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Dalyn_NHL_Betting_Models
Runtime error

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Multichem commited on
Commit
4e8fdc8
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1 Parent(s): 1cde72c

Update app.py

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Files changed (1) hide show
  1. app.py +4 -4
app.py CHANGED
@@ -239,7 +239,7 @@ with tab3:
239
  st.table(prop_df)
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  prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
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  prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
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- prop = prop_df['prop_type']
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  df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
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  elif prop_type_var == "points":
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  prop_df = prop_trends[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
@@ -250,7 +250,7 @@ with tab3:
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  st.table(prop_df)
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  prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
252
  prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
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- prop = prop_df['prop_type']
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  df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
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  elif prop_type_var == "assists":
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  prop_df = prop_trends[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
@@ -261,7 +261,7 @@ with tab3:
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  st.table(prop_df)
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  prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
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  prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
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- prop = prop_df['prop_type']
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  df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
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  elif prop_type_var == "blocked_shots":
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  prop_df = prop_trends[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
@@ -272,7 +272,7 @@ with tab3:
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  st.table(prop_df)
273
  prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
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  prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
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- prop = prop_df['prop_type']
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  df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
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  prop_dict = dict(zip(df.Player, df.Prop))
 
239
  st.table(prop_df)
240
  prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
241
  prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
242
+ prop = 'SOG'
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  df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
244
  elif prop_type_var == "points":
245
  prop_df = prop_trends[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
 
250
  st.table(prop_df)
251
  prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
252
  prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
253
+ prop = 'points'
254
  df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
255
  elif prop_type_var == "assists":
256
  prop_df = prop_trends[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
 
261
  st.table(prop_df)
262
  prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
263
  prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
264
+ prop = 'assists'
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  df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
266
  elif prop_type_var == "blocked_shots":
267
  prop_df = prop_trends[['Player', 'over_prop', 'over_line', 'under_line', 'prop_type']]
 
272
  st.table(prop_df)
273
  prop_df['Over'] = np.where(prop_df['over_line'] < 0, (-(prop_df['over_line'])/((-(prop_df['over_line']))+101)), 101/(prop_df['over_line']+101))
274
  prop_df['Under'] = np.where(prop_df['under_line'] < 0, (-(prop_df['under_line'])/((-(prop_df['under_line']))+101)), 101/(prop_df['under_line']+101))
275
+ prop = 'blocked_shots'
276
  df = pd.merge(prop_display, prop_df, how='left', left_on=['Player'], right_on = ['Player'])
277
 
278
  prop_dict = dict(zip(df.Player, df.Prop))