Bowling Statistics

bowlers.py

# Group details on bowler
bowlgroup = balldf.groupby(['bowler'])

# Create a bowling dataframe (bowldf) with a summary statistics for each batsman
bowldf = pd.DataFrame(bowlgroup['ball'].count()).rename(columns={'ball':'balls_bowled'})

# Get no. of wickets taken by each bowler
bwl_wkts = balldf[balldf['dismissal_kind'].isin(['caught','bowled', 'lbw','stumped', 'caught and bowled', 'hit wicket'])]
bowldf['wickets'] = bwl_wkts.groupby(['bowler'])['ball'].count()
bowldf['wickets'].fillna(0,inplace=True)
 
# Calculate the total no. of overs bowled
overs = pd.DataFrame(balldf.groupby(['bowler','id'])['over'].nunique())
bowldf['overs'] = overs.groupby(['bowler'])['over'].sum()    

# Calculate the runs conceded
bowldf['runs_conceded'] = balldf.groupby('bowler')['batsman_runs'].sum()
bowldf['runs_conceded'] = bowldf['runs_conceded'].fillna(0)
# Add the runs conceded through wide and noball
bowldf['runs_conceded'] = bowldf['runs_conceded'].add(balldf[balldf['extras_type'].isin(['wides','noballs'])].groupby('bowler')['extra_runs'].sum(),fill_value=0)

# Note - roughly apprx to overs.  Should be runs_conceded/overs.balls
bowldf['bowl_econ'] = round(bowldf['runs_conceded']/bowldf['overs'],2)