|
||||
return df
|
||||
|
||||
@staticmethod
|
||||
def _calculate_economy_features(conn, player_ids):
|
||||
|
||||
@@ -725,6 +725,7 @@ class StatsService:
|
||||
metrics = [
|
||||
'basic_avg_rating', 'basic_avg_kd', 'basic_avg_kast', 'basic_avg_rws', 'basic_avg_adr',
|
||||
'basic_avg_headshot_kills', 'basic_headshot_rate', 'basic_avg_assisted_kill', 'basic_avg_awp_kill', 'basic_avg_jump_count',
|
||||
'basic_avg_knife_kill', 'basic_avg_zeus_kill', 'basic_zeus_pick_rate',
|
||||
'basic_avg_mvps', 'basic_avg_plants', 'basic_avg_defuses', 'basic_avg_flash_assists',
|
||||
'basic_avg_first_kill', 'basic_avg_first_death', 'basic_first_kill_rate', 'basic_first_death_rate',
|
||||
'basic_avg_kill_2', 'basic_avg_kill_3', 'basic_avg_kill_4', 'basic_avg_kill_5',
|
||||
@@ -745,6 +746,13 @@ class StatsService:
|
||||
# New: ECO & PACE
|
||||
'eco_avg_damage_per_1k', 'eco_rating_eco_rounds', 'eco_kd_ratio', 'eco_avg_rounds',
|
||||
'pace_avg_time_to_first_contact', 'pace_trade_kill_rate', 'pace_opening_kill_time', 'pace_avg_life_time',
|
||||
# New: ROUND (Round Dynamics)
|
||||
'rd_phase_kill_early_share', 'rd_phase_kill_mid_share', 'rd_phase_kill_late_share',
|
||||
'rd_phase_death_early_share', 'rd_phase_death_mid_share', 'rd_phase_death_late_share',
|
||||
'rd_firstdeath_team_first_death_win_rate', 'rd_invalid_death_rate',
|
||||
'rd_pressure_kpr_ratio', 'rd_matchpoint_kpr_ratio', 'rd_trade_response_10s_rate',
|
||||
'rd_pressure_perf_ratio', 'rd_matchpoint_perf_ratio',
|
||||
'rd_comeback_kill_share', 'map_stability_coef',
|
||||
# New: Party Size Stats
|
||||
'party_1_win_rate', 'party_1_rating', 'party_1_adr',
|
||||
'party_2_win_rate', 'party_2_rating', 'party_2_adr',
|
||||
@@ -766,7 +774,7 @@ class StatsService:
|
||||
# But here we just use L3 columns directly.
|
||||
|
||||
# Define metrics where LOWER is BETTER
|
||||
lower_is_better = ['pace_avg_time_to_first_contact', 'pace_opening_kill_time']
|
||||
lower_is_better = ['pace_avg_time_to_first_contact', 'pace_opening_kill_time', 'rd_invalid_death_rate', 'map_stability_coef']
|
||||
|
||||
result = {}
|
||||
|
||||
@@ -808,6 +816,141 @@ class StatsService:
|
||||
if m in legacy_map:
|
||||
result[legacy_map[m]] = result[m]
|
||||
|
||||
def build_roundtype_metric_distribution(metric_key, round_type, subkey):
|
||||
values2 = []
|
||||
for sid, p in stats_map.items():
|
||||
raw = p.get('rd_roundtype_split_json') or ''
|
||||
if not raw:
|
||||
continue
|
||||
try:
|
||||
obj = json.loads(raw) if isinstance(raw, str) else raw
|
||||
except:
|
||||
continue
|
||||
if not isinstance(obj, dict):
|
||||
continue
|
||||
bucket = obj.get(round_type)
|
||||
if not isinstance(bucket, dict):
|
||||
continue
|
||||
v = bucket.get(subkey)
|
||||
if v is None:
|
||||
continue
|
||||
try:
|
||||
v = float(v)
|
||||
except:
|
||||
continue
|
||||
values2.append(v)
|
||||
raw_target = stats_map.get(target_steam_id, {}).get('rd_roundtype_split_json') or ''
|
||||
target_val2 = None
|
||||
if raw_target:
|
||||
try:
|
||||
obj_t = json.loads(raw_target) if isinstance(raw_target, str) else raw_target
|
||||
if isinstance(obj_t, dict) and isinstance(obj_t.get(round_type), dict):
|
||||
tv = obj_t[round_type].get(subkey)
|
||||
if tv is not None:
|
||||
target_val2 = float(tv)
|
||||
except:
|
||||
target_val2 = None
|
||||
if not values2 or target_val2 is None:
|
||||
return None
|
||||
values2.sort(reverse=True)
|
||||
try:
|
||||
rank2 = values2.index(target_val2) + 1
|
||||
except ValueError:
|
||||
rank2 = len(values2)
|
||||
return {
|
||||
'val': target_val2,
|
||||
'rank': rank2,
|
||||
'total': len(values2),
|
||||
'min': min(values2),
|
||||
'max': max(values2),
|
||||
'avg': sum(values2) / len(values2),
|
||||
'inverted': False
|
||||
}
|
||||
|
||||
rt_kpr_types = ['pistol', 'reg', 'overtime']
|
||||
rt_perf_types = ['eco', 'rifle', 'fullbuy', 'overtime']
|
||||
for t in rt_kpr_types:
|
||||
result[f'rd_rt_kpr_{t}'] = build_roundtype_metric_distribution('rd_roundtype_split_json', t, 'kpr')
|
||||
for t in rt_perf_types:
|
||||
result[f'rd_rt_perf_{t}'] = build_roundtype_metric_distribution('rd_roundtype_split_json', t, 'perf')
|
||||
|
||||
top_weapon_rank_map = {}
|
||||
try:
|
||||
raw_tw = stats_map.get(target_steam_id, {}).get('rd_weapon_top_json') or '[]'
|
||||
tw_items = json.loads(raw_tw) if isinstance(raw_tw, str) else raw_tw
|
||||
weapons = []
|
||||
if isinstance(tw_items, list):
|
||||
for it in tw_items:
|
||||
if isinstance(it, dict) and it.get('weapon'):
|
||||
weapons.append(str(it.get('weapon')))
|
||||
weapons = weapons[:5]
|
||||
except Exception:
|
||||
weapons = []
|
||||
|
||||
if weapons:
|
||||
w_placeholders = ','.join('?' for _ in weapons)
|
||||
sql_w = f"""
|
||||
SELECT attacker_steam_id as steam_id_64,
|
||||
weapon,
|
||||
COUNT(*) as kills,
|
||||
SUM(is_headshot) as hs
|
||||
FROM fact_round_events
|
||||
WHERE event_type='kill'
|
||||
AND attacker_steam_id IN ({l2_placeholders})
|
||||
AND weapon IN ({w_placeholders})
|
||||
GROUP BY attacker_steam_id, weapon
|
||||
"""
|
||||
weapon_rows = query_db('l2', sql_w, active_roster_ids + weapons)
|
||||
per_weapon = {}
|
||||
for r in weapon_rows:
|
||||
sid = str(r['steam_id_64'])
|
||||
w = str(r['weapon'] or '')
|
||||
if not w:
|
||||
continue
|
||||
kills = int(r['kills'] or 0)
|
||||
hs = int(r['hs'] or 0)
|
||||
mp = stats_map.get(sid, {}).get('total_matches') or 0
|
||||
try:
|
||||
mp = float(mp)
|
||||
except Exception:
|
||||
mp = 0
|
||||
kpm = (kills / mp) if (kills > 0 and mp > 0) else None
|
||||
hs_rate = (hs / kills) if kills > 0 else None
|
||||
per_weapon.setdefault(w, {})[sid] = {"kpm": kpm, "hs_rate": hs_rate}
|
||||
|
||||
for w in weapons:
|
||||
d = per_weapon.get(w) or {}
|
||||
target_d = d.get(target_steam_id) or {}
|
||||
target_kpm = target_d.get("kpm")
|
||||
target_hs = target_d.get("hs_rate")
|
||||
|
||||
kpm_vals = [v.get("kpm") for v in d.values() if v.get("kpm") is not None]
|
||||
hs_vals = [v.get("hs_rate") for v in d.values() if v.get("hs_rate") is not None]
|
||||
|
||||
kpm_rank = None
|
||||
hs_rank = None
|
||||
if kpm_vals and target_kpm is not None:
|
||||
kpm_vals.sort(reverse=True)
|
||||
try:
|
||||
kpm_rank = kpm_vals.index(target_kpm) + 1
|
||||
except ValueError:
|
||||
kpm_rank = len(kpm_vals)
|
||||
if hs_vals and target_hs is not None:
|
||||
hs_vals.sort(reverse=True)
|
||||
try:
|
||||
hs_rank = hs_vals.index(target_hs) + 1
|
||||
except ValueError:
|
||||
hs_rank = len(hs_vals)
|
||||
|
||||
top_weapon_rank_map[w] = {
|
||||
"kpm_rank": kpm_rank,
|
||||
"kpm_total": len(kpm_vals),
|
||||
"hs_rank": hs_rank,
|
||||
"hs_total": len(hs_vals),
|
||||
}
|
||||
|
||||
result['top_weapon_rank_map'] = top_weapon_rank_map
|
||||
|
||||
return result
|
||||
|
||||
@staticmethod
|
||||
|
||||
119
web/services/weapon_service.py
Normal file
119
web/services/weapon_service.py
Normal file
@@ -0,0 +1,119 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from typing import Optional
|
||||
|
||||
|
||||
@dataclass(frozen=True)
|
||||
class WeaponInfo:
|
||||
name: str
|
||||
price: int
|
||||
side: str
|
||||
category: str
|
||||
|
||||
|
||||
_WEAPON_TABLE = {
|
||||
"glock": WeaponInfo(name="Glock-18", price=200, side="T", category="pistol"),
|
||||
"hkp2000": WeaponInfo(name="P2000", price=200, side="CT", category="pistol"),
|
||||
"usp_silencer": WeaponInfo(name="USP-S", price=200, side="CT", category="pistol"),
|
||||
"elite": WeaponInfo(name="Dual Berettas", price=300, side="Both", category="pistol"),
|
||||
"p250": WeaponInfo(name="P250", price=300, side="Both", category="pistol"),
|
||||
"tec9": WeaponInfo(name="Tec-9", price=500, side="T", category="pistol"),
|
||||
"fiveseven": WeaponInfo(name="Five-SeveN", price=500, side="CT", category="pistol"),
|
||||
"cz75a": WeaponInfo(name="CZ75-Auto", price=500, side="Both", category="pistol"),
|
||||
"revolver": WeaponInfo(name="R8 Revolver", price=600, side="Both", category="pistol"),
|
||||
"deagle": WeaponInfo(name="Desert Eagle", price=700, side="Both", category="pistol"),
|
||||
"mac10": WeaponInfo(name="MAC-10", price=1050, side="T", category="smg"),
|
||||
"mp9": WeaponInfo(name="MP9", price=1250, side="CT", category="smg"),
|
||||
"ump45": WeaponInfo(name="UMP-45", price=1200, side="Both", category="smg"),
|
||||
"bizon": WeaponInfo(name="PP-Bizon", price=1400, side="Both", category="smg"),
|
||||
"mp7": WeaponInfo(name="MP7", price=1500, side="Both", category="smg"),
|
||||
"mp5sd": WeaponInfo(name="MP5-SD", price=1500, side="Both", category="smg"),
|
||||
"nova": WeaponInfo(name="Nova", price=1050, side="Both", category="shotgun"),
|
||||
"mag7": WeaponInfo(name="MAG-7", price=1300, side="CT", category="shotgun"),
|
||||
"sawedoff": WeaponInfo(name="Sawed-Off", price=1100, side="T", category="shotgun"),
|
||||
"xm1014": WeaponInfo(name="XM1014", price=2000, side="Both", category="shotgun"),
|
||||
"galilar": WeaponInfo(name="Galil AR", price=1800, side="T", category="rifle"),
|
||||
"famas": WeaponInfo(name="FAMAS", price=2050, side="CT", category="rifle"),
|
||||
"ak47": WeaponInfo(name="AK-47", price=2700, side="T", category="rifle"),
|
||||
"m4a1": WeaponInfo(name="M4A4", price=2900, side="CT", category="rifle"),
|
||||
"m4a1_silencer": WeaponInfo(name="M4A1-S", price=2900, side="CT", category="rifle"),
|
||||
"aug": WeaponInfo(name="AUG", price=3300, side="CT", category="rifle"),
|
||||
"sg556": WeaponInfo(name="SG 553", price=3300, side="T", category="rifle"),
|
||||
"awp": WeaponInfo(name="AWP", price=4750, side="Both", category="sniper"),
|
||||
"scar20": WeaponInfo(name="SCAR-20", price=5000, side="CT", category="sniper"),
|
||||
"g3sg1": WeaponInfo(name="G3SG1", price=5000, side="T", category="sniper"),
|
||||
"negev": WeaponInfo(name="Negev", price=1700, side="Both", category="lmg"),
|
||||
"m249": WeaponInfo(name="M249", price=5200, side="Both", category="lmg"),
|
||||
}
|
||||
|
||||
_ALIASES = {
|
||||
"weapon_glock": "glock",
|
||||
"weapon_hkp2000": "hkp2000",
|
||||
"weapon_usp_silencer": "usp_silencer",
|
||||
"weapon_elite": "elite",
|
||||
"weapon_p250": "p250",
|
||||
"weapon_tec9": "tec9",
|
||||
"weapon_fiveseven": "fiveseven",
|
||||
"weapon_cz75a": "cz75a",
|
||||
"weapon_revolver": "revolver",
|
||||
"weapon_deagle": "deagle",
|
||||
"weapon_mac10": "mac10",
|
||||
"weapon_mp9": "mp9",
|
||||
"weapon_ump45": "ump45",
|
||||
"weapon_bizon": "bizon",
|
||||
"weapon_mp7": "mp7",
|
||||
"weapon_mp5sd": "mp5sd",
|
||||
"weapon_nova": "nova",
|
||||
"weapon_mag7": "mag7",
|
||||
"weapon_sawedoff": "sawedoff",
|
||||
"weapon_xm1014": "xm1014",
|
||||
"weapon_galilar": "galilar",
|
||||
"weapon_famas": "famas",
|
||||
"weapon_ak47": "ak47",
|
||||
"weapon_m4a1": "m4a1",
|
||||
"weapon_m4a1_silencer": "m4a1_silencer",
|
||||
"weapon_aug": "aug",
|
||||
"weapon_sg556": "sg556",
|
||||
"weapon_awp": "awp",
|
||||
"weapon_scar20": "scar20",
|
||||
"weapon_g3sg1": "g3sg1",
|
||||
"weapon_negev": "negev",
|
||||
"weapon_m249": "m249",
|
||||
"m4a4": "m4a1",
|
||||
"m4a1-s": "m4a1_silencer",
|
||||
"m4a1s": "m4a1_silencer",
|
||||
"sg553": "sg556",
|
||||
"pp-bizon": "bizon",
|
||||
}
|
||||
|
||||
|
||||
def normalize_weapon_name(raw: Optional[str]) -> str:
|
||||
if not raw:
|
||||
return ""
|
||||
s = str(raw).strip().lower()
|
||||
if not s:
|
||||
return ""
|
||||
s = s.replace(" ", "").replace("\t", "").replace("\n", "")
|
||||
s = s.replace("weapon_", "weapon_")
|
||||
if s in _ALIASES:
|
||||
return _ALIASES[s]
|
||||
if s.startswith("weapon_") and s in _ALIASES:
|
||||
return _ALIASES[s]
|
||||
if s.startswith("weapon_"):
|
||||
s2 = s[len("weapon_") :]
|
||||
return _ALIASES.get(s2, s2)
|
||||
return _ALIASES.get(s, s)
|
||||
|
||||
|
||||
def get_weapon_info(raw: Optional[str]) -> Optional[WeaponInfo]:
|
||||
key = normalize_weapon_name(raw)
|
||||
if not key:
|
||||
return None
|
||||
return _WEAPON_TABLE.get(key)
|
||||
|
||||
|
||||
def get_weapon_price(raw: Optional[str]) -> Optional[int]:
|
||||
info = get_weapon_info(raw)
|
||||
return info.price if info else None
|
||||
|
||||
@@ -217,20 +217,21 @@
|
||||
{{ detail_item('Assists (场均助攻)', features['basic_avg_assisted_kill'], 'basic_avg_assisted_kill') }}
|
||||
{{ detail_item('AWP Kills (狙击击杀)', features['basic_avg_awp_kill'], 'basic_avg_awp_kill') }}
|
||||
{{ detail_item('Jumps (场均跳跃)', features['basic_avg_jump_count'], 'basic_avg_jump_count', '{:.1f}') }}
|
||||
{{ detail_item('Knife Kills (场均刀杀)', features['basic_avg_knife_kill'], 'basic_avg_knife_kill') }}
|
||||
{{ detail_item('Zeus Kills (电击枪杀)', features['basic_avg_zeus_kill'], 'basic_avg_zeus_kill') }}
|
||||
{{ detail_item('Zeus Buy% (起电击枪)', features['basic_zeus_pick_rate'], 'basic_zeus_pick_rate', '{:.1%}') }}
|
||||
|
||||
<!-- Row 3: Objective -->
|
||||
{{ detail_item('MVP (最有价值)', features['basic_avg_mvps'], 'basic_avg_mvps') }}
|
||||
{{ detail_item('Plants (下包)', features['basic_avg_plants'], 'basic_avg_plants') }}
|
||||
{{ detail_item('Defuses (拆包)', features['basic_avg_defuses'], 'basic_avg_defuses') }}
|
||||
{{ detail_item('Flash Assist (闪光助攻)', features['basic_avg_flash_assists'], 'basic_avg_flash_assists') }}
|
||||
<div class="hidden lg:block"></div> <!-- Spacer -->
|
||||
|
||||
<!-- Row 4: Opening -->
|
||||
{{ detail_item('First Kill (场均首杀)', features['basic_avg_first_kill'], 'basic_avg_first_kill') }}
|
||||
{{ detail_item('First Death (场均首死)', features['basic_avg_first_death'], 'basic_avg_first_death') }}
|
||||
{{ detail_item('FK Rate (首杀率)', features['basic_first_kill_rate'], 'basic_first_kill_rate', '{:.1%}') }}
|
||||
{{ detail_item('FD Rate (首死率)', features['basic_first_death_rate'], 'basic_first_death_rate', '{:.1%}') }}
|
||||
<div class="hidden lg:block"></div> <!-- Spacer -->
|
||||
|
||||
<!-- Row 5: Multi-Kills -->
|
||||
{{ detail_item('2K Rounds (双杀)', features['basic_avg_kill_2'], 'basic_avg_kill_2') }}
|
||||
@@ -321,6 +322,51 @@
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<h4 class="text-xs font-black text-gray-400 uppercase tracking-widest mb-4 border-b border-gray-100 dark:border-slate-700 pb-2">
|
||||
ROUND (Round Dynamics)
|
||||
</h4>
|
||||
<div class="grid grid-cols-2 md:grid-cols-3 lg:grid-cols-5 gap-y-6 gap-x-4">
|
||||
{{ detail_item('Kill Early (前30秒击杀)', features['rd_phase_kill_early_share'], 'rd_phase_kill_early_share', '{:.1%}') }}
|
||||
{{ detail_item('Kill Mid (30-60秒击杀)', features['rd_phase_kill_mid_share'], 'rd_phase_kill_mid_share', '{:.1%}') }}
|
||||
{{ detail_item('Kill Late (60秒后击杀)', features['rd_phase_kill_late_share'], 'rd_phase_kill_late_share', '{:.1%}') }}
|
||||
{{ detail_item('Death Early (前30秒死亡)', features['rd_phase_death_early_share'], 'rd_phase_death_early_share', '{:.1%}') }}
|
||||
{{ detail_item('Death Mid (30-60秒死亡)', features['rd_phase_death_mid_share'], 'rd_phase_death_mid_share', '{:.1%}') }}
|
||||
{{ detail_item('Death Late (60秒后死亡)', features['rd_phase_death_late_share'], 'rd_phase_death_late_share', '{:.1%}') }}
|
||||
|
||||
{{ detail_item('FirstDeath Win% (首死后胜率)', features['rd_firstdeath_team_first_death_win_rate'], 'rd_firstdeath_team_first_death_win_rate', '{:.1%}', count_label=features['rd_firstdeath_team_first_death_rounds']) }}
|
||||
{{ detail_item('Invalid Death% (无效死亡)', features['rd_invalid_death_rate'], 'rd_invalid_death_rate', '{:.1%}', count_label=features['rd_invalid_death_rounds']) }}
|
||||
{{ detail_item('Pressure KPR (落后≥3)', features['rd_pressure_kpr_ratio'], 'rd_pressure_kpr_ratio', '{:.2f}x') }}
|
||||
{{ detail_item('MatchPt KPR (赛点放大)', features['rd_matchpoint_kpr_ratio'], 'rd_matchpoint_kpr_ratio', '{:.2f}x', count_label=features['rd_matchpoint_rounds']) }}
|
||||
{{ detail_item('Trade Resp (10s响应)', features['rd_trade_response_10s_rate'], 'rd_trade_response_10s_rate', '{:.1%}') }}
|
||||
|
||||
{{ detail_item('Pressure Perf (Leetify)', features['rd_pressure_perf_ratio'], 'rd_pressure_perf_ratio', '{:.2f}x') }}
|
||||
{{ detail_item('MatchPt Perf (Leetify)', features['rd_matchpoint_perf_ratio'], 'rd_matchpoint_perf_ratio', '{:.2f}x') }}
|
||||
{{ detail_item('Comeback KillShare (追分)', features['rd_comeback_kill_share'], 'rd_comeback_kill_share', '{:.1%}', count_label=features['rd_comeback_rounds']) }}
|
||||
{{ detail_item('Map Stability (地图稳定)', features['map_stability_coef'], 'map_stability_coef', '{:.3f}') }}
|
||||
</div>
|
||||
|
||||
<div class="mt-6 grid grid-cols-1 lg:grid-cols-3 gap-4">
|
||||
<div class="bg-gray-50 dark:bg-slate-700/30 rounded-xl p-4 border border-gray-100 dark:border-slate-600">
|
||||
<div class="text-xs font-bold text-gray-400 uppercase tracking-wider mb-2">Phase Split</div>
|
||||
<div class="h-40">
|
||||
<canvas id="phaseChart"></canvas>
|
||||
</div>
|
||||
</div>
|
||||
<div class="bg-gray-50 dark:bg-slate-700/30 rounded-xl p-4 border border-gray-100 dark:border-slate-600">
|
||||
<div class="text-xs font-bold text-gray-400 uppercase tracking-wider mb-2">Top Weapons</div>
|
||||
<div id="weaponTopTable" class="text-sm"></div>
|
||||
</div>
|
||||
<div class="bg-gray-50 dark:bg-slate-700/30 rounded-xl p-4 border border-gray-100 dark:border-slate-600">
|
||||
<div class="text-xs font-bold text-gray-400 uppercase tracking-wider mb-2">Round Type Split</div>
|
||||
<div class="text-[11px] text-gray-500 dark:text-gray-400 mb-2">
|
||||
KPR=Kills per Round（每回合击杀） · Perf=Leetify Round Performance Score（回合表现分）
|
||||
</div>
|
||||
<div id="roundTypeTable" class="text-sm"></div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Group 5: SPECIAL (Clutch & Multi) -->
|
||||
<div>
|
||||
<h4 class="text-xs font-black text-gray-400 uppercase tracking-widest mb-4 border-b border-gray-100 dark:border-slate-700 pb-2">
|
||||
@@ -951,7 +997,176 @@ document.addEventListener('DOMContentLoaded', function() {
|
||||
}
|
||||
}
|
||||
});
|
||||
|
||||
const phaseCanvas = document.getElementById('phaseChart');
|
||||
if (phaseCanvas) {
|
||||
const ctxPhase = phaseCanvas.getContext('2d');
|
||||
new Chart(ctxPhase, {
|
||||
type: 'bar',
|
||||
data: {
|
||||
labels: ['Early', 'Mid', 'Late'],
|
||||
datasets: [
|
||||
{
|
||||
label: 'Kills',
|
||||
data: [
|
||||
{{ features.get('rd_phase_kill_early_share', 0) }},
|
||||
{{ features.get('rd_phase_kill_mid_share', 0) }},
|
||||
{{ features.get('rd_phase_kill_late_share', 0) }}
|
||||
],
|
||||
backgroundColor: 'rgba(124, 58, 237, 0.55)'
|
||||
},
|
||||
{
|
||||
label: 'Deaths',
|
||||
data: [
|
||||
{{ features.get('rd_phase_death_early_share', 0) }},
|
||||
{{ features.get('rd_phase_death_mid_share', 0) }},
|
||||
{{ features.get('rd_phase_death_late_share', 0) }}
|
||||
],
|
||||
backgroundColor: 'rgba(148, 163, 184, 0.55)'
|
||||
}
|
||||
]
|
||||
},
|
||||
options: {
|
||||
responsive: true,
|
||||
maintainAspectRatio: false,
|
||||
scales: {
|
||||
y: {
|
||||
beginAtZero: true,
|
||||
suggestedMax: 1,
|
||||
ticks: {
|
||||
callback: (v) => `${Math.round(v * 100)}%`
|
||||
}
|
||||
}
|
||||
},
|
||||
plugins: {
|
||||
legend: { display: true, position: 'bottom' },
|
||||
tooltip: {
|
||||
callbacks: {
|
||||
label: (ctx) => `${ctx.dataset.label}: ${(ctx.parsed.y * 100).toFixed(1)}%`
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
const weaponTop = JSON.parse({{ (features.get('rd_weapon_top_json', '[]') or '[]') | tojson }});
|
||||
const weaponTopEl = document.getElementById('weaponTopTable');
|
||||
if (weaponTopEl) {
|
||||
if (!Array.isArray(weaponTop) || weaponTop.length === 0) {
|
||||
weaponTopEl.innerHTML = '<div class="text-gray-500 dark:text-gray-400">No data</div>';
|
||||
} else {
|
||||
const matchesPlayed = Number({{ features.get('total_matches', 0) or 0 }}) || 0;
|
||||
const weaponRankMap = {{ (distribution.get('top_weapon_rank_map', {}) or {}) | tojson }};
|
||||
const rows = weaponTop.map(w => {
|
||||
const kills = Number(w.kills || 0);
|
||||
const hsRate = Number(w.hs_rate || 0);
|
||||
const kpm = matchesPlayed > 0 ? (kills / matchesPlayed) : kills;
|
||||
return { ...w, kills, hsRate, kpm };
|
||||
});
|
||||
|
||||
rows.sort((a, b) => b.kpm - a.kpm);
|
||||
|
||||
const catMap = { pistol: '副武器', smg: '冲锋枪', shotgun: '霰弹枪', rifle: '步枪', sniper: '狙击枪', lmg: '重机枪' };
|
||||
const fmtPct = (v) => `${(v * 100).toFixed(1)}%`;
|
||||
|
||||
weaponTopEl.innerHTML = `
|
||||
<div class="overflow-x-auto">
|
||||
<table class="w-full text-xs">
|
||||
<thead class="text-gray-500 dark:text-gray-400">
|
||||
<tr>
|
||||
<th class="text-left font-bold py-1 pr-2">武器</th>
|
||||
<th class="text-right font-bold py-1 px-2">击杀</th>
|
||||
<th class="text-right font-bold py-1 px-2">爆头率</th>
|
||||
<th class="text-left font-bold py-1 pl-2">价格/类型</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody class="text-gray-700 dark:text-gray-200">
|
||||
${rows.map((w) => {
|
||||
const category = catMap[w.category] || (w.category || '');
|
||||
const price = (w.price != null) ? `$${w.price}` : '—';
|
||||
const info = weaponRankMap[w.weapon] || {};
|
||||
const kpmRank = (info.kpm_rank != null && info.kpm_total != null) ? `#${info.kpm_rank}/${info.kpm_total}` : '—';
|
||||
const hsRank = (info.hs_rank != null && info.hs_total != null) ? `#${info.hs_rank}/${info.hs_total}` : '—';
|
||||
const killCell = `${w.kills} (场均 ${w.kpm.toFixed(2)} · ${kpmRank})`;
|
||||
const hsCell = `${fmtPct(w.hsRate)} (${hsRank})`;
|
||||
const priceType = `${price}${category ? '-' + category : ''}`;
|
||||
return `
|
||||
<tr class="border-t border-gray-100 dark:border-slate-600/40">
|
||||
<td class="py-1 pr-2 font-mono">${w.weapon}</td>
|
||||
<td class="py-1 px-2 text-right font-mono">${killCell}</td>
|
||||
<td class="py-1 px-2 text-right font-mono">${hsCell}</td>
|
||||
<td class="py-1 pl-2 font-mono">${priceType}</td>
|
||||
</tr>
|
||||
`;
|
||||
}).join('')}
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
}
|
||||
|
||||
const roundSplit = JSON.parse({{ (features.get('rd_roundtype_split_json', '{}') or '{}') | tojson }});
|
||||
const roundSplitEl = document.getElementById('roundTypeTable');
|
||||
if (roundSplitEl) {
|
||||
const keys = Object.keys(roundSplit || {});
|
||||
if (keys.length === 0) {
|
||||
roundSplitEl.innerHTML = '<div class="text-gray-500 dark:text-gray-400">No data</div>';
|
||||
} else {
|
||||
const order = ['pistol', 'reg', 'eco', 'rifle', 'fullbuy', 'overtime'];
|
||||
keys.sort((a, b) => order.indexOf(a) - order.indexOf(b));
|
||||
const rtRank = {
|
||||
pistol: { kpr: { rank: {{ (distribution.get('rd_rt_kpr_pistol') or {}).get('rank', 'null') }}, total: {{ (distribution.get('rd_rt_kpr_pistol') or {}).get('total', 'null') }} } },
|
||||
reg: { kpr: { rank: {{ (distribution.get('rd_rt_kpr_reg') or {}).get('rank', 'null') }}, total: {{ (distribution.get('rd_rt_kpr_reg') or {}).get('total', 'null') }} } },
|
||||
overtime: { kpr: { rank: {{ (distribution.get('rd_rt_kpr_overtime') or {}).get('rank', 'null') }}, total: {{ (distribution.get('rd_rt_kpr_overtime') or {}).get('total', 'null') }} },
|
||||
perf: { rank: {{ (distribution.get('rd_rt_perf_overtime') or {}).get('rank', 'null') }}, total: {{ (distribution.get('rd_rt_perf_overtime') or {}).get('total', 'null') }} } },
|
||||
eco: { perf: { rank: {{ (distribution.get('rd_rt_perf_eco') or {}).get('rank', 'null') }}, total: {{ (distribution.get('rd_rt_perf_eco') or {}).get('total', 'null') }} } },
|
||||
rifle: { perf: { rank: {{ (distribution.get('rd_rt_perf_rifle') or {}).get('rank', 'null') }}, total: {{ (distribution.get('rd_rt_perf_rifle') or {}).get('total', 'null') }} } },
|
||||
fullbuy: { perf: { rank: {{ (distribution.get('rd_rt_perf_fullbuy') or {}).get('rank', 'null') }}, total: {{ (distribution.get('rd_rt_perf_fullbuy') or {}).get('total', 'null') }} } },
|
||||
};
|
||||
const fmtRank = (r) => (r && r.rank != null && r.total != null) ? `#${r.rank}/${r.total}` : '—';
|
||||
|
||||
roundSplitEl.innerHTML = `
|
||||
<div class="overflow-x-auto">
|
||||
<table class="w-full text-xs">
|
||||
<thead class="text-gray-500 dark:text-gray-400">
|
||||
<tr>
|
||||
<th class="text-left font-bold py-1 pr-2">类型</th>
|
||||
<th class="text-right font-bold py-1 px-2">KPR</th>
|
||||
<th class="text-right font-bold py-1 px-2">队内</th>
|
||||
<th class="text-right font-bold py-1 px-2">Perf</th>
|
||||
<th class="text-right font-bold py-1 px-2">队内</th>
|
||||
<th class="text-right font-bold py-1 pl-2">样本</th>
|
||||
</tr>
|
||||
</thead>
|
||||
<tbody class="text-gray-700 dark:text-gray-200">
|
||||
${keys.map(k => {
|
||||
const v = roundSplit[k] || {};
|
||||
const kpr = (v.kpr != null) ? Number(v.kpr).toFixed(2) : '—';
|
||||
const perf = (v.perf != null) ? Number(v.perf).toFixed(2) : '—';
|
||||
const rounds = v.rounds != null ? v.rounds : 0;
|
||||
const rk = rtRank[k] || {};
|
||||
const kprRank = fmtRank(rk.kpr);
|
||||
const perfRank = fmtRank(rk.perf);
|
||||
return `
|
||||
<tr class="border-t border-gray-100 dark:border-slate-600/40">
|
||||
<td class="py-1 pr-2 font-mono">${k}</td>
|
||||
<td class="py-1 px-2 text-right font-mono">${kpr}</td>
|
||||
<td class="py-1 px-2 text-right font-mono">${kprRank}</td>
|
||||
<td class="py-1 px-2 text-right font-mono">${perf}</td>
|
||||
<td class="py-1 px-2 text-right font-mono">${perfRank}</td>
|
||||
<td class="py-1 pl-2 text-right font-mono">n=${rounds}</td>
|
||||
</tr>
|
||||
`;
|
||||
}).join('')}
|
||||
</tbody>
|
||||
</table>
|
||||
</div>
|
||||
`;
|
||||
}
|
||||
}
|
||||
});
|
||||
});
|
||||
</script>
|
||||
{% endblock %}
|
||||
{% endblock %}
|
||||
|
||||
Reference in New Issue
Block a user