initial

app.py

@@ -0,0 +1,13 @@
+import streamlit as st
+import pandas as pd
+import snowflake.connector
+
+def on_page_load():
+    st.set_page_config(layout="wide")
+on_page_load()
+
+st.markdown("<h1 style='text-align: center; color: steelblue;'>NBA</h1>", unsafe_allow_html=True)
+
+st.markdown("<h5 style='text-align: center; color: white;'>A Simple app to test your skill in building a Team based on career stats to compete with a Computer</h5>", unsafe_allow_html=True)
+
+

pages/1_home_team.py

@@ -0,0 +1,111 @@
+import streamlit as st
+import pandas as pd
+import snowflake.connector
+
+def on_page_load():
+    st.set_page_config(layout="wide")
+on_page_load()
+
+col1, col2, col3 = st.columns(3)
+
+with col2:
+    st.markdown("<h1 style='text-align: center; color: steelblue;'>Build Your Team</h1>", unsafe_allow_html=True)
+    player_add = st.text_input('Who\'re you picking?', 'James')
+    player = player_add.lower()
+st.markdown("<p style='text-align: center; color: steelblue;'>Search for a player to populate the dropdown menu then pick and save your team before searching for another player.</p>", unsafe_allow_html=True)
+search_string = 'select full_name from NBA where full_name_lower=\'{}\' or first_name_lower=\'{}\' or last_name_lower=\'{}\';'.format(player, player, player)
+
+if 'home_team' not in st.session_state:
+        st.session_state['home_team'] = []
+if 'away_team' not in st.session_state:
+        st.session_state['away_team'] = []
+if 'away_stats' not in st.session_state:
+    st.session_state['away_stats'] = []
+if 'home_team_df' not in st.session_state:
+    st.session_state['home_team_df'] = pd.DataFrame()
+if 'radio_index' not in st.session_state:
+    st.session_state['radio_index'] = 0
+
+def find_player():
+  cnx = snowflake.connector.connect(**st.secrets["snowflake"])
+  data = get_player(cnx)
+  cnx.close()
+  return data
+
+def get_player(cnx):
+  with cnx.cursor() as cur:
+    cur.execute(search_string)
+    return cur.fetchall()
+
+player_search = find_player()
+
+def find_home_team():
+    test =[]
+    cnx = snowflake.connector.connect(**st.secrets["snowflake"])
+    for i in st.session_state.home_team:
+        with cnx.cursor() as cur:
+            cur.execute('SELECT * FROM NBA WHERE FULL_NAME=\'{}\''.format(i))
+            test.append(cur.fetchall()[0])
+    cnx.close()    
+    df = pd.DataFrame(test, columns=['FULL_NAME', 'AST', 'BLK', 'DREB', 'FG3A', 'FG3M', 'FG3_PCT', 'FGA', 'FGM', 'FG_PCT', 'FTA', 'FTM', 'FT_PCT','GP', 'GS', 'MIN', 'OREB', 'PF', 'PTS', 'REB', 'STL', 'TOV', 'FIRST_NAME', 'LAST_NAME', 'FULL_NAME_LOWER', 'FIRST_NAME_LOWER', 'LAST_NAME_LOWER', 'IS_ACTIVE'])
+    st.session_state.home_team_df = df
+    return df
+
+home_team_df = find_home_team()
+
+player_search = [player[0] for player in player_search]
+if not home_team_df.empty:
+    name_list = home_team_df['FULL_NAME'].tolist()
+    player_search += name_list
+
+def save_state():
+    saved_players = home_team_df['FULL_NAME'].tolist()
+    holder = saved_players + player_selected
+    if len(player_selected) > len(saved_players):
+        for i in holder:
+            if i not in st.session_state.home_team:
+                st.session_state.home_team.append(i)
+    elif len(player_selected) < len(saved_players):
+        for i in saved_players:
+            if i not in player_selected:
+                st.session_state.home_team.remove(i)
+    st.rerun()
+
+col1, col2 = st.columns([7,1])
+with col1:
+    player_selected = st.multiselect("Search Results:", player_search, home_team_df['FULL_NAME'].tolist(), label_visibility="collapsed")
+with col2:
+    if st.button('Save Team'):
+        save_state()
+
+st.markdown("<h1 style='text-align: center; color: steelblue;'>Preview</h1>", unsafe_allow_html=True)
+   
+st.dataframe(home_team_df)
+radio_index = st.session_state.radio_index
+col1, col2, col3, col4, col5 = st.columns(5)
+with col3:
+    st.markdown("<h3 style='text-align: center; color: steelblue;'>Away Team</h3>", unsafe_allow_html=True)
+    difficulty = st.radio(
+        label="Difficulty", index=radio_index, options=['Regular','93\' Bulls', 'All-Stars', 'Dream Team'],
+        label_visibility="collapsed", )
+
+    if difficulty == 'Regular':
+        st.session_state.away_stats = [850, 400, 200, 60]
+        st.session_state.radio_index = 0       
+    elif difficulty == '93\' Bulls':
+        st.session_state.away_stats = [1050, 500, 300, 80]
+        st.session_state.radio_index = 1
+    elif difficulty == 'All-Stars':
+        st.session_state.away_stats = [1250, 600, 400, 100]
+        st.session_state.radio_index = 2
+    elif difficulty == 'Dream Team':
+        st.session_state.away_stats = [1450, 700, 500, 120]
+        st.session_state.radio_index = 3
+    else:
+        st.write("You didn't select a difficulty.")
+
+    
+  
+
+
+

pages/2_play_game.py

@@ -0,0 +1,115 @@
+import streamlit as st
+import pandas as pd
+import snowflake.connector
+import numpy as np
+import tensorflow as tf
+import random
+from tensorflow.keras.models import load_model
+
+
+def on_page_load():
+    st.set_page_config(layout="wide")
+on_page_load()
+
+stats = st.session_state.away_stats    
+teams_good = True
+winner_prediction = 0
+away_point_prediction = 0
+home_point_prediction = 0
+
+query_string = ('SELECT * FROM (select * from NBA where PTS > {}) sample (2 rows) UNION '.format(stats[0]))
+query_string += ('SELECT * FROM (select * from NBA where REB > {}) sample (1 rows) UNION '.format(stats[1]))
+query_string += ('SELECT * FROM (select * from NBA where AST > {}) sample (1 rows) UNION '.format(stats[2]))
+query_string += ('SELECT * FROM (select * from NBA where STL > {}) sample (1 rows);'.format(stats[3]))
+
+def get_away_team(cnx, query_string):
+    with cnx.cursor() as cur:
+        cur.execute(query_string)
+        players = cur.fetchall()
+        while len(players) != 5:
+            cur.execute(query_string)   
+            players = cur.fetchall()
+    return players    
+              
+def find_away_team():
+    cnx = snowflake.connector.connect(**st.secrets["snowflake"])
+
+    data = get_away_team(cnx, query_string)
+    cnx.close()
+    df = pd.DataFrame(data, columns=['FULL_NAME', 'AST', 'BLK', 'DREB', 'FG3A', 'FG3M', 'FG3_PCT', 'FGA', 'FGM', 'FG_PCT', 'FTA', 'FTM', 'FT_PCT','GP', 'GS', 'MIN', 'OREB', 'PF', 'PTS', 'REB', 'STL', 'TOV', 'FIRST_NAME', 'LAST_NAME', 'FULL_NAME_LOWER', 'FIRST_NAME_LOWER', 'LAST_NAME_LOWER', 'IS_ACTIVE'])
+    return df   
+
+if not st.session_state.home_team_df.shape[0] == 5:
+    st.markdown("<h3 style='text-align: center; color: red;'>Your Team Doesn't Have 5</h3>", unsafe_allow_html=True)
+    away_data = pd.DataFrame()
+    teams_good = False
+    winner = ''
+else:
+    away_data = find_away_team()
+    
+def analyze_stats(home_stats, away_stats):
+    home=[]
+    away=[]
+    for j in range(len(home_stats)):
+        home += home_stats[j]
+    for j in range(len(away_stats)):
+        away += away_stats[j]
+    return np.array(home).reshape(1,-1), np.array(away).reshape(1,-1), np.array(home + away).reshape(1, -1)
+
+def get_score_board(p_pred, w_score):
+    score = []
+    quarter_score = int(w_score/4)
+    score.append(quarter_score + random.randint(-7, 7))
+    score.append(quarter_score + random.randint(-3, 3))
+    score.append(quarter_score + random.randint(-8, 8))
+    score.append(w_score - (score[0] + score[1] + score[2]))
+    score.append(w_score)
+    return score
+
+if teams_good:
+    #first pass algo to determine winner
+    cols = ['PTS', 'OREB', 'DREB', 'AST', 'STL', 'BLK', 'TOV', 'FG3_PCT', 'FT_PCT', 'FGM']
+    home_stats = st.session_state.home_team_df[cols].values.tolist()
+    away_stats = away_data[cols].values.tolist()
+    home, away, winner = analyze_stats(home_stats, away_stats)
+    
+    winner_model = load_model('winner.keras')
+
+    winner_sigmoid= winner_model.predict(winner)
+    winner_prediction = np.round(winner_sigmoid)
+
+    score = []
+    winner_score = random.randint(90, 130)
+    loser_score = random.randint(80, 120)
+    while winner_score <= loser_score:
+        winner_score = random.randint(90, 130)
+        loser_score = random.randint(80, 120)
+        
+
+    if winner_prediction == 1:
+        score.append(get_score_board(winner_prediction, winner_score))
+        score.append(get_score_board(away_point_prediction, loser_score))
+        winner = 'Winner'
+    else:
+        score.append(get_score_board(winner_prediction, loser_score))
+        score.append(get_score_board(away_point_prediction, winner_score))
+        winner = 'Loser'
+
+    box_score = pd.DataFrame(score , columns=['1', '2', '3', '4', 'Final'], index=['Home Team', 'Away Team'] )
+    
+    print(f"Prediction: {winner_sigmoid}")
+
+st.markdown("<h1 style='text-align: center; color: steelblue;'>Home Team</h1>", unsafe_allow_html=True)
+st.dataframe(st.session_state.home_team_df)
+if teams_good:
+    print(f"Teams Good")
+    st.markdown(f"<h3 style='text-align: center; color: steelblue;'>{winner}</h3>", unsafe_allow_html=True)
+    col1, col2, col3 = st.columns(3)
+    with col2:
+      st.dataframe(box_score)
+st.markdown("<h1 style='text-align: center; color: steelblue;'>Away Team</h1>", unsafe_allow_html=True)
+st.dataframe(away_data)
+
+if st.button("Play New Team"):
+    print("New Team")
+

player_stats.txt

@@ -0,0 +1,151 @@
+Rk,Name,Age,G,GS,MP▼,FG,FGA,FG%,3P,3PA,3P%,2P,2PA,2P%,eFG%,FT,FTA,FT%,ORB,DRB,TRB,AST,STL,BLK,TOV,PF,PTS/G,TEAM
+1,Kyrie Irving,26,67,67,33.0,9.0,18.5,.487,2.6,6.5,.401,6.4,12.0,.533,.557,3.2,3.7,.873,1.1,3.9,5.0,6.9,1.5,0.5,2.6,2.5,23.8,Boston Celtics
+2,Jayson Tatum,20,79,79,31.1,5.9,13.1,.450,1.5,3.9,.373,4.4,9.2,.483,.506,2.5,2.9,.855,0.9,5.2,6.0,2.1,1.1,0.7,1.5,2.1,15.7,Boston Celtics
+3,Al Horford,32,68,68,29.0,5.7,10.6,.535,1.1,3.0,.360,4.6,7.6,.604,.586,1.1,1.4,.821,1.8,5.0,6.7,4.2,0.9,1.3,1.5,1.9,13.6,Boston Celtics
+4,Marcus Morris,29,75,53,27.9,5.0,11.3,.447,1.9,5.2,.375,3.1,6.1,.508,.533,1.9,2.3,.844,1.0,5.1,6.1,1.5,0.6,0.3,1.2,2.4,13.9,Boston Celtics
+5,Marcus Smart,24,80,60,27.5,3.0,7.1,.422,1.6,4.3,.364,1.4,2.8,.511,.533,1.3,1.6,.806,0.7,2.2,2.9,4.0,1.8,0.4,1.5,2.5,8.9,Boston Celtics
+1,Kawhi Leonard,27,60,60,34.0,9.3,18.8,.496,1.9,5.0,.371,7.5,13.8,.542,.546,6.1,7.1,.854,1.3,6.0,7.3,3.3,1.8,0.4,2.0,1.5,26.6,Toronto Raptors
+2,Kyle Lowry,32,65,65,34.0,4.7,11.4,.411,2.4,7.0,.347,2.3,4.4,.514,.518,2.5,3.0,.830,0.6,4.2,4.8,8.7,1.4,0.5,2.8,2.6,14.2,Toronto Raptors
+3,Pascal Siakam,24,80,79,31.9,6.5,11.8,.549,1.0,2.7,.369,5.5,9.1,.602,.591,3.0,3.8,.785,1.6,5.3,6.9,3.1,0.9,0.7,1.9,3.0,16.9,Toronto Raptors
+4,Danny Green,31,80,80,27.7,3.7,7.9,.465,2.5,5.4,.455,1.2,2.4,.487,.622,0.5,0.6,.841,0.8,3.2,4.0,1.6,0.9,0.7,0.9,2.1,10.3,Toronto Raptors
+5,Fred VanVleet,24,64,28,27.5,3.8,9.4,.410,1.8,4.6,.378,2.1,4.8,.441,.503,1.5,1.8,.843,0.3,2.3,2.6,4.8,0.9,0.3,1.3,1.7,11.0,Toronto Raptors
+1,Tim Hardaway Jr.,26,46,46,32.6,6.1,15.8,.388,2.5,7.3,.347,3.6,8.5,.424,.469,4.3,5.1,.854,0.6,2.9,3.5,2.7,0.9,0.1,1.8,2.3,19.1,New York Knicks
+2,Kevin Knox,19,75,57,28.8,4.5,12.2,.370,1.7,4.9,.343,2.8,7.3,.387,.438,2.2,3.0,.717,0.8,3.7,4.5,1.1,0.6,0.3,1.5,2.3,12.8,New York Knicks
+3,Dennis Smith Jr.,21,21,18,28.6,5.8,14.0,.413,1.1,4.0,.289,4.6,10.0,.462,.454,2.0,3.5,.568,0.7,2.1,2.8,5.4,1.3,0.4,2.6,2.2,14.7,New York Knicks
+4,Damyean Dotson,24,73,40,27.5,4.0,9.6,.415,1.7,4.7,.368,2.2,4.9,.461,.506,1.0,1.3,.745,0.5,3.1,3.6,1.8,0.8,0.1,1.0,1.8,10.7,New York Knicks
+5,Emmanuel Mudiay,22,59,42,27.2,5.6,12.5,.446,1.2,3.6,.329,4.4,9.0,.492,.493,2.4,3.2,.774,0.6,2.8,3.3,3.9,0.7,0.3,2.4,1.7,14.8,New York Knicks
+1,D'Angelo Russell,22,81,81,30.2,8.1,18.7,.434,2.9,7.8,.369,5.2,10.9,.482,.512,2.0,2.5,.780,0.7,3.2,3.9,7.0,1.2,0.2,3.1,1.7,21.1,Brooklyn Nets
+2,Joe Harris,27,76,76,30.2,4.9,9.8,.500,2.4,5.1,.474,2.5,4.8,.528,.622,1.4,1.8,.827,0.7,3.1,3.8,2.4,0.5,0.2,1.6,2.4,13.7,Brooklyn Nets
+3,Spencer Dinwiddie,25,68,4,28.1,5.4,12.2,.442,1.8,5.4,.335,3.6,6.7,.528,.517,4.2,5.2,.806,0.4,2.1,2.4,4.6,0.6,0.3,2.2,2.8,16.8,Brooklyn Nets
+4,Caris LeVert,24,40,25,26.6,5.2,12.1,.429,1.2,3.9,.312,4.0,8.2,.483,.478,2.1,3.1,.691,0.9,2.9,3.8,3.9,1.1,0.4,1.7,1.9,13.7,Brooklyn Nets
+5,Allen Crabbe,26,43,20,26.3,3.2,8.7,.367,2.3,6.0,.378,0.9,2.7,.342,.499,1.0,1.3,.732,0.4,3.1,3.4,1.1,0.5,0.3,1.1,2.4,9.6,Brooklyn Nets
+1,Tobias Harris,26,27,27,35.0,6.9,14.8,.469,1.6,5.0,.326,5.3,9.8,.542,.524,2.7,3.3,.841,1.2,6.7,7.9,2.9,0.4,0.5,1.6,2.3,18.2,Philadelphia 76ers
+2,Ben Simmons,22,79,79,34.2,6.8,12.2,.563,0.0,0.1,.000,6.8,12.1,.566,.563,3.3,5.4,.600,2.2,6.6,8.8,7.7,1.4,0.8,3.5,2.6,16.9,Philadelphia 76ers
+3,Robert Covington,28,13,13,33.8,3.8,9.0,.427,2.3,5.9,.390,1.5,3.1,.500,.556,1.3,1.8,.739,0.5,4.6,5.2,1.1,1.8,1.8,1.7,3.5,11.3,Philadelphia 76ers
+4,Joel Embiid,24,64,64,33.7,9.1,18.7,.484,1.2,4.1,.300,7.8,14.6,.535,.517,8.2,10.1,.804,2.5,11.1,13.6,3.7,0.7,1.9,3.5,3.3,27.5,Philadelphia 76ers
+5,Jimmy Butler,29,55,55,33.2,6.3,13.6,.461,0.9,2.7,.338,5.3,10.9,.491,.494,4.8,5.5,.868,1.9,3.4,5.3,4.0,1.8,0.5,1.5,1.7,18.2,Philadelphia 76ers
+1,Donovan Mitchell,26,4,4,37.8,9.8,22.0,.443,3.0,8.3,.364,6.8,13.8,.491,.511,6.0,7.0,.857,1.8,3.3,5.0,7.3,2.0,0.3,3.5,3.0,28.5,Cleveland Cavaliers
+2,Caris LeVert,28,4,4,34.3,3.3,11.3,.289,2.5,5.3,.476,0.8,6.0,.125,.400,2.5,3.5,.714,0.0,3.5,3.5,6.3,1.0,0.3,2.5,2.8,11.5,Cleveland Cavaliers
+3,Evan Mobley,21,4,4,32.8,5.8,10.0,.575,0.3,0.8,.333,5.5,9.3,.595,.588,3.3,4.0,.813,0.8,4.0,4.8,1.8,1.3,1.0,2.8,2.3,15.0,Cleveland Cavaliers
+4,Jarrett Allen,24,4,4,32.5,5.5,9.5,.579,0.0,0.0,,5.5,9.5,.579,.579,2.5,3.3,.769,5.3,6.3,11.5,1.5,0.3,1.5,1.0,2.8,13.5,Cleveland Cavaliers
+5,Cedi Osman,27,4,0,29.0,5.5,10.5,.524,2.3,4.8,.474,3.3,5.8,.565,.631,2.3,2.8,.818,0.5,2.5,3.0,2.8,0.3,0.3,0.8,3.3,15.5,Cleveland Cavaliers
+1,Victor Oladipo,26,36,36,31.9,6.9,16.3,.423,2.1,6.0,.343,4.9,10.3,.470,.486,2.9,3.9,.730,0.6,5.0,5.6,5.2,1.7,0.3,2.3,2.0,18.8,Indiana Pacers
+2,Bojan Bogdanović,29,81,81,31.8,6.4,13.0,.497,2.0,4.8,.425,4.4,8.2,.538,.575,3.0,3.8,.807,0.4,3.7,4.1,2.0,0.9,0.0,1.7,1.7,18.0,Indiana Pacers
+3,Wesley Matthews,32,23,23,31.5,3.5,9.1,.386,2.1,5.7,.369,1.4,3.5,.413,.500,1.8,2.1,.854,0.5,2.3,2.8,2.4,0.9,0.2,1.3,2.4,10.9,Indiana Pacers
+4,Thaddeus Young,30,81,81,30.7,5.5,10.4,.527,0.6,1.8,.349,4.8,8.6,.564,.557,1.1,1.7,.644,2.4,4.1,6.5,2.5,1.5,0.4,1.5,2.4,12.6,Indiana Pacers
+5,Myles Turner,22,74,74,28.6,5.1,10.5,.487,1.0,2.6,.388,4.1,7.9,.521,.536,2.0,2.7,.736,1.4,5.8,7.2,1.6,0.8,2.7,1.4,2.6,13.3,Indiana Pacers
+1,Blake Griffin,29,75,75,35.0,8.3,17.9,.462,2.5,7.0,.362,5.7,10.9,.525,.532,5.5,7.3,.753,1.3,6.2,7.5,5.4,0.7,0.4,3.4,2.7,24.5,Detroit Pistons
+2,Andre Drummond,25,79,79,33.5,7.1,13.3,.533,0.1,0.5,.132,7.0,12.8,.548,.536,3.1,5.2,.590,5.4,10.2,15.6,1.4,1.7,1.7,2.2,3.4,17.3,Detroit Pistons
+3,Reggie Bullock,27,44,44,30.8,4.1,10.0,.413,2.6,6.7,.388,1.5,3.3,.463,.542,1.3,1.5,.875,0.5,2.3,2.8,2.5,0.5,0.1,1.2,1.8,12.1,Detroit Pistons
+4,Reggie Jackson,28,82,82,27.9,5.4,12.8,.421,2.1,5.7,.369,3.3,7.0,.464,.504,2.5,2.9,.864,0.5,2.1,2.6,4.2,0.7,0.1,1.8,2.5,15.4,Detroit Pistons
+5,Wayne Ellington,31,28,26,27.3,4.1,9.8,.421,2.9,7.8,.373,1.2,2.0,.607,.570,0.9,1.2,.758,0.3,1.9,2.1,1.5,1.1,0.1,0.9,1.9,12.0,Detroit Pistons
+1,Justin Holiday,29,38,38,34.9,4.0,10.4,.383,2.6,7.1,.359,1.4,3.3,.435,.506,1.1,1.2,.891,0.5,3.9,4.4,2.2,1.8,0.6,1.2,2.1,11.6,Chicago Bulls
+2,Zach LaVine,23,63,62,34.5,8.4,18.0,.467,1.9,5.1,.374,6.5,12.9,.504,.520,5.0,6.0,.832,0.6,4.0,4.7,4.5,1.0,0.4,3.4,2.2,23.7,Chicago Bulls
+3,Otto Porter Jr.,25,15,15,32.8,6.5,13.4,.483,2.6,5.3,.488,3.9,8.1,.479,.580,1.9,2.1,.906,0.9,4.6,5.5,2.7,1.2,0.6,1.7,1.9,17.5,Chicago Bulls
+4,Lauri Markkanen,21,52,51,32.3,6.6,15.3,.430,2.3,6.4,.361,4.3,8.9,.479,.506,3.3,3.8,.872,1.4,7.6,9.0,1.4,0.7,0.6,1.6,2.3,18.7,Chicago Bulls
+5,JaKarr Sampson,25,4,0,31.8,7.3,13.5,.537,1.3,3.5,.357,6.0,10.0,.600,.583,4.3,5.3,.810,1.3,6.8,8.0,1.0,1.0,0.8,1.0,2.0,20.0,Chicago Bulls
+1,Giannis Antetokounmpo,24,72,72,32.8,10.0,17.3,.578,0.7,2.8,.256,9.3,14.5,.641,.599,6.9,9.5,.729,2.2,10.3,12.5,5.9,1.3,1.5,3.7,3.2,27.7,Milwaukee Bucks
+2,Khris Middleton,27,77,77,31.1,6.6,14.9,.441,2.3,6.2,.378,4.2,8.8,.485,.519,2.8,3.4,.837,0.6,5.3,6.0,4.3,1.0,0.1,2.3,2.2,18.3,Milwaukee Bucks
+3,Eric Bledsoe,29,78,78,29.1,6.0,12.4,.484,1.6,4.8,.329,4.4,7.6,.582,.548,2.3,3.0,.750,1.1,3.6,4.6,5.5,1.5,0.4,2.1,2.0,15.9,Milwaukee Bucks
+4,Brook Lopez,30,81,81,28.7,4.4,9.7,.452,2.3,6.3,.365,2.1,3.4,.613,.571,1.4,1.6,.842,0.4,4.5,4.9,1.2,0.6,2.2,1.0,2.3,12.5,Milwaukee Bucks
+5,Malcolm Brogdon,26,64,64,28.6,5.9,11.7,.505,1.6,3.8,.426,4.3,7.9,.544,.575,2.2,2.4,.928,1.0,3.5,4.5,3.2,0.7,0.2,1.4,1.6,15.6,Milwaukee Bucks
+1,Jimmy Butler,33,6,6,35.0,7.3,14.5,.506,1.2,2.5,.467,6.2,12.0,.514,.546,6.8,7.8,.872,2.2,4.2,6.3,5.0,1.7,0.2,1.3,1.3,22.7,Miami Heat
+2,Bam Adebayo,25,6,6,34.7,6.2,11.7,.529,0.0,0.3,.000,6.2,11.3,.544,.529,4.2,5.0,.833,2.5,5.8,8.3,2.5,1.3,1.0,4.0,2.8,16.5,Miami Heat
+3,Kyle Lowry,36,6,6,33.5,3.3,9.5,.351,2.3,6.7,.350,1.0,2.8,.353,.474,3.0,3.5,.857,0.3,3.2,3.5,5.3,1.5,0.3,1.8,3.2,12.0,Miami Heat
+4,Tyler Herro,23,6,6,32.2,6.3,14.5,.437,2.2,6.7,.325,4.2,7.8,.532,.511,2.7,3.0,.889,0.5,6.7,7.2,3.3,0.5,0.3,1.8,2.3,17.5,Miami Heat
+5,Max Strus,26,6,1,30.2,5.0,10.7,.469,2.5,6.7,.375,2.5,4.0,.625,.586,0.8,1.3,.625,1.0,4.5,5.5,1.7,0.3,0.7,1.0,1.7,13.3,Miami Heat
+1,Trae Young,20,81,81,30.9,6.5,15.5,.418,1.9,6.0,.324,4.6,9.6,.477,.480,4.2,5.1,.829,0.8,2.9,3.7,8.1,0.9,0.2,3.8,1.7,19.1,Atlanta Hawks
+2,John Collins,21,61,59,30.0,7.6,13.6,.560,0.9,2.6,.348,6.7,11.0,.609,.593,3.3,4.4,.763,3.6,6.2,9.8,2.0,0.4,0.6,2.0,3.3,19.5,Atlanta Hawks
+3,Taurean Prince,24,55,47,28.2,4.8,10.8,.441,2.2,5.7,.390,2.5,5.1,.498,.545,1.7,2.1,.819,0.4,3.2,3.6,2.1,1.0,0.3,1.8,2.6,13.5,Atlanta Hawks
+4,Kevin Huerter,20,75,59,27.3,3.7,8.8,.419,1.8,4.7,.385,1.9,4.1,.457,.522,0.5,0.7,.732,0.8,2.5,3.3,2.9,0.9,0.3,1.5,2.1,9.7,Atlanta Hawks
+5,Dewayne Dedmon,29,64,52,25.1,4.0,8.2,.492,1.3,3.4,.382,2.8,4.8,.570,.571,1.4,1.8,.814,1.6,5.9,7.5,1.4,1.1,1.1,1.3,3.3,10.8,Atlanta Hawks
+1,Kemba Walker,28,82,82,34.9,8.9,20.5,.434,3.2,8.9,.356,5.7,11.6,.494,.511,4.6,5.5,.844,0.6,3.8,4.4,5.9,1.2,0.4,2.6,1.6,25.6,Charlotte Hornets
+2,Nicolas Batum,30,75,72,31.4,3.4,7.5,.450,1.5,4.0,.389,1.8,3.5,.519,.553,1.0,1.2,.865,0.9,4.3,5.2,3.3,0.9,0.6,1.6,1.9,9.3,Charlotte Hornets
+3,Jeremy Lamb,26,79,55,28.5,5.5,12.4,.440,1.5,4.2,.348,4.0,8.2,.487,.499,2.9,3.3,.888,0.8,4.7,5.5,2.2,1.1,0.4,1.0,1.8,15.3,Charlotte Hornets
+4,Marvin Williams,32,75,75,28.4,3.7,8.7,.422,1.9,5.1,.366,1.8,3.6,.500,.529,0.9,1.1,.767,1.0,4.4,5.4,1.2,0.9,0.8,0.6,2.1,10.1,Charlotte Hornets
+5,Cody Zeller,26,49,47,25.4,3.9,7.0,.551,0.1,0.4,.273,3.8,6.6,.570,.559,2.3,2.9,.787,2.2,4.6,6.8,2.1,0.8,0.8,1.3,3.3,10.1,Charlotte Hornets
+1,Bradley Beal,25,82,82,36.9,9.3,19.6,.475,2.5,7.3,.351,6.8,12.4,.548,.540,4.4,5.5,.808,1.1,3.9,5.0,5.5,1.5,0.7,2.7,2.8,25.6,Washington Wizards
+2,John Wall,28,32,32,34.5,7.7,17.3,.444,1.6,5.3,.302,6.1,12.0,.507,.490,3.8,5.5,.697,0.5,3.2,3.6,8.7,1.5,0.9,3.8,2.2,20.7,Washington Wizards
+3,Trevor Ariza,33,43,43,34.1,4.8,11.8,.409,2.2,6.9,.322,2.6,5.0,.528,.502,2.2,2.8,.777,0.8,4.5,5.3,3.8,1.2,0.3,1.6,2.0,14.1,Washington Wizards
+4,Otto Porter Jr.,25,41,28,29.0,4.9,10.8,.457,1.6,4.3,.369,3.3,6.5,.515,.531,1.2,1.6,.766,1.0,4.7,5.6,2.0,1.6,0.5,1.0,1.9,12.6,Washington Wizards
+5,Bobby Portis,23,28,22,27.4,5.6,12.8,.440,1.7,4.3,.403,3.9,8.5,.458,.507,1.4,1.7,.809,2.3,6.4,8.6,1.5,0.9,0.4,1.6,3.0,14.3,Washington Wizards
+1,Aaron Gordon,23,78,78,33.8,6.0,13.4,.449,1.6,4.4,.349,4.5,9.0,.499,.507,2.4,3.2,.731,1.7,5.7,7.4,3.7,0.7,0.7,2.1,2.2,16.0,Orlando Magic
+2,Evan Fournier,26,81,81,31.5,5.8,13.2,.438,1.9,5.6,.340,3.9,7.6,.509,.509,1.7,2.1,.806,0.5,2.7,3.2,3.6,0.9,0.1,1.9,2.8,15.1,Orlando Magic
+3,Nikola Vučević,28,80,80,31.4,8.8,16.9,.518,1.1,2.9,.364,7.7,14.0,.549,.549,2.2,2.8,.789,2.8,9.2,12.0,3.8,1.0,1.1,2.0,2.0,20.8,Orlando Magic
+4,D.J. Augustin,31,81,81,28.0,3.9,8.4,.470,1.6,3.8,.421,2.3,4.5,.511,.566,2.2,2.6,.866,0.5,2.0,2.5,5.3,0.6,0.0,1.6,1.4,11.7,Orlando Magic
+5,Jonathan Isaac,21,75,64,26.6,3.5,8.1,.429,1.1,3.5,.323,2.3,4.6,.510,.499,1.5,1.8,.815,1.3,4.2,5.5,1.1,0.8,1.3,1.0,1.9,9.6,Orlando Magic
+1,Paul George,28,77,77,36.9,9.2,21.0,.438,3.8,9.8,.386,5.4,11.1,.484,.529,5.9,7.0,.839,1.4,6.8,8.2,4.1,2.2,0.4,2.7,2.8,28.0,Oklahoma City Thunder
+2,Russell Westbrook,30,73,73,36.0,8.6,20.2,.428,1.6,5.6,.290,7.0,14.5,.481,.468,4.1,6.2,.656,1.5,9.6,11.1,10.7,1.9,0.5,4.5,3.4,22.9,Oklahoma City Thunder
+3,Steven Adams,25,80,80,33.4,6.0,10.1,.595,0.0,0.0,.000,6.0,10.1,.596,.595,1.8,3.7,.500,4.9,4.6,9.5,1.6,1.5,1.0,1.7,2.6,13.9,Oklahoma City Thunder
+4,Jerami Grant,24,80,77,32.7,5.1,10.3,.497,1.4,3.7,.392,3.7,6.6,.555,.567,2.0,2.8,.710,1.2,4.0,5.2,1.0,0.8,1.3,0.8,2.7,13.6,Oklahoma City Thunder
+5,Dennis Schröder,25,79,14,29.3,5.8,14.0,.414,1.6,4.6,.341,4.2,9.4,.450,.470,2.4,2.9,.819,0.5,3.1,3.6,4.1,0.8,0.2,2.2,2.4,15.5,Oklahoma City Thunder
+1,Damian Lillard,28,80,80,35.5,8.5,19.2,.444,3.0,8.0,.369,5.6,11.1,.499,.522,5.9,6.4,.912,0.9,3.8,4.6,6.9,1.1,0.4,2.7,1.9,25.8,Portland Trail Blazers
+2,CJ McCollum,27,70,70,33.9,8.2,17.8,.459,2.4,6.4,.375,5.8,11.4,.506,.527,2.3,2.7,.828,0.9,3.1,4.0,3.0,0.8,0.4,1.5,2.5,21.0,Portland Trail Blazers
+3,Al-Farouq Aminu,28,81,81,28.3,3.2,7.3,.433,1.2,3.5,.343,2.0,3.9,.514,.514,1.9,2.1,.867,1.4,6.1,7.5,1.3,0.8,0.4,0.9,1.8,9.4,Portland Trail Blazers
+4,Jusuf Nurkić,24,72,72,27.4,5.8,11.5,.508,0.0,0.4,.103,5.8,11.1,.523,.510,3.9,5.1,.773,3.4,7.0,10.4,3.2,1.0,1.4,2.3,3.5,15.6,Portland Trail Blazers
+5,Rodney Hood,26,27,4,24.4,3.6,8.0,.452,1.1,3.1,.345,2.6,4.9,.519,.518,1.2,1.5,.805,0.3,1.4,1.7,1.3,0.8,0.3,0.7,1.7,9.6,Portland Trail Blazers
+1,Donovan Mitchell,22,77,77,33.7,8.6,19.9,.432,2.4,6.7,.362,6.1,13.1,.468,.493,4.1,5.1,.806,0.8,3.3,4.1,4.2,1.4,0.4,2.8,2.7,23.8,Utah Jazz
+2,Rudy Gobert,26,81,80,31.8,5.9,8.8,.669,0.0,0.0,,5.9,8.8,.669,.669,4.1,6.4,.636,3.8,9.0,12.9,2.0,0.8,2.3,1.6,2.9,15.9,Utah Jazz
+3,Joe Ingles,31,82,82,31.3,4.4,9.8,.448,2.3,5.9,.391,2.1,3.9,.533,.565,1.1,1.5,.707,0.4,3.6,4.0,5.7,1.2,0.2,2.4,2.2,12.1,Utah Jazz
+4,Ricky Rubio,28,68,67,27.9,4.3,10.7,.404,1.2,3.7,.311,3.2,7.0,.454,.458,2.9,3.4,.855,0.5,3.1,3.6,6.1,1.3,0.1,2.6,2.6,12.7,Utah Jazz
+5,Jae Crowder,28,80,11,27.1,4.0,10.0,.399,2.2,6.5,.331,1.8,3.4,.527,.508,1.8,2.5,.721,0.8,4.1,4.8,1.7,0.8,0.4,1.1,2.1,11.9,Utah Jazz
+1,Nikola Jokić,27,5,5,33.6,8.0,12.2,.656,0.6,2.0,.300,7.4,10.2,.725,.680,5.8,6.4,.906,1.6,9.2,10.8,9.4,1.6,0.2,3.0,3.6,22.4,Denver Nuggets
+2,Kentavious Caldwell-Pope,29,5,5,31.0,4.0,8.6,.465,2.6,5.2,.500,1.4,3.4,.412,.616,1.2,1.2,1.000,0.6,3.2,3.8,3.0,1.2,0.2,1.2,2.6,11.8,Denver Nuggets
+3,Aaron Gordon,27,5,5,29.2,6.4,12.4,.516,0.2,3.2,.063,6.2,9.2,.674,.524,2.0,3.2,.625,3.0,4.6,7.6,2.6,0.2,1.0,1.4,1.4,15.0,Denver Nuggets
+4,Michael Porter Jr.,24,4,4,29.0,6.5,12.8,.510,4.0,8.0,.500,2.5,4.8,.526,.667,1.0,1.3,.800,1.3,4.5,5.8,1.3,0.8,0.5,2.0,4.5,18.0,Denver Nuggets
+5,Bruce Brown,26,5,2,27.2,4.6,8.6,.535,1.6,3.2,.500,3.0,5.4,.556,.628,0.6,1.2,.500,1.0,1.8,2.8,3.4,0.8,0.4,1.2,1.8,11.4,Denver Nuggets
+1,Jimmy Butler,29,10,10,36.1,7.4,15.7,.471,1.7,4.5,.378,5.7,11.2,.509,.525,4.8,6.1,.787,1.6,3.6,5.2,4.3,2.4,1.0,1.4,1.8,21.3,Minnesota Timberwolves
+2,Andrew Wiggins,23,73,73,34.8,6.8,16.6,.412,1.6,4.8,.339,5.2,11.8,.441,.461,2.8,4.1,.699,1.1,3.7,4.8,2.5,1.0,0.7,1.9,2.1,18.1,Minnesota Timberwolves
+3,Robert Covington,28,22,22,34.7,4.8,11.1,.433,2.5,6.7,.372,2.3,4.4,.526,.545,2.3,3.0,.773,1.0,4.8,5.7,1.5,2.3,1.1,1.1,3.7,14.5,Minnesota Timberwolves
+4,Karl-Anthony Towns,23,77,77,33.1,8.8,17.1,.518,1.8,4.6,.400,7.0,12.5,.562,.572,4.9,5.8,.836,3.4,9.0,12.4,3.4,0.9,1.6,3.1,3.8,24.4,Minnesota Timberwolves
+5,Jeff Teague,30,42,41,30.1,4.2,9.9,.423,0.8,2.5,.333,3.4,7.4,.453,.465,2.9,3.6,.804,0.4,2.1,2.5,8.2,1.0,0.4,2.3,2.1,12.1,Minnesota Timberwolves
+1,Kevin Durant,30,78,78,34.6,9.2,17.7,.521,1.8,5.0,.353,7.5,12.8,.587,.571,5.7,6.5,.885,0.4,5.9,6.4,5.9,0.7,1.1,2.9,2.0,26.0,Golden State Warriors
+2,Klay Thompson,28,78,78,34.0,8.4,18.0,.467,3.1,7.7,.402,5.3,10.3,.516,.553,1.7,2.0,.816,0.5,3.4,3.8,2.4,1.1,0.6,1.5,2.0,21.5,Golden State Warriors
+3,Stephen Curry,30,69,69,33.8,9.2,19.4,.472,5.1,11.7,.437,4.0,7.7,.525,.604,3.8,4.2,.916,0.7,4.7,5.3,5.2,1.3,0.4,2.8,2.4,27.3,Golden State Warriors
+4,Draymond Green,28,66,66,31.3,2.8,6.4,.445,0.7,2.5,.285,2.1,3.9,.549,.501,1.0,1.4,.692,0.9,6.4,7.3,6.9,1.4,1.1,2.6,3.0,7.4,Golden State Warriors
+5,DeMarcus Cousins,28,30,30,25.7,5.9,12.4,.480,0.9,3.2,.274,5.1,9.2,.551,.515,3.5,4.8,.736,1.4,6.8,8.2,3.6,1.3,1.5,2.4,3.6,16.3,Golden State Warriors
+1,Tobias Harris,26,55,55,34.6,7.7,15.5,.496,2.0,4.7,.434,5.7,10.9,.523,.561,3.5,4.0,.877,0.7,7.2,7.9,2.7,0.7,0.4,2.0,2.2,20.9,Los Angeles Clippers
+2,Danilo Gallinari,30,68,68,30.3,6.0,13.0,.463,2.4,5.5,.433,3.6,7.5,.484,.554,5.4,6.0,.904,0.8,5.3,6.1,2.6,0.7,0.3,1.5,1.9,19.8,Los Angeles Clippers
+3,Avery Bradley,28,49,49,29.9,3.3,8.6,.383,1.2,3.5,.337,2.1,5.1,.415,.452,0.4,0.5,.800,0.7,2.0,2.7,2.0,0.6,0.3,1.2,2.7,8.2,Los Angeles Clippers
+4,Landry Shamet,21,25,23,27.8,3.5,8.4,.414,2.7,6.0,.450,0.8,2.4,.322,.576,1.2,1.6,.795,0.3,2.0,2.2,2.3,0.5,0.1,0.8,2.0,10.9,Los Angeles Clippers
+5,Patrick Beverley,30,78,49,27.4,2.5,6.1,.407,1.4,3.6,.397,1.1,2.5,.421,.524,1.2,1.6,.780,1.0,4.0,5.0,3.8,0.9,0.6,1.1,3.4,7.6,Los Angeles Clippers
+1,Harrison Barnes,26,28,28,33.9,5.0,11.1,.455,1.9,4.6,.408,3.1,6.4,.489,.540,2.3,2.9,.800,0.8,4.8,5.5,1.9,0.6,0.1,1.1,1.5,14.3,Sacramento Kings
+2,Buddy Hield,26,82,82,31.9,7.6,16.6,.458,3.4,7.9,.427,4.2,8.6,.487,.560,2.1,2.4,.886,1.3,3.7,5.0,2.5,0.7,0.4,1.8,2.5,20.7,Sacramento Kings
+3,De'Aaron Fox,21,81,81,31.4,6.2,13.6,.458,1.1,2.9,.371,5.2,10.7,.482,.497,3.7,5.1,.727,0.5,3.2,3.8,7.3,1.6,0.6,2.8,2.5,17.3,Sacramento Kings
+4,Bogdan Bogdanović,26,70,17,27.8,5.2,12.3,.418,1.9,5.3,.360,3.2,7.0,.462,.496,1.9,2.3,.827,0.6,2.9,3.5,3.8,1.0,0.2,1.7,2.0,14.1,Sacramento Kings
+5,Willie Cauley-Stein,25,81,81,27.3,5.1,9.1,.556,0.0,0.0,.500,5.1,9.1,.556,.557,1.7,3.1,.551,2.2,6.1,8.4,2.4,1.2,0.6,1.0,2.8,11.9,Sacramento Kings
+1,Devin Booker,22,64,64,35.0,9.2,19.6,.467,2.1,6.5,.326,7.0,13.1,.536,.521,6.1,7.1,.866,0.6,3.5,4.1,6.8,0.9,0.2,4.1,3.1,26.6,Phoenix Suns
+2,Trevor Ariza,33,26,26,34.0,3.3,8.7,.379,1.9,5.3,.360,1.4,3.4,.409,.489,1.4,1.7,.837,0.6,5.0,5.6,3.3,1.5,0.3,1.5,1.7,9.9,Phoenix Suns
+3,T.J. Warren,25,43,36,31.6,6.9,14.2,.486,1.8,4.2,.428,5.1,10.0,.510,.549,2.3,2.9,.815,0.7,3.3,4.0,1.5,1.2,0.7,1.2,2.8,18.0,Phoenix Suns
+4,Tyler Johnson,26,13,12,31.2,3.5,9.6,.368,1.4,4.3,.321,2.2,5.3,.406,.440,2.6,3.0,.872,1.2,2.8,4.0,4.2,1.1,0.5,1.1,1.9,11.1,Phoenix Suns
+5,Deandre Ayton,20,71,70,30.7,7.2,12.3,.585,0.0,0.1,.000,7.2,12.2,.588,.585,2.0,2.7,.746,3.1,7.1,10.3,1.8,0.9,0.9,1.8,2.9,16.3,Phoenix Suns
+1,LeBron James,34,55,55,35.2,10.1,19.9,.510,2.0,5.9,.339,8.1,14.0,.582,.560,5.1,7.6,.665,1.0,7.4,8.5,8.3,1.3,0.6,3.6,1.7,27.4,Los Angeles Lakers
+2,Brandon Ingram,21,52,52,33.8,7.0,14.0,.497,0.6,1.8,.330,6.4,12.2,.521,.518,3.8,5.6,.675,0.8,4.3,5.1,3.0,0.5,0.6,2.5,2.9,18.3,Los Angeles Lakers
+3,Kyle Kuzma,23,70,68,33.1,7.1,15.5,.456,1.8,6.0,.303,5.3,9.5,.553,.515,2.7,3.6,.752,0.9,4.6,5.5,2.5,0.6,0.4,1.9,2.4,18.7,Los Angeles Lakers
+4,Lonzo Ball,21,47,45,30.3,3.9,9.7,.406,1.6,4.9,.329,2.3,4.9,.482,.488,0.4,1.0,.417,1.1,4.2,5.3,5.4,1.5,0.4,2.2,2.4,9.9,Los Angeles Lakers
+5,Rajon Rondo,32,46,29,29.8,3.8,9.4,.405,1.1,3.1,.359,2.7,6.3,.428,.464,0.5,0.8,.639,0.7,4.5,5.3,8.0,1.2,0.2,2.8,2.2,9.2,Los Angeles Lakers
+1,DeMar DeRozan,29,77,77,34.9,8.2,17.1,.481,0.1,0.6,.156,8.1,16.5,.492,.483,4.8,5.7,.830,0.7,5.3,6.0,6.2,1.1,0.5,2.6,2.3,21.2,San Antonio Spurs
+2,LaMarcus Aldridge,33,81,81,33.2,8.4,16.3,.519,0.1,0.5,.238,8.3,15.8,.528,.522,4.3,5.1,.847,3.1,6.1,9.2,2.4,0.5,1.3,1.8,2.2,21.3,San Antonio Spurs
+3,Bryn Forbes,25,82,81,28.0,4.4,9.6,.456,2.1,5.0,.426,2.3,4.6,.489,.568,0.8,1.0,.885,0.2,2.7,2.9,2.1,0.5,0.0,1.0,1.9,11.8,San Antonio Spurs
+4,Rudy Gay,32,69,51,26.7,5.4,10.8,.504,1.1,2.7,.402,4.4,8.1,.537,.554,1.7,2.1,.816,0.9,5.9,6.8,2.6,0.8,0.5,1.7,2.3,13.7,San Antonio Spurs
+5,Derrick White,24,67,55,25.8,3.9,8.1,.479,0.7,2.1,.338,3.2,6.0,.529,.523,1.4,1.8,.772,0.5,3.2,3.7,3.9,1.0,0.7,1.4,2.2,9.9,San Antonio Spurs
+1,Harrison Barnes,26,49,49,32.3,5.9,14.6,.404,2.5,6.3,.389,3.4,8.3,.416,.489,3.4,4.0,.833,0.7,3.5,4.2,1.3,0.7,0.2,1.4,1.6,17.7,Dallas Mavericks
+2,Luka Dončić,19,72,72,32.2,7.0,16.5,.427,2.3,7.1,.327,4.7,9.3,.503,.497,4.8,6.7,.713,1.2,6.6,7.8,6.0,1.1,0.3,3.4,1.9,21.2,Dallas Mavericks
+3,DeAndre Jordan,30,50,50,31.1,4.2,6.5,.644,0.0,0.0,,4.2,6.5,.644,.644,2.7,4.0,.682,3.2,10.5,13.7,2.0,0.7,1.1,2.2,2.5,11.0,Dallas Mavericks
+4,Wesley Matthews,32,44,44,29.8,4.4,10.7,.414,2.3,6.0,.380,2.1,4.7,.456,.520,2.0,2.5,.791,0.5,1.9,2.3,2.3,0.8,0.3,1.3,2.3,13.1,Dallas Mavericks
+5,Tim Hardaway Jr.,26,19,17,29.4,5.7,14.1,.404,2.4,7.4,.321,3.3,6.7,.496,.489,1.7,2.3,.767,0.4,2.8,3.2,1.9,0.6,0.1,1.3,1.8,15.5,Dallas Mavericks
+1,Marc Gasol,34,53,53,33.7,5.7,12.9,.444,1.4,4.2,.344,4.3,8.7,.491,.499,2.9,3.8,.756,1.1,7.5,8.6,4.7,1.1,1.2,2.2,2.8,15.7,Memphis Grizzlies
+2,Mike Conley,31,70,70,33.5,7.0,16.0,.438,2.2,6.1,.364,4.8,9.9,.483,.507,4.9,5.8,.845,0.6,2.8,3.4,6.4,1.3,0.3,1.9,1.8,21.1,Memphis Grizzlies
+3,Avery Bradley,28,14,14,31.6,6.2,13.4,.463,2.0,5.2,.384,4.2,8.2,.513,.537,1.6,1.8,.920,0.6,2.6,3.1,4.0,1.0,0.0,2.0,2.4,16.1,Memphis Grizzlies
+4,Garrett Temple,32,49,49,31.2,3.4,7.9,.429,1.5,4.3,.352,1.9,3.6,.520,.525,1.2,1.6,.750,0.4,2.7,3.1,1.4,1.0,0.5,1.1,2.7,9.4,Memphis Grizzlies
+5,Delon Wright,26,26,11,30.8,4.4,10.2,.434,0.8,3.0,.256,3.7,7.2,.508,.472,2.5,3.4,.742,1.1,4.3,5.4,5.3,1.6,0.6,1.5,1.9,12.2,Memphis Grizzlies
+1,James Harden,29,78,78,36.8,10.8,24.5,.442,4.8,13.2,.368,6.0,11.3,.528,.541,9.7,11.0,.879,0.8,5.8,6.6,7.5,2.0,0.7,5.0,3.1,36.1,Houston Rockets
+2,P.J. Tucker,33,82,82,34.2,2.5,6.4,.396,1.8,4.7,.377,0.7,1.7,.449,.535,0.5,0.7,.695,1.5,4.4,5.8,1.2,1.6,0.5,0.8,3.1,7.3,Houston Rockets
+3,Clint Capela,24,67,67,33.6,7.1,10.9,.648,0.0,0.0,,7.1,10.9,.648,.648,2.5,3.9,.636,4.4,8.2,12.7,1.4,0.7,1.5,1.4,2.5,16.6,Houston Rockets
+4,Chris Paul,33,58,58,32.0,5.2,12.4,.419,2.2,6.1,.358,3.0,6.3,.479,.508,3.0,3.5,.862,0.6,3.9,4.6,8.2,2.0,0.3,2.6,2.5,15.6,Houston Rockets
+5,Eric Gordon,30,68,53,31.7,5.6,13.8,.409,3.2,8.8,.360,2.5,5.0,.497,.525,1.8,2.2,.783,0.3,1.9,2.2,1.9,0.6,0.4,1.3,2.1,16.2,Houston Rockets
+1,Jrue Holiday,28,67,67,35.9,8.2,17.3,.472,1.8,5.4,.325,6.4,11.9,.539,.523,3.1,4.0,.768,1.1,3.9,5.0,7.7,1.6,0.8,3.1,2.2,21.2,New Orleans Pelicans
+2,Anthony Davis,25,56,56,33.0,9.5,18.3,.517,0.9,2.6,.331,8.6,15.7,.547,.540,6.1,7.7,.794,3.1,8.9,12.0,3.9,1.6,2.4,2.0,2.4,25.9,New Orleans Pelicans
+3,Julius Randle,24,73,49,30.6,7.8,14.9,.524,0.9,2.7,.344,6.9,12.2,.564,.555,4.9,6.7,.731,2.2,6.5,8.7,3.1,0.7,0.6,2.8,3.4,21.4,New Orleans Pelicans
+4,Elfrid Payton,24,42,42,29.8,4.3,9.8,.434,0.8,2.5,.314,3.5,7.3,.476,.475,1.3,1.8,.743,1.2,4.1,5.2,7.6,1.0,0.4,2.7,1.9,10.6,New Orleans Pelicans
+5,Nikola Mirotić,27,32,22,28.9,5.7,12.7,.447,2.7,7.2,.368,3.0,5.5,.551,.552,2.7,3.2,.842,1.4,6.8,8.3,1.1,0.7,0.8,1.2,2.7,16.7,New Orleans Pelicans

player_stats_2018.csv

@@ -0,0 +1,151 @@
+Rk,Name,Age,G,GS,MP,FG,FGA,FG%,3P,3PA,3P%,2P,2PA,2P%,eFG%,FT,FTA,FT%,ORB,DRB,TRB,AST,STL,BLK,TOV,PF,PTS/G,TEAM
+1,Kyrie Irving,26,67,67,33.0,9.0,18.5,.487,2.6,6.5,.401,6.4,12.0,.533,.557,3.2,3.7,.873,1.1,3.9,5.0,6.9,1.5,0.5,2.6,2.5,23.8,Boston Celtics
+2,Jayson Tatum,20,79,79,31.1,5.9,13.1,.450,1.5,3.9,.373,4.4,9.2,.483,.506,2.5,2.9,.855,0.9,5.2,6.0,2.1,1.1,0.7,1.5,2.1,15.7,Boston Celtics
+3,Al Horford,32,68,68,29.0,5.7,10.6,.535,1.1,3.0,.360,4.6,7.6,.604,.586,1.1,1.4,.821,1.8,5.0,6.7,4.2,0.9,1.3,1.5,1.9,13.6,Boston Celtics
+4,Marcus Morris,29,75,53,27.9,5.0,11.3,.447,1.9,5.2,.375,3.1,6.1,.508,.533,1.9,2.3,.844,1.0,5.1,6.1,1.5,0.6,0.3,1.2,2.4,13.9,Boston Celtics
+5,Marcus Smart,24,80,60,27.5,3.0,7.1,.422,1.6,4.3,.364,1.4,2.8,.511,.533,1.3,1.6,.806,0.7,2.2,2.9,4.0,1.8,0.4,1.5,2.5,8.9,Boston Celtics
+1,Kawhi Leonard,27,60,60,34.0,9.3,18.8,.496,1.9,5.0,.371,7.5,13.8,.542,.546,6.1,7.1,.854,1.3,6.0,7.3,3.3,1.8,0.4,2.0,1.5,26.6,Toronto Raptors
+2,Kyle Lowry,32,65,65,34.0,4.7,11.4,.411,2.4,7.0,.347,2.3,4.4,.514,.518,2.5,3.0,.830,0.6,4.2,4.8,8.7,1.4,0.5,2.8,2.6,14.2,Toronto Raptors
+3,Pascal Siakam,24,80,79,31.9,6.5,11.8,.549,1.0,2.7,.369,5.5,9.1,.602,.591,3.0,3.8,.785,1.6,5.3,6.9,3.1,0.9,0.7,1.9,3.0,16.9,Toronto Raptors
+4,Danny Green,31,80,80,27.7,3.7,7.9,.465,2.5,5.4,.455,1.2,2.4,.487,.622,0.5,0.6,.841,0.8,3.2,4.0,1.6,0.9,0.7,0.9,2.1,10.3,Toronto Raptors
+5,Fred VanVleet,24,64,28,27.5,3.8,9.4,.410,1.8,4.6,.378,2.1,4.8,.441,.503,1.5,1.8,.843,0.3,2.3,2.6,4.8,0.9,0.3,1.3,1.7,11.0,Toronto Raptors
+1,Tim Hardaway Jr.,26,46,46,32.6,6.1,15.8,.388,2.5,7.3,.347,3.6,8.5,.424,.469,4.3,5.1,.854,0.6,2.9,3.5,2.7,0.9,0.1,1.8,2.3,19.1,New York Knicks
+2,Kevin Knox,19,75,57,28.8,4.5,12.2,.370,1.7,4.9,.343,2.8,7.3,.387,.438,2.2,3.0,.717,0.8,3.7,4.5,1.1,0.6,0.3,1.5,2.3,12.8,New York Knicks
+3,Dennis Smith Jr.,21,21,18,28.6,5.8,14.0,.413,1.1,4.0,.289,4.6,10.0,.462,.454,2.0,3.5,.568,0.7,2.1,2.8,5.4,1.3,0.4,2.6,2.2,14.7,New York Knicks
+4,Damyean Dotson,24,73,40,27.5,4.0,9.6,.415,1.7,4.7,.368,2.2,4.9,.461,.506,1.0,1.3,.745,0.5,3.1,3.6,1.8,0.8,0.1,1.0,1.8,10.7,New York Knicks
+5,Emmanuel Mudiay,22,59,42,27.2,5.6,12.5,.446,1.2,3.6,.329,4.4,9.0,.492,.493,2.4,3.2,.774,0.6,2.8,3.3,3.9,0.7,0.3,2.4,1.7,14.8,New York Knicks
+1,D'Angelo Russell,22,81,81,30.2,8.1,18.7,.434,2.9,7.8,.369,5.2,10.9,.482,.512,2.0,2.5,.780,0.7,3.2,3.9,7.0,1.2,0.2,3.1,1.7,21.1,Brooklyn Nets
+2,Joe Harris,27,76,76,30.2,4.9,9.8,.500,2.4,5.1,.474,2.5,4.8,.528,.622,1.4,1.8,.827,0.7,3.1,3.8,2.4,0.5,0.2,1.6,2.4,13.7,Brooklyn Nets
+3,Spencer Dinwiddie,25,68,4,28.1,5.4,12.2,.442,1.8,5.4,.335,3.6,6.7,.528,.517,4.2,5.2,.806,0.4,2.1,2.4,4.6,0.6,0.3,2.2,2.8,16.8,Brooklyn Nets
+4,Caris LeVert,24,40,25,26.6,5.2,12.1,.429,1.2,3.9,.312,4.0,8.2,.483,.478,2.1,3.1,.691,0.9,2.9,3.8,3.9,1.1,0.4,1.7,1.9,13.7,Brooklyn Nets
+5,Allen Crabbe,26,43,20,26.3,3.2,8.7,.367,2.3,6.0,.378,0.9,2.7,.342,.499,1.0,1.3,.732,0.4,3.1,3.4,1.1,0.5,0.3,1.1,2.4,9.6,Brooklyn Nets
+1,Tobias Harris,26,27,27,35.0,6.9,14.8,.469,1.6,5.0,.326,5.3,9.8,.542,.524,2.7,3.3,.841,1.2,6.7,7.9,2.9,0.4,0.5,1.6,2.3,18.2,Philadelphia 76ers
+2,Ben Simmons,22,79,79,34.2,6.8,12.2,.563,0.0,0.1,.000,6.8,12.1,.566,.563,3.3,5.4,.600,2.2,6.6,8.8,7.7,1.4,0.8,3.5,2.6,16.9,Philadelphia 76ers
+3,Robert Covington,28,13,13,33.8,3.8,9.0,.427,2.3,5.9,.390,1.5,3.1,.500,.556,1.3,1.8,.739,0.5,4.6,5.2,1.1,1.8,1.8,1.7,3.5,11.3,Philadelphia 76ers
+4,Joel Embiid,24,64,64,33.7,9.1,18.7,.484,1.2,4.1,.300,7.8,14.6,.535,.517,8.2,10.1,.804,2.5,11.1,13.6,3.7,0.7,1.9,3.5,3.3,27.5,Philadelphia 76ers
+5,Jimmy Butler,29,55,55,33.2,6.3,13.6,.461,0.9,2.7,.338,5.3,10.9,.491,.494,4.8,5.5,.868,1.9,3.4,5.3,4.0,1.8,0.5,1.5,1.7,18.2,Philadelphia 76ers
+1,Donovan Mitchell,26,4,4,37.8,9.8,22.0,.443,3.0,8.3,.364,6.8,13.8,.491,.511,6.0,7.0,.857,1.8,3.3,5.0,7.3,2.0,0.3,3.5,3.0,28.5,Cleveland Cavaliers
+2,Caris LeVert,28,4,4,34.3,3.3,11.3,.289,2.5,5.3,.476,0.8,6.0,.125,.400,2.5,3.5,.714,0.0,3.5,3.5,6.3,1.0,0.3,2.5,2.8,11.5,Cleveland Cavaliers
+3,Evan Mobley,21,4,4,32.8,5.8,10.0,.575,0.3,0.8,.333,5.5,9.3,.595,.588,3.3,4.0,.813,0.8,4.0,4.8,1.8,1.3,1.0,2.8,2.3,15.0,Cleveland Cavaliers
+4,Jarrett Allen,24,4,4,32.5,5.5,9.5,.579,0.0,0.0,,5.5,9.5,.579,.579,2.5,3.3,.769,5.3,6.3,11.5,1.5,0.3,1.5,1.0,2.8,13.5,Cleveland Cavaliers
+5,Cedi Osman,27,4,0,29.0,5.5,10.5,.524,2.3,4.8,.474,3.3,5.8,.565,.631,2.3,2.8,.818,0.5,2.5,3.0,2.8,0.3,0.3,0.8,3.3,15.5,Cleveland Cavaliers
+1,Victor Oladipo,26,36,36,31.9,6.9,16.3,.423,2.1,6.0,.343,4.9,10.3,.470,.486,2.9,3.9,.730,0.6,5.0,5.6,5.2,1.7,0.3,2.3,2.0,18.8,Indiana Pacers
+2,Bojan Bogdanović,29,81,81,31.8,6.4,13.0,.497,2.0,4.8,.425,4.4,8.2,.538,.575,3.0,3.8,.807,0.4,3.7,4.1,2.0,0.9,0.0,1.7,1.7,18.0,Indiana Pacers
+3,Wesley Matthews,32,23,23,31.5,3.5,9.1,.386,2.1,5.7,.369,1.4,3.5,.413,.500,1.8,2.1,.854,0.5,2.3,2.8,2.4,0.9,0.2,1.3,2.4,10.9,Indiana Pacers
+4,Thaddeus Young,30,81,81,30.7,5.5,10.4,.527,0.6,1.8,.349,4.8,8.6,.564,.557,1.1,1.7,.644,2.4,4.1,6.5,2.5,1.5,0.4,1.5,2.4,12.6,Indiana Pacers
+5,Myles Turner,22,74,74,28.6,5.1,10.5,.487,1.0,2.6,.388,4.1,7.9,.521,.536,2.0,2.7,.736,1.4,5.8,7.2,1.6,0.8,2.7,1.4,2.6,13.3,Indiana Pacers
+1,Blake Griffin,29,75,75,35.0,8.3,17.9,.462,2.5,7.0,.362,5.7,10.9,.525,.532,5.5,7.3,.753,1.3,6.2,7.5,5.4,0.7,0.4,3.4,2.7,24.5,Detroit Pistons
+2,Andre Drummond,25,79,79,33.5,7.1,13.3,.533,0.1,0.5,.132,7.0,12.8,.548,.536,3.1,5.2,.590,5.4,10.2,15.6,1.4,1.7,1.7,2.2,3.4,17.3,Detroit Pistons
+3,Reggie Bullock,27,44,44,30.8,4.1,10.0,.413,2.6,6.7,.388,1.5,3.3,.463,.542,1.3,1.5,.875,0.5,2.3,2.8,2.5,0.5,0.1,1.2,1.8,12.1,Detroit Pistons
+4,Reggie Jackson,28,82,82,27.9,5.4,12.8,.421,2.1,5.7,.369,3.3,7.0,.464,.504,2.5,2.9,.864,0.5,2.1,2.6,4.2,0.7,0.1,1.8,2.5,15.4,Detroit Pistons
+5,Wayne Ellington,31,28,26,27.3,4.1,9.8,.421,2.9,7.8,.373,1.2,2.0,.607,.570,0.9,1.2,.758,0.3,1.9,2.1,1.5,1.1,0.1,0.9,1.9,12.0,Detroit Pistons
+1,Justin Holiday,29,38,38,34.9,4.0,10.4,.383,2.6,7.1,.359,1.4,3.3,.435,.506,1.1,1.2,.891,0.5,3.9,4.4,2.2,1.8,0.6,1.2,2.1,11.6,Chicago Bulls
+2,Zach LaVine,23,63,62,34.5,8.4,18.0,.467,1.9,5.1,.374,6.5,12.9,.504,.520,5.0,6.0,.832,0.6,4.0,4.7,4.5,1.0,0.4,3.4,2.2,23.7,Chicago Bulls
+3,Otto Porter Jr.,25,15,15,32.8,6.5,13.4,.483,2.6,5.3,.488,3.9,8.1,.479,.580,1.9,2.1,.906,0.9,4.6,5.5,2.7,1.2,0.6,1.7,1.9,17.5,Chicago Bulls
+4,Lauri Markkanen,21,52,51,32.3,6.6,15.3,.430,2.3,6.4,.361,4.3,8.9,.479,.506,3.3,3.8,.872,1.4,7.6,9.0,1.4,0.7,0.6,1.6,2.3,18.7,Chicago Bulls
+5,JaKarr Sampson,25,4,0,31.8,7.3,13.5,.537,1.3,3.5,.357,6.0,10.0,.600,.583,4.3,5.3,.810,1.3,6.8,8.0,1.0,1.0,0.8,1.0,2.0,20.0,Chicago Bulls
+1,Giannis Antetokounmpo,24,72,72,32.8,10.0,17.3,.578,0.7,2.8,.256,9.3,14.5,.641,.599,6.9,9.5,.729,2.2,10.3,12.5,5.9,1.3,1.5,3.7,3.2,27.7,Milwaukee Bucks
+2,Khris Middleton,27,77,77,31.1,6.6,14.9,.441,2.3,6.2,.378,4.2,8.8,.485,.519,2.8,3.4,.837,0.6,5.3,6.0,4.3,1.0,0.1,2.3,2.2,18.3,Milwaukee Bucks
+3,Eric Bledsoe,29,78,78,29.1,6.0,12.4,.484,1.6,4.8,.329,4.4,7.6,.582,.548,2.3,3.0,.750,1.1,3.6,4.6,5.5,1.5,0.4,2.1,2.0,15.9,Milwaukee Bucks
+4,Brook Lopez,30,81,81,28.7,4.4,9.7,.452,2.3,6.3,.365,2.1,3.4,.613,.571,1.4,1.6,.842,0.4,4.5,4.9,1.2,0.6,2.2,1.0,2.3,12.5,Milwaukee Bucks
+5,Malcolm Brogdon,26,64,64,28.6,5.9,11.7,.505,1.6,3.8,.426,4.3,7.9,.544,.575,2.2,2.4,.928,1.0,3.5,4.5,3.2,0.7,0.2,1.4,1.6,15.6,Milwaukee Bucks
+1,Jimmy Butler,33,6,6,35.0,7.3,14.5,.506,1.2,2.5,.467,6.2,12.0,.514,.546,6.8,7.8,.872,2.2,4.2,6.3,5.0,1.7,0.2,1.3,1.3,22.7,Miami Heat
+2,Bam Adebayo,25,6,6,34.7,6.2,11.7,.529,0.0,0.3,.000,6.2,11.3,.544,.529,4.2,5.0,.833,2.5,5.8,8.3,2.5,1.3,1.0,4.0,2.8,16.5,Miami Heat
+3,Kyle Lowry,36,6,6,33.5,3.3,9.5,.351,2.3,6.7,.350,1.0,2.8,.353,.474,3.0,3.5,.857,0.3,3.2,3.5,5.3,1.5,0.3,1.8,3.2,12.0,Miami Heat
+4,Tyler Herro,23,6,6,32.2,6.3,14.5,.437,2.2,6.7,.325,4.2,7.8,.532,.511,2.7,3.0,.889,0.5,6.7,7.2,3.3,0.5,0.3,1.8,2.3,17.5,Miami Heat
+5,Max Strus,26,6,1,30.2,5.0,10.7,.469,2.5,6.7,.375,2.5,4.0,.625,.586,0.8,1.3,.625,1.0,4.5,5.5,1.7,0.3,0.7,1.0,1.7,13.3,Miami Heat
+1,Trae Young,20,81,81,30.9,6.5,15.5,.418,1.9,6.0,.324,4.6,9.6,.477,.480,4.2,5.1,.829,0.8,2.9,3.7,8.1,0.9,0.2,3.8,1.7,19.1,Atlanta Hawks
+2,John Collins,21,61,59,30.0,7.6,13.6,.560,0.9,2.6,.348,6.7,11.0,.609,.593,3.3,4.4,.763,3.6,6.2,9.8,2.0,0.4,0.6,2.0,3.3,19.5,Atlanta Hawks
+3,Taurean Prince,24,55,47,28.2,4.8,10.8,.441,2.2,5.7,.390,2.5,5.1,.498,.545,1.7,2.1,.819,0.4,3.2,3.6,2.1,1.0,0.3,1.8,2.6,13.5,Atlanta Hawks
+4,Kevin Huerter,20,75,59,27.3,3.7,8.8,.419,1.8,4.7,.385,1.9,4.1,.457,.522,0.5,0.7,.732,0.8,2.5,3.3,2.9,0.9,0.3,1.5,2.1,9.7,Atlanta Hawks
+5,Dewayne Dedmon,29,64,52,25.1,4.0,8.2,.492,1.3,3.4,.382,2.8,4.8,.570,.571,1.4,1.8,.814,1.6,5.9,7.5,1.4,1.1,1.1,1.3,3.3,10.8,Atlanta Hawks
+1,Kemba Walker,28,82,82,34.9,8.9,20.5,.434,3.2,8.9,.356,5.7,11.6,.494,.511,4.6,5.5,.844,0.6,3.8,4.4,5.9,1.2,0.4,2.6,1.6,25.6,Charlotte Hornets
+2,Nicolas Batum,30,75,72,31.4,3.4,7.5,.450,1.5,4.0,.389,1.8,3.5,.519,.553,1.0,1.2,.865,0.9,4.3,5.2,3.3,0.9,0.6,1.6,1.9,9.3,Charlotte Hornets
+3,Jeremy Lamb,26,79,55,28.5,5.5,12.4,.440,1.5,4.2,.348,4.0,8.2,.487,.499,2.9,3.3,.888,0.8,4.7,5.5,2.2,1.1,0.4,1.0,1.8,15.3,Charlotte Hornets
+4,Marvin Williams,32,75,75,28.4,3.7,8.7,.422,1.9,5.1,.366,1.8,3.6,.500,.529,0.9,1.1,.767,1.0,4.4,5.4,1.2,0.9,0.8,0.6,2.1,10.1,Charlotte Hornets
+5,Cody Zeller,26,49,47,25.4,3.9,7.0,.551,0.1,0.4,.273,3.8,6.6,.570,.559,2.3,2.9,.787,2.2,4.6,6.8,2.1,0.8,0.8,1.3,3.3,10.1,Charlotte Hornets
+1,Bradley Beal,25,82,82,36.9,9.3,19.6,.475,2.5,7.3,.351,6.8,12.4,.548,.540,4.4,5.5,.808,1.1,3.9,5.0,5.5,1.5,0.7,2.7,2.8,25.6,Washington Wizards
+2,John Wall,28,32,32,34.5,7.7,17.3,.444,1.6,5.3,.302,6.1,12.0,.507,.490,3.8,5.5,.697,0.5,3.2,3.6,8.7,1.5,0.9,3.8,2.2,20.7,Washington Wizards
+3,Trevor Ariza,33,43,43,34.1,4.8,11.8,.409,2.2,6.9,.322,2.6,5.0,.528,.502,2.2,2.8,.777,0.8,4.5,5.3,3.8,1.2,0.3,1.6,2.0,14.1,Washington Wizards
+4,Otto Porter Jr.,25,41,28,29.0,4.9,10.8,.457,1.6,4.3,.369,3.3,6.5,.515,.531,1.2,1.6,.766,1.0,4.7,5.6,2.0,1.6,0.5,1.0,1.9,12.6,Washington Wizards
+5,Bobby Portis,23,28,22,27.4,5.6,12.8,.440,1.7,4.3,.403,3.9,8.5,.458,.507,1.4,1.7,.809,2.3,6.4,8.6,1.5,0.9,0.4,1.6,3.0,14.3,Washington Wizards
+1,Aaron Gordon,23,78,78,33.8,6.0,13.4,.449,1.6,4.4,.349,4.5,9.0,.499,.507,2.4,3.2,.731,1.7,5.7,7.4,3.7,0.7,0.7,2.1,2.2,16.0,Orlando Magic
+2,Evan Fournier,26,81,81,31.5,5.8,13.2,.438,1.9,5.6,.340,3.9,7.6,.509,.509,1.7,2.1,.806,0.5,2.7,3.2,3.6,0.9,0.1,1.9,2.8,15.1,Orlando Magic
+3,Nikola Vučević,28,80,80,31.4,8.8,16.9,.518,1.1,2.9,.364,7.7,14.0,.549,.549,2.2,2.8,.789,2.8,9.2,12.0,3.8,1.0,1.1,2.0,2.0,20.8,Orlando Magic
+4,D.J. Augustin,31,81,81,28.0,3.9,8.4,.470,1.6,3.8,.421,2.3,4.5,.511,.566,2.2,2.6,.866,0.5,2.0,2.5,5.3,0.6,0.0,1.6,1.4,11.7,Orlando Magic
+5,Jonathan Isaac,21,75,64,26.6,3.5,8.1,.429,1.1,3.5,.323,2.3,4.6,.510,.499,1.5,1.8,.815,1.3,4.2,5.5,1.1,0.8,1.3,1.0,1.9,9.6,Orlando Magic
+1,Paul George,28,77,77,36.9,9.2,21.0,.438,3.8,9.8,.386,5.4,11.1,.484,.529,5.9,7.0,.839,1.4,6.8,8.2,4.1,2.2,0.4,2.7,2.8,28.0,Oklahoma City Thunder
+2,Russell Westbrook,30,73,73,36.0,8.6,20.2,.428,1.6,5.6,.290,7.0,14.5,.481,.468,4.1,6.2,.656,1.5,9.6,11.1,10.7,1.9,0.5,4.5,3.4,22.9,Oklahoma City Thunder
+3,Steven Adams,25,80,80,33.4,6.0,10.1,.595,0.0,0.0,.000,6.0,10.1,.596,.595,1.8,3.7,.500,4.9,4.6,9.5,1.6,1.5,1.0,1.7,2.6,13.9,Oklahoma City Thunder
+4,Jerami Grant,24,80,77,32.7,5.1,10.3,.497,1.4,3.7,.392,3.7,6.6,.555,.567,2.0,2.8,.710,1.2,4.0,5.2,1.0,0.8,1.3,0.8,2.7,13.6,Oklahoma City Thunder
+5,Dennis Schröder,25,79,14,29.3,5.8,14.0,.414,1.6,4.6,.341,4.2,9.4,.450,.470,2.4,2.9,.819,0.5,3.1,3.6,4.1,0.8,0.2,2.2,2.4,15.5,Oklahoma City Thunder
+1,Damian Lillard,28,80,80,35.5,8.5,19.2,.444,3.0,8.0,.369,5.6,11.1,.499,.522,5.9,6.4,.912,0.9,3.8,4.6,6.9,1.1,0.4,2.7,1.9,25.8,Portland Trail Blazers
+2,CJ McCollum,27,70,70,33.9,8.2,17.8,.459,2.4,6.4,.375,5.8,11.4,.506,.527,2.3,2.7,.828,0.9,3.1,4.0,3.0,0.8,0.4,1.5,2.5,21.0,Portland Trail Blazers
+3,Al-Farouq Aminu,28,81,81,28.3,3.2,7.3,.433,1.2,3.5,.343,2.0,3.9,.514,.514,1.9,2.1,.867,1.4,6.1,7.5,1.3,0.8,0.4,0.9,1.8,9.4,Portland Trail Blazers
+4,Jusuf Nurkić,24,72,72,27.4,5.8,11.5,.508,0.0,0.4,.103,5.8,11.1,.523,.510,3.9,5.1,.773,3.4,7.0,10.4,3.2,1.0,1.4,2.3,3.5,15.6,Portland Trail Blazers
+5,Rodney Hood,26,27,4,24.4,3.6,8.0,.452,1.1,3.1,.345,2.6,4.9,.519,.518,1.2,1.5,.805,0.3,1.4,1.7,1.3,0.8,0.3,0.7,1.7,9.6,Portland Trail Blazers
+1,Donovan Mitchell,22,77,77,33.7,8.6,19.9,.432,2.4,6.7,.362,6.1,13.1,.468,.493,4.1,5.1,.806,0.8,3.3,4.1,4.2,1.4,0.4,2.8,2.7,23.8,Utah Jazz
+2,Rudy Gobert,26,81,80,31.8,5.9,8.8,.669,0.0,0.0,,5.9,8.8,.669,.669,4.1,6.4,.636,3.8,9.0,12.9,2.0,0.8,2.3,1.6,2.9,15.9,Utah Jazz
+3,Joe Ingles,31,82,82,31.3,4.4,9.8,.448,2.3,5.9,.391,2.1,3.9,.533,.565,1.1,1.5,.707,0.4,3.6,4.0,5.7,1.2,0.2,2.4,2.2,12.1,Utah Jazz
+4,Ricky Rubio,28,68,67,27.9,4.3,10.7,.404,1.2,3.7,.311,3.2,7.0,.454,.458,2.9,3.4,.855,0.5,3.1,3.6,6.1,1.3,0.1,2.6,2.6,12.7,Utah Jazz
+5,Jae Crowder,28,80,11,27.1,4.0,10.0,.399,2.2,6.5,.331,1.8,3.4,.527,.508,1.8,2.5,.721,0.8,4.1,4.8,1.7,0.8,0.4,1.1,2.1,11.9,Utah Jazz
+1,Nikola Jokić,27,5,5,33.6,8.0,12.2,.656,0.6,2.0,.300,7.4,10.2,.725,.680,5.8,6.4,.906,1.6,9.2,10.8,9.4,1.6,0.2,3.0,3.6,22.4,Denver Nuggets
+2,Kentavious Caldwell-Pope,29,5,5,31.0,4.0,8.6,.465,2.6,5.2,.500,1.4,3.4,.412,.616,1.2,1.2,1.000,0.6,3.2,3.8,3.0,1.2,0.2,1.2,2.6,11.8,Denver Nuggets
+3,Aaron Gordon,27,5,5,29.2,6.4,12.4,.516,0.2,3.2,.063,6.2,9.2,.674,.524,2.0,3.2,.625,3.0,4.6,7.6,2.6,0.2,1.0,1.4,1.4,15.0,Denver Nuggets
+4,Michael Porter Jr.,24,4,4,29.0,6.5,12.8,.510,4.0,8.0,.500,2.5,4.8,.526,.667,1.0,1.3,.800,1.3,4.5,5.8,1.3,0.8,0.5,2.0,4.5,18.0,Denver Nuggets
+5,Bruce Brown,26,5,2,27.2,4.6,8.6,.535,1.6,3.2,.500,3.0,5.4,.556,.628,0.6,1.2,.500,1.0,1.8,2.8,3.4,0.8,0.4,1.2,1.8,11.4,Denver Nuggets
+1,Jimmy Butler,29,10,10,36.1,7.4,15.7,.471,1.7,4.5,.378,5.7,11.2,.509,.525,4.8,6.1,.787,1.6,3.6,5.2,4.3,2.4,1.0,1.4,1.8,21.3,Minnesota Timberwolves
+2,Andrew Wiggins,23,73,73,34.8,6.8,16.6,.412,1.6,4.8,.339,5.2,11.8,.441,.461,2.8,4.1,.699,1.1,3.7,4.8,2.5,1.0,0.7,1.9,2.1,18.1,Minnesota Timberwolves
+3,Robert Covington,28,22,22,34.7,4.8,11.1,.433,2.5,6.7,.372,2.3,4.4,.526,.545,2.3,3.0,.773,1.0,4.8,5.7,1.5,2.3,1.1,1.1,3.7,14.5,Minnesota Timberwolves
+4,Karl-Anthony Towns,23,77,77,33.1,8.8,17.1,.518,1.8,4.6,.400,7.0,12.5,.562,.572,4.9,5.8,.836,3.4,9.0,12.4,3.4,0.9,1.6,3.1,3.8,24.4,Minnesota Timberwolves
+5,Jeff Teague,30,42,41,30.1,4.2,9.9,.423,0.8,2.5,.333,3.4,7.4,.453,.465,2.9,3.6,.804,0.4,2.1,2.5,8.2,1.0,0.4,2.3,2.1,12.1,Minnesota Timberwolves
+1,Kevin Durant,30,78,78,34.6,9.2,17.7,.521,1.8,5.0,.353,7.5,12.8,.587,.571,5.7,6.5,.885,0.4,5.9,6.4,5.9,0.7,1.1,2.9,2.0,26.0,Golden State Warriors
+2,Klay Thompson,28,78,78,34.0,8.4,18.0,.467,3.1,7.7,.402,5.3,10.3,.516,.553,1.7,2.0,.816,0.5,3.4,3.8,2.4,1.1,0.6,1.5,2.0,21.5,Golden State Warriors
+3,Stephen Curry,30,69,69,33.8,9.2,19.4,.472,5.1,11.7,.437,4.0,7.7,.525,.604,3.8,4.2,.916,0.7,4.7,5.3,5.2,1.3,0.4,2.8,2.4,27.3,Golden State Warriors
+4,Draymond Green,28,66,66,31.3,2.8,6.4,.445,0.7,2.5,.285,2.1,3.9,.549,.501,1.0,1.4,.692,0.9,6.4,7.3,6.9,1.4,1.1,2.6,3.0,7.4,Golden State Warriors
+5,DeMarcus Cousins,28,30,30,25.7,5.9,12.4,.480,0.9,3.2,.274,5.1,9.2,.551,.515,3.5,4.8,.736,1.4,6.8,8.2,3.6,1.3,1.5,2.4,3.6,16.3,Golden State Warriors
+1,Tobias Harris,26,55,55,34.6,7.7,15.5,.496,2.0,4.7,.434,5.7,10.9,.523,.561,3.5,4.0,.877,0.7,7.2,7.9,2.7,0.7,0.4,2.0,2.2,20.9,Los Angeles Clippers
+2,Danilo Gallinari,30,68,68,30.3,6.0,13.0,.463,2.4,5.5,.433,3.6,7.5,.484,.554,5.4,6.0,.904,0.8,5.3,6.1,2.6,0.7,0.3,1.5,1.9,19.8,Los Angeles Clippers
+3,Avery Bradley,28,49,49,29.9,3.3,8.6,.383,1.2,3.5,.337,2.1,5.1,.415,.452,0.4,0.5,.800,0.7,2.0,2.7,2.0,0.6,0.3,1.2,2.7,8.2,Los Angeles Clippers
+4,Landry Shamet,21,25,23,27.8,3.5,8.4,.414,2.7,6.0,.450,0.8,2.4,.322,.576,1.2,1.6,.795,0.3,2.0,2.2,2.3,0.5,0.1,0.8,2.0,10.9,Los Angeles Clippers
+5,Patrick Beverley,30,78,49,27.4,2.5,6.1,.407,1.4,3.6,.397,1.1,2.5,.421,.524,1.2,1.6,.780,1.0,4.0,5.0,3.8,0.9,0.6,1.1,3.4,7.6,Los Angeles Clippers
+1,Harrison Barnes,26,28,28,33.9,5.0,11.1,.455,1.9,4.6,.408,3.1,6.4,.489,.540,2.3,2.9,.800,0.8,4.8,5.5,1.9,0.6,0.1,1.1,1.5,14.3,Sacramento Kings
+2,Buddy Hield,26,82,82,31.9,7.6,16.6,.458,3.4,7.9,.427,4.2,8.6,.487,.560,2.1,2.4,.886,1.3,3.7,5.0,2.5,0.7,0.4,1.8,2.5,20.7,Sacramento Kings
+3,De'Aaron Fox,21,81,81,31.4,6.2,13.6,.458,1.1,2.9,.371,5.2,10.7,.482,.497,3.7,5.1,.727,0.5,3.2,3.8,7.3,1.6,0.6,2.8,2.5,17.3,Sacramento Kings
+4,Bogdan Bogdanović,26,70,17,27.8,5.2,12.3,.418,1.9,5.3,.360,3.2,7.0,.462,.496,1.9,2.3,.827,0.6,2.9,3.5,3.8,1.0,0.2,1.7,2.0,14.1,Sacramento Kings
+5,Willie Cauley-Stein,25,81,81,27.3,5.1,9.1,.556,0.0,0.0,.500,5.1,9.1,.556,.557,1.7,3.1,.551,2.2,6.1,8.4,2.4,1.2,0.6,1.0,2.8,11.9,Sacramento Kings
+1,Devin Booker,22,64,64,35.0,9.2,19.6,.467,2.1,6.5,.326,7.0,13.1,.536,.521,6.1,7.1,.866,0.6,3.5,4.1,6.8,0.9,0.2,4.1,3.1,26.6,Phoenix Suns
+2,Trevor Ariza,33,26,26,34.0,3.3,8.7,.379,1.9,5.3,.360,1.4,3.4,.409,.489,1.4,1.7,.837,0.6,5.0,5.6,3.3,1.5,0.3,1.5,1.7,9.9,Phoenix Suns
+3,T.J. Warren,25,43,36,31.6,6.9,14.2,.486,1.8,4.2,.428,5.1,10.0,.510,.549,2.3,2.9,.815,0.7,3.3,4.0,1.5,1.2,0.7,1.2,2.8,18.0,Phoenix Suns
+4,Tyler Johnson,26,13,12,31.2,3.5,9.6,.368,1.4,4.3,.321,2.2,5.3,.406,.440,2.6,3.0,.872,1.2,2.8,4.0,4.2,1.1,0.5,1.1,1.9,11.1,Phoenix Suns
+5,Deandre Ayton,20,71,70,30.7,7.2,12.3,.585,0.0,0.1,.000,7.2,12.2,.588,.585,2.0,2.7,.746,3.1,7.1,10.3,1.8,0.9,0.9,1.8,2.9,16.3,Phoenix Suns
+1,LeBron James,34,55,55,35.2,10.1,19.9,.510,2.0,5.9,.339,8.1,14.0,.582,.560,5.1,7.6,.665,1.0,7.4,8.5,8.3,1.3,0.6,3.6,1.7,27.4,Los Angeles Lakers
+2,Brandon Ingram,21,52,52,33.8,7.0,14.0,.497,0.6,1.8,.330,6.4,12.2,.521,.518,3.8,5.6,.675,0.8,4.3,5.1,3.0,0.5,0.6,2.5,2.9,18.3,Los Angeles Lakers
+3,Kyle Kuzma,23,70,68,33.1,7.1,15.5,.456,1.8,6.0,.303,5.3,9.5,.553,.515,2.7,3.6,.752,0.9,4.6,5.5,2.5,0.6,0.4,1.9,2.4,18.7,Los Angeles Lakers
+4,Lonzo Ball,21,47,45,30.3,3.9,9.7,.406,1.6,4.9,.329,2.3,4.9,.482,.488,0.4,1.0,.417,1.1,4.2,5.3,5.4,1.5,0.4,2.2,2.4,9.9,Los Angeles Lakers
+5,Rajon Rondo,32,46,29,29.8,3.8,9.4,.405,1.1,3.1,.359,2.7,6.3,.428,.464,0.5,0.8,.639,0.7,4.5,5.3,8.0,1.2,0.2,2.8,2.2,9.2,Los Angeles Lakers
+1,DeMar DeRozan,29,77,77,34.9,8.2,17.1,.481,0.1,0.6,.156,8.1,16.5,.492,.483,4.8,5.7,.830,0.7,5.3,6.0,6.2,1.1,0.5,2.6,2.3,21.2,San Antonio Spurs
+2,LaMarcus Aldridge,33,81,81,33.2,8.4,16.3,.519,0.1,0.5,.238,8.3,15.8,.528,.522,4.3,5.1,.847,3.1,6.1,9.2,2.4,0.5,1.3,1.8,2.2,21.3,San Antonio Spurs
+3,Bryn Forbes,25,82,81,28.0,4.4,9.6,.456,2.1,5.0,.426,2.3,4.6,.489,.568,0.8,1.0,.885,0.2,2.7,2.9,2.1,0.5,0.0,1.0,1.9,11.8,San Antonio Spurs
+4,Rudy Gay,32,69,51,26.7,5.4,10.8,.504,1.1,2.7,.402,4.4,8.1,.537,.554,1.7,2.1,.816,0.9,5.9,6.8,2.6,0.8,0.5,1.7,2.3,13.7,San Antonio Spurs
+5,Derrick White,24,67,55,25.8,3.9,8.1,.479,0.7,2.1,.338,3.2,6.0,.529,.523,1.4,1.8,.772,0.5,3.2,3.7,3.9,1.0,0.7,1.4,2.2,9.9,San Antonio Spurs
+1,Harrison Barnes,26,49,49,32.3,5.9,14.6,.404,2.5,6.3,.389,3.4,8.3,.416,.489,3.4,4.0,.833,0.7,3.5,4.2,1.3,0.7,0.2,1.4,1.6,17.7,Dallas Mavericks
+2,Luka Dončić,19,72,72,32.2,7.0,16.5,.427,2.3,7.1,.327,4.7,9.3,.503,.497,4.8,6.7,.713,1.2,6.6,7.8,6.0,1.1,0.3,3.4,1.9,21.2,Dallas Mavericks
+3,DeAndre Jordan,30,50,50,31.1,4.2,6.5,.644,0.0,0.0,,4.2,6.5,.644,.644,2.7,4.0,.682,3.2,10.5,13.7,2.0,0.7,1.1,2.2,2.5,11.0,Dallas Mavericks
+4,Wesley Matthews,32,44,44,29.8,4.4,10.7,.414,2.3,6.0,.380,2.1,4.7,.456,.520,2.0,2.5,.791,0.5,1.9,2.3,2.3,0.8,0.3,1.3,2.3,13.1,Dallas Mavericks
+5,Tim Hardaway Jr.,26,19,17,29.4,5.7,14.1,.404,2.4,7.4,.321,3.3,6.7,.496,.489,1.7,2.3,.767,0.4,2.8,3.2,1.9,0.6,0.1,1.3,1.8,15.5,Dallas Mavericks
+1,Marc Gasol,34,53,53,33.7,5.7,12.9,.444,1.4,4.2,.344,4.3,8.7,.491,.499,2.9,3.8,.756,1.1,7.5,8.6,4.7,1.1,1.2,2.2,2.8,15.7,Memphis Grizzlies
+2,Mike Conley,31,70,70,33.5,7.0,16.0,.438,2.2,6.1,.364,4.8,9.9,.483,.507,4.9,5.8,.845,0.6,2.8,3.4,6.4,1.3,0.3,1.9,1.8,21.1,Memphis Grizzlies
+3,Avery Bradley,28,14,14,31.6,6.2,13.4,.463,2.0,5.2,.384,4.2,8.2,.513,.537,1.6,1.8,.920,0.6,2.6,3.1,4.0,1.0,0.0,2.0,2.4,16.1,Memphis Grizzlies
+4,Garrett Temple,32,49,49,31.2,3.4,7.9,.429,1.5,4.3,.352,1.9,3.6,.520,.525,1.2,1.6,.750,0.4,2.7,3.1,1.4,1.0,0.5,1.1,2.7,9.4,Memphis Grizzlies
+5,Delon Wright,26,26,11,30.8,4.4,10.2,.434,0.8,3.0,.256,3.7,7.2,.508,.472,2.5,3.4,.742,1.1,4.3,5.4,5.3,1.6,0.6,1.5,1.9,12.2,Memphis Grizzlies
+1,James Harden,29,78,78,36.8,10.8,24.5,.442,4.8,13.2,.368,6.0,11.3,.528,.541,9.7,11.0,.879,0.8,5.8,6.6,7.5,2.0,0.7,5.0,3.1,36.1,Houston Rockets
+2,P.J. Tucker,33,82,82,34.2,2.5,6.4,.396,1.8,4.7,.377,0.7,1.7,.449,.535,0.5,0.7,.695,1.5,4.4,5.8,1.2,1.6,0.5,0.8,3.1,7.3,Houston Rockets
+3,Clint Capela,24,67,67,33.6,7.1,10.9,.648,0.0,0.0,,7.1,10.9,.648,.648,2.5,3.9,.636,4.4,8.2,12.7,1.4,0.7,1.5,1.4,2.5,16.6,Houston Rockets
+4,Chris Paul,33,58,58,32.0,5.2,12.4,.419,2.2,6.1,.358,3.0,6.3,.479,.508,3.0,3.5,.862,0.6,3.9,4.6,8.2,2.0,0.3,2.6,2.5,15.6,Houston Rockets
+5,Eric Gordon,30,68,53,31.7,5.6,13.8,.409,3.2,8.8,.360,2.5,5.0,.497,.525,1.8,2.2,.783,0.3,1.9,2.2,1.9,0.6,0.4,1.3,2.1,16.2,Houston Rockets
+1,Jrue Holiday,28,67,67,35.9,8.2,17.3,.472,1.8,5.4,.325,6.4,11.9,.539,.523,3.1,4.0,.768,1.1,3.9,5.0,7.7,1.6,0.8,3.1,2.2,21.2,New Orleans Pelicans
+2,Anthony Davis,25,56,56,33.0,9.5,18.3,.517,0.9,2.6,.331,8.6,15.7,.547,.540,6.1,7.7,.794,3.1,8.9,12.0,3.9,1.6,2.4,2.0,2.4,25.9,New Orleans Pelicans
+3,Julius Randle,24,73,49,30.6,7.8,14.9,.524,0.9,2.7,.344,6.9,12.2,.564,.555,4.9,6.7,.731,2.2,6.5,8.7,3.1,0.7,0.6,2.8,3.4,21.4,New Orleans Pelicans
+4,Elfrid Payton,24,42,42,29.8,4.3,9.8,.434,0.8,2.5,.314,3.5,7.3,.476,.475,1.3,1.8,.743,1.2,4.1,5.2,7.6,1.0,0.4,2.7,1.9,10.6,New Orleans Pelicans
+5,Nikola Mirotić,27,32,22,28.9,5.7,12.7,.447,2.7,7.2,.368,3.0,5.5,.551,.552,2.7,3.2,.842,1.4,6.8,8.3,1.1,0.7,0.8,1.2,2.7,16.7,New Orleans Pelicans

requirements.txt

@@ -0,0 +1,4 @@
+snowflake-connector-python
+tensorflow
+numpy
+pandas

train_model.py

@@ -0,0 +1,74 @@
+import pandas as pd
+import numpy as np
+from tensorflow import keras
+from tensorflow.keras import layers
+from tensorflow.keras.losses import BinaryCrossentropy
+from sklearn.model_selection import train_test_split
+from sklearn.model_selection import RandomizedSearchCV
+from scikeras.wrappers import KerasClassifier 
+
+
+def create_stats(roster, schedule):
+    home_stats = []
+    away_stats = []
+    S = []
+
+    # Loading Relavent Columns from f-test
+    cols = ['TEAM','PTS/G', 'ORB', 'DRB', 'AST', 'STL', 'BLK', 'TOV', '3P%', 'FT%','2P'] 
+    new_roster = roster[cols]
+    for i in schedule['Home/Neutral']:
+        home_stats.append((new_roster[new_roster['TEAM'] == i]).values.tolist())
+    for i in schedule['Visitor/Neutral']:
+        away_stats.append((new_roster.loc[new_roster['TEAM'] == i]).values.tolist())
+    for i in range(len(home_stats)):
+        arr = []
+        for j in range(len(home_stats[i])):
+            del home_stats[i][j][0]
+            arr += home_stats[i][j]
+        for j in range(len(away_stats[i])):
+            del away_stats[i][j][0]
+            arr += away_stats[i][j]
+
+        # Create numpy array with all the players on the Home Team's Stats followed by the Away Team's stats    
+        S.append(np.nan_to_num(np.array(arr), copy=False))
+    return S
+
+roster = pd.read_csv('player_stats.txt', delimiter=',')
+schedule = pd.read_csv('schedule.txt', delimiter=',')
+
+# Create winning condition to train on
+schedule['winner'] = schedule.apply(lambda x: 0 if x['PTS'] > x['PTS.1'] else 1, axis=1) 
+
+X = np.array(create_stats(roster, schedule))
+y = np.array(schedule['winner'])
+X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
+
+def create_model(optimizer='rmsprop', init='glorot_uniform'):
+    inputs = keras.Input(shape=(100,))
+    dense = layers.Dense(50, activation="relu")
+    x = dense(inputs)
+    x = layers.Dense(64, activation="relu")(x)
+    outputs = layers.Dense(1, activation='sigmoid')(x)
+    model = keras.Model(inputs=inputs, outputs=outputs, name="nba_model")
+    model.compile(loss=BinaryCrossentropy(from_logits=False), optimizer=optimizer, metrics=["accuracy"])
+    
+    return model
+
+model = KerasClassifier(model=create_model, verbose=0, init='glorot_uniform')
+
+optimizer = ['SGD', 'RMSprop', 'Adagrad', 'Adadelta', 'Adam', 'Adamax', 'Nadam']
+init = ['uniform', 'lecun_uniform', 'normal', 'zero', 'glorot_normal', 'glorot_uniform', 'he_normal', 'he_uniform']
+epochs = [500, 1000, 1500]
+batches = [50, 100, 200]
+param_grid = dict(optimizer=optimizer, epochs=epochs, batch_size=batches, init=init)
+
+random_search = RandomizedSearchCV(estimator=model, param_distributions=param_grid, n_iter=100, verbose=3)
+random_search_result = random_search.fit(X_train, y_train)
+best_model = random_search_result.best_estimator_
+
+best_model.model_.save('winner.keras')
+best_parameters = random_search_result.best_params_
+print("Best parameters: ", best_parameters)
+
+test_accuracy = random_search_result.best_estimator_.score(X_test, y_test)
+print("Test accuracy: ", test_accuracy)

winner_model/fingerprint.pb

@@ -0,0 +1 @@
+���������
�����ΏϨ
������� э�������
(��ۓ岩W2

winner_model/keras_metadata.pb

@@ -0,0 +1,8 @@
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