Karl/football-manager-squad-and-recruitment
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updated usage and docstring

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jake-fawcett 2023-10-28 20:00:02 +01:00
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11
README.md
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@ -1,4 +1,9 @@
# football-manager-squad-and-recruitment # Football Manager player role evaluation
Python code to evaluate Squad and Scouted Players in Football Manager. Work in progress. Python code to evaluate Player attributes in Football Manager against roles based on role weightings. Work in progress.
Inspired by squirrel_plays_FOF's video [FM24 player recruitment using python](https://www.youtube.com/watch?v=hnAuOakqR90) Inspired by squirrel_plays_FOF's video [FM24 player recruitment using python](https://www.youtube.com/watch?v=hnAuOakqR90)
## Usage
```
python3 position_score_calculator.py --input-filepath "squad.html" --output-filepath "squad_output.html" --roles goalkeeper fullback
```

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position_score_calculator.py
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@ -2,7 +2,7 @@ import pandas as pd
import argparse import argparse
# Define Player attributes # Define Player attributes
# TODO: Add roles.
goalkeeper = { goalkeeper = {
"role_name": "goalkeeper", "role_name": "goalkeeper",
"primary_multiplier": 5, "primary_multiplier": 5,
@ -13,6 +13,16 @@ goalkeeper = {
"tertiary_attributes": ["Acc", "Aer", "Cmp", "Dec", "Fir", "Han", "Pas", "Thr", "Vis"] "tertiary_attributes": ["Acc", "Aer", "Cmp", "Dec", "Fir", "Han", "Pas", "Thr", "Vis"]
} }
fullback = {
"role_name": "fullback",
"primary_multiplier": 5,
"primary_attributes": ["Wor", "Acc", "Pac", "Sta"],
"secondary_multiplier": 3,
"secondary_attributes": ["Cro", "Dri", "Mar", "OtB", "Tck", "Tea"],
"tertiary_multiplier": 1,
"tertiary_attributes": ["Agi", "Ant", "Cnt", "Dec", "Fir", "Pas", "Pos", "Tec"]
}
def load_html_data_to_dataframe(filepath: str) -> pd.DataFrame: def load_html_data_to_dataframe(filepath: str) -> pd.DataFrame:
"""Read HTML file exported by FM into a Dataframe """Read HTML file exported by FM into a Dataframe
@ -98,20 +108,28 @@ def calc_role_scores(player_df: pd.DataFrame, role: dict) -> pd.DataFrame:
player_df[f'{role["role_name"]}'] = round((((player_df[f'{role["role_name"]}_primary'] * 5) + (player_df[f'{role["role_name"]}_secondary'] * 3) + (player_df[f'{role["role_name"]}_tertiary'] * 1)) / divisor ), 2) player_df[f'{role["role_name"]}'] = round((((player_df[f'{role["role_name"]}_primary'] * 5) + (player_df[f'{role["role_name"]}_secondary'] * 3) + (player_df[f'{role["role_name"]}_tertiary'] * 1)) / divisor ), 2)
return player_df return player_df
def calc_player_scores(player_df: pd.DataFrame): def calc_role_scores_for_tactic_roles(player_df: pd.DataFrame, tactic_roles: [dict]):
# TODO: Create objects for each role that can be used here. for role in tactic_roles:
player_df = calc_role_scores(player_df, goalkeeper) player_df = calc_role_scores(player_df, role)
# TODO: Add roles.
return player_df return player_df
if __name__ == "__main__": if __name__ == "__main__":
# Parse Input args
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument("-i", "--input-filepath", type=str) parser.add_argument("-i", "--input-filepath", type=str, help="Path to Input Html file")
parser.add_argument("-o", "--output-filepath", type=str) parser.add_argument("-o", "--output-filepath", type=str, help="Path to Export resultant Html file")
parser.add_argument("-r", "--roles", nargs='+', type=str, help="Space seperated list of roles for Evaluation")
args = parser.parse_args() args = parser.parse_args()
input_filepath = args.input_filepath input_filepath = args.input_filepath
output_filepath = args.output_filepath output_filepath = args.output_filepath
roles = args.roles
# Take Role arg and convert to list of role dictionaries
tactic_roles = []
for role in roles:
tactic_roles.append(globals()[role])
# Inport data, calculate scores for role, export results as html
player_df = load_html_data_to_dataframe(input_filepath) player_df = load_html_data_to_dataframe(input_filepath)
player_df = calc_player_scores(player_df) player_df = calc_role_scores_for_tactic_roles(player_df, tactic_roles)
export_html_from_dataframe(player_df, output_filepath) export_html_from_dataframe(player_df, output_filepath)