<jupyter_start><jupyter_text>What makes a good rebounder?1) Height2) Wingspan3) Relative Weight3) Positioning on the court when shots are taken4) HustleHow to check for good rebounders? - Compare each player's TRB to other players of the same size / wingspan    - TRB-Ht: R = .459    - TRB-Wt: R = .504 - Check for a negative correlation for 3PA and TRB with centers (R = -.327)<jupyter_code># centers_per_36 = get_player_offense(filter="per_36",position="C")
# centers_per_36["PPI"] = round(centers_per_36["Wt"] / centers_per_36["Ht"],2)
# centers_per_36["zHT"] = round((centers_per_36["Ht"]-centers_per_36["Ht"].mean())/centers_per_36["Ht"].std(),2)
# centers_per_36["zPPI"]= round((centers_per_36["PPI"]-centers_per_36["PPI"].mean())/centers_per_36["PPI"].std(),2)
# centers_per_36["z3PA"]= -round((centers_per_36["3PA"]-centers_per_36["3PA"].mean())/centers_per_36["3PA"].std(),2)
# centers_per_36["Z"]= round(sum([centers_per_36["zHT"],centers_per_36["zPPI"],centers_per_36["z3PA"]])/3,2)

# centers_per_36.sort_values(by="Z",ascending=True)[:30].drop(columns=["Pos","MP","Wt","3P","3PA"])

### Compare two teams
# centers_per_36[(centers_per_36["Team"]=="MIA") | (centers_per_36["Team"]=="CHI")].drop(columns=["Pos","MP","Wt","3P","3PA"])

### Find stats that relate to each other
# centers_per_36.corr()

### Reveal normal rebounding range for position
# print(f'{centers_per_36["TRB"].mean()-centers_per_36["TRB"].std()} - {centers_per_36["TRB"].mean()+centers_per_36["TRB"].std()}')<jupyter_output><empty_output>
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