A python package for reading volleyball scouting files in DataVolley format (*.dvw).
https://pydatavolley.openvolley.org/
pip install pydatavolley
# Using read_dv.DataVolley(None) will use example file
import pandas as pd
from datavolley import read_dv
pd.set_option('display.max_rows', 50)
pd.set_option('display.max_columns', 500)
pd.set_option('display.width', 400)
dv_instance = read_dv.DataVolley(None)
df = dv_instance.get_plays()
print(df.head(10)) match_id video_file_number video_time code team player_number player_name player_id skill evaluation_code setter_position attack_code set_code set_type start_zone end_zone end_subzone num_players_numeric home_team_score visiting_team_score home_setter_position visiting_setter_position custom_code home_p1 home_p2 \
0 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 494 *P19>LUp University of Louisville NaN NaN NaN NaN NaN 1 NaN NaN NaN NaN NaN NaN NaN <NA> <NA> 1 6 None 19 9
1 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 494 *z1>LUp University of Louisville NaN NaN NaN NaN NaN 1 NaN NaN NaN NaN NaN NaN NaN <NA> <NA> 1 6 None 19 9
2 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 494 aP08>LUp University of Dayton NaN NaN NaN NaN NaN 6 NaN NaN NaN NaN NaN NaN NaN <NA> <NA> 1 6 None 19 9
3 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 494 az6>LUp University of Dayton NaN NaN NaN NaN NaN 6 NaN NaN NaN NaN NaN NaN NaN <NA> <NA> 1 6 None 19 9
4 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 494 *19SM+~~~78A~~~00 University of Louisville 19 Shannon Shields -296094 Serve + 1 NaN NaN NaN 7 8 A NaN 1 0 1 6 00 19 9
5 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 495 a02RM-~~~58AM~~00B University of Dayton 2 Maura Collins -230138 Reception - 6 NaN NaN NaN 5 8 A NaN 1 0 1 6 00B 19 9
6 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 497 a08ET#~~~~8C~~~00 University of Dayton 8 Brooke Westbeld -232525 Set # 6 NaN NaN ~ NaN 8 C NaN 1 0 1 6 00 19 9
7 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 499 a10AT-X5~46CH2~00F University of Dayton 10 Jamie Peterson -11802 Attack - 6 X5 NaN NaN 4 6 C 2 1 0 1 6 00F 19 9
8 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 499 *11BT+~~~~2C~~~00 University of Louisville 11 Anna Stevenson -278838 Block + 1 NaN NaN NaN NaN 2 C NaN 1 0 1 6 00 19 9
9 6e6d55e3-96b6-4c63-b000-d5bbb7c1794a 1 500 *19DT+~~~42AB~~00B University of Louisville 19 Shannon Shields -296094 Dig + 1 NaN NaN NaN 4 2 A NaN 1 0 1 6 00B 19 9
home_p3 home_p4 home_p5 home_p6 visiting_p1 visiting_p2 visiting_p3 visiting_p4 visiting_p5 visiting_p6 start_coordinate mid_coordinate end_coordinate point_phase attack_phase start_coordinate_x start_coordinate_y mid_coordinate_x mid_coordinate_y end_coordinate_x end_coordinate_y set_number home_team visiting_team home_team_id visiting_team_id \
0 11 15 10 7 1 16 17 10 6 8 <NA> <NA> <NA> Reception nan <NA> <NA> <NA> <NA> <NA> <NA> 1 University of Louisville University of Dayton 17 42
1 11 15 10 7 1 16 17 10 6 8 <NA> <NA> <NA> Reception nan <NA> <NA> <NA> <NA> <NA> <NA> 1 University of Louisville University of Dayton 17 42
2 11 15 10 7 1 16 17 10 6 8 <NA> <NA> <NA> Reception nan <NA> <NA> <NA> <NA> <NA> <NA> 1 University of Louisville University of Dayton 17 42
3 11 15 10 7 1 16 17 10 6 8 <NA> <NA> <NA> Reception nan <NA> <NA> <NA> <NA> <NA> <NA> 1 University of Louisville University of Dayton 17 42
4 11 15 10 7 1 16 17 10 6 8 431 <NA> 7642 Serve nan 1.26875 0.092596 <NA> <NA> 1.68125 5.425924 1 University of Louisville University of Dayton 17 42
5 11 15 10 7 1 16 17 10 6 8 431 <NA> 7642 Reception nan 1.26875 0.092596 <NA> <NA> 1.68125 5.425924 1 University of Louisville University of Dayton 17 42
6 11 15 10 7 1 16 17 10 6 8 3147 <NA> <NA> Reception nan 1.86875 2.092594 <NA> <NA> <NA> <NA> 1 University of Louisville University of Dayton 17 42
7 11 15 10 7 1 16 17 10 6 8 4512 5522 8150 Reception Reception 0.55625 3.12963 0.93125 3.87037 1.98125 5.796294 1 University of Louisville University of Dayton 17 42
8 11 15 10 7 1 16 17 10 6 8 4578 <NA> <NA> Serve nan 3.03125 3.12963 <NA> <NA> <NA> <NA> 1 University of Louisville University of Dayton 17 42
9 11 15 10 7 1 16 17 10 6 8 4512 5522 5912 Serve nan 0.55625 3.12963 0.93125 3.87037 0.55625 4.166666 1 University of Louisville University of Dayton 17 42
point_won_by serving_team receiving_team rally_number possesion_number
0 NaN NaN NaN 0 0
1 NaN NaN NaN 0 1
2 NaN NaN NaN 0 1
3 NaN NaN NaN 0 1
4 University of Louisville University of Louisville University of Dayton 1 0
5 University of Louisville University of Louisville University of Dayton 1 1
6 University of Louisville University of Louisville University of Dayton 1 1
7 University of Louisville University of Louisville University of Dayton 1 1
8 University of Louisville University of Louisville University of Dayton 1 2
9 University of Louisville University of Louisville University of Dayton 1 2
import pandas as pd
from datavolley import read_dv
import os
# Assign path
dvw_path_folder = os.path.expanduser("~\\desktop\\dvws")
file_extension = ".dvw"
# Get a list of all files with the specified extension in the directory
file_list = [f for f in os.listdir(dvw_path_folder) if f.endswith(file_extension)]
# Initialize an empty DataFrame to store combined data
combined_df = pd.DataFrame()
def process_file(path):
dv_instance = read_dv.DataVolley(os.path.join(dvw_path_folder, path))
df = dv_instance.get_plays()
return df
# Loop through each file path
for file_name in file_list:
combined_df = pd.concat([combined_df, process_file(file_name)], ignore_index=True)
# Filter for attacks and print attacks
print(
combined_df[combined_df['skill'] == 'Attack']
.groupby(['player_name', 'team'])
.agg(Att=('skill', 'count'),
K=('evaluation_code', lambda x: x.eq('#').sum(skipna=True)),
K_pct=('evaluation_code', lambda x: round((x.eq('#').sum(skipna=True) / x.count()), 3)))
.reset_index()
.sort_values(by='K_pct', ascending=False)
.head(20)
.reset_index(drop=True)
.to_string()
) player_name team Att K K_pct
0 Breklyn Pulling California State University, Bakersfield 17 13 0.765
1 Ally Chandler University of California, Davis 8 6 0.750
2 Nicole Briggs University of Arizona 5 3 0.600
3 Kate Hatch Eastern Washington University 7 4 0.571
4 Olivia Utterback University of California, Davis 31 17 0.548
5 Taylor Underwood San Diego State University 26 14 0.538
6 Bailey Ortega University of Iowa 2 1 0.500
7 Ana Heath University of Arizona 2 1 0.500
8 Fatimah Hall San Diego State University 8 4 0.500
9 Ava Palm California State University, Bakersfield 20 9 0.450
10 Jaelyn Hodge University of Arizona 33 14 0.424
11 Anna Davis University of Iowa 19 8 0.421
12 Delaney McSweeney University of Iowa 22 9 0.409
13 Heipua Tautua'A San Diego State University 27 11 0.407
14 Katherine Cooper San Diego State University 10 4 0.400
15 Julia Haynie San Diego State University 15 6 0.400
16 Allie Caldwell University of California, Davis 5 2 0.400
17 Nataly Moravec University of Iowa 23 9 0.391
18 Jordan Wilson University of Arizona 31 12 0.387
19 Bianca Martinez California State University, Fullerton 21 8 0.381
# Using read_dv.DataVolley(None) will use example file
import datavolley.pycourt as pycourt
from datavolley import read_dv
import glob
import matplotlib.pyplot as plt
import pandas as pd
dv_instance = read_dv.DataVolley(None)
df = dv_instance.get_plays()
atk_data = df[(df['skill'] == 'Attack') & (df['attack_code'] == 'X5')]
coordainte_df = atk_data[['start_coordinate_x',
'start_coordinate_y',
'end_coordinate_x',
'end_coordinate_y']]
def plot_coordinates(coordinates):
pycourt.pycourt()
# Plot the coordinates
plt.scatter(coordinates['start_coordinate_x'], coordinates['start_coordinate_y'], color='red')
plt.scatter(coordinates['end_coordinate_x'], coordinates['end_coordinate_y'], color='blue')
# Connect the coordinates with lines
for i in range(len(coordinates)):
start_point = (coordinates['start_coordinate_x'].iloc[i], coordinates['start_coordinate_y'].iloc[i])
end_point = (coordinates['end_coordinate_x'].iloc[i], coordinates['end_coordinate_y'].iloc[i])
plt.plot([start_point[0], end_point[0]], [start_point[1], end_point[1]], color='gray', linestyle='--', linewidth=1)
plt.show(block=True)
plot_coordinates(coordainte_df)