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FPL Statistics UI App
Release v1.6
Ilias Charitos
Aug 02, 2021TABLE OF CONTENTS:
1 Readme 3
1.1 Changelog in Version 1.8.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 EXECUTABLE AVAILABLE!! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Code setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.5 Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
2 Environment Requirements 5
3 License 7
4 Algorithmic Model 9
4.1 Mathematical modelling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9
5 best_15_optimisation module 11
6 FPLController module 13
7 FPLModel module 15
8 FPLViewer module 17
9 main module 19
10 Indices and tables 21
Python Module Index 23
Index 25
iii
FPL Statistics UI App, Release v1.6 Below you can find the scripts that make up the application and the documentation of their classes and functions. You will also find the README, Environment Requirements and LICENCE docs. TABLE OF CONTENTS: 1
FPL Statistics UI App, Release v1.6 2 TABLE OF CONTENTS:
CHAPTER
ONE
README
This is a python application providing users with a GUI in order to download the FPL database by using the FPL API
URL and make statistical calculations.
1.1 Changelog in Version 1.8.0
• Reverted to PyQt5 due to PyQt6 failing auto docs and pyinstaller build.
• Added Archive folder that stores the databases of previous years.
• Restructured GUI to use Tabs for different app features (enabling more space for future features).
1.2 Features
• Graphical Interface
• Info bar for interesting stats
• Download and save useful data from FPL database
• Save and load database to/from local JSON file for OFFLINE use
• Show sorted statistics based on your selection
• Calculate best 15 selection using mathematical engine solver optimization
• Calculate most valuable players
• Calculate most valuable position
• Calculate most valuable team
• Save data in CSVs
3FPL Statistics UI App, Release v1.6
1.3 EXECUTABLE AVAILABLE!!
You can download the zip containing the application’s executable if you don’t care about the code. Just download the
FPL_Statistics_UI zip and double click the FPL_Python_Stats.exe inside it. Enjoy!
1.4 Code setup
1. Create a python virtual environment.
2. Install the required dependencies by executing: pip install -r requirements.txt
3. Then you execute the main.py file either from an IDE or from CMD running: python fpls_ui_app/main.py
To build the application into an executable the following command was used: pyinstaller –onedir –windowed
–add-data “C:/Users/. . . /Lib/site-packages/pulp;pulp/” -n FPL_Python_Stats fpls_ui_app/main.py
1.5 Support
If you have new ideas on features you would like feel free to either send an email to ilias4780@gmail.com or jump into
the code yourself building it. You can also use the Issues page of Github.
4 Chapter 1. ReadmeCHAPTER
TWO
ENVIRONMENT REQUIREMENTS
• PyQt5
• numpy
• pandas
• pulp
• requests
5FPL Statistics UI App, Release v1.6 6 Chapter 2. Environment Requirements
CHAPTER
THREE
LICENSE
MIT License
Copyright (c) 2020-2021 Ilias Charitos
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documen-
tation files (the “Software”), to deal in the Software without restriction, including without limitation the rights to use,
copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom
the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the
Software.
THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED,
INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PAR-
TICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFT-
WARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
7FPL Statistics UI App, Release v1.6 8 Chapter 3. License
CHAPTER
FOUR
ALGORITHMIC MODEL
The mathematical problem that the best 15 optimisation solves is a MIP problem of maximizing the objective value
selected by the user (selection between: Value, Form, Total Point, ICT Index), while also respecting the following
constraints:
1. Maximum of 3 players can be selected by each team.
2. Exactly 2 Goalkeepers, 5 Defenders, 5 Midfielders and 3 Forwards should be selected.
3. Cost of players selected has a maximum of 100 units.
4.1 Mathematical modelling
• Pi: player of team i
• G: goalkeeper - binary
• D: defender - binary
• M: midfielder - binary
• F: forward - binary
• T: set of teams
• Cp: cost of player
• Vp: objective value of player
• Pi {G, D, M, F}
• (Pi) = 2G + 5D + 5M + 3F
• (Pi * Cp)FPL Statistics UI App, Release v1.6 10 Chapter 4. Algorithmic Model
CHAPTER
FIVE
BEST_15_OPTIMISATION MODULE
Source file that holds the model formulation of the best 15 players optimization problem.
Functions in the source file:
• find_best_15_players_by_value(): Calculates the best 15 player selection according to the
value passed as an argument.
• OptimizationValuesAllZeroError(): Exception for when the values chosen to be used as the
main optimization values in find_best_15_players_by_value() are all zero.
exception best_15_optimisation.OptimizationValuesAllZeroError
Bases: Exception
Exception for when the values chosen to be used as the main optimization values in
find_best_15_players_by_value() are all zero. This would technically happen only in the pre sea-
son period when for example ‘Form’ is zero for all players.
best_15_optimisation.find_best_15_players_by_value(player_names, player_positions, player_values,
player_prices, player_teams, opt_target)
Calculates the best 15 player selection according to the value passed as an argument. Uses the PULP library and
default CBC solver. It satisfies the max 3 players per team constraint and the 100 cost constraint.
Parameters
• player_names – list of the player names
• player_positions – list of the player positions
• player_values – list of the player values
• player_prices – list of the player prices
• player_teams – list of the player teams
• opt_target – string containing the optimization target (the target value)
Returns two pandas dataframes, first containing the players and their details, the second the opti-
mization information
11FPL Statistics UI App, Release v1.6 12 Chapter 5. best_15_optimisation module
CHAPTER
SIX
FPLCONTROLLER MODULE
Source file that holds the controller of the application. All the logic of the application and the use of the GUI elements
lies here.
Classes in the source file:
• Controller(): Class that holds all the logic of the application and the manipulation of the GUI elements
that the FPLViewer source file holds.
class FPLController.Controller(main_window)
Bases: object
Class that holds all the logic of the application and the manipulation of the GUI elements that the FPLViewer
source file holds.
calculate_best_15_players()
Calculate and display the best 15 players selection based on the criteria selected by the user.
display_most_valuable_position()
Create a table view with the most valuable positions.
display_most_valuable_teams()
Create a table view with the most valuable teams.
display_sorted_statistics()
Sort the table view with the player statistics.
get_fpl_database_in_json()
Get the FPL database using the FPL’s API.
static get_sep_data_from_results(results, statistics)
Separate the results returned by the optimization and bring it in a format suitable for display.
Parameters
• results – pandas dataframe containing the results of the optimization
• statistics – pandas dataframe containing the statistics of the optimization process
Returns lists containing the goalkeepers, defenders, midfielders and forwards returned by the
optimization, plus a list containing the statistics of the optimization process
load_database_from_file()
Load Offline the FPL data from a JSON file selected by the user.
process_data()
Extract the parts that we want to keep from the downloaded data and process them.
save_database_to_file()
Save the downloaded FPL data to a JSON in a selected directory by the user.
13FPL Statistics UI App, Release v1.6
save_df_for_view_to_csv()
Save the table view dataframe to a CSV in a selected directory by the user.
save_useful_player_attributes_df_to_csv()
Save the useful player attributes dataframe to a CSV in a selected directory by the user.
show_player_statistics()
Create a table view with the player statistics.
14 Chapter 6. FPLController moduleCHAPTER
SEVEN
FPLMODEL MODULE
Source file that holds the table view model of the window.
Classes in the source file:
• TableViewModel(): Class that holds all the logic of the application and the manipulation of the GUI elements
that the FPLViewer source file holds.
class FPLModel.TableViewModel(data)
Bases: PyQt5.QtCore.QAbstractTableModel
The table view model that is used by the application to display the various dataframes.
columnCount(parnet=None)
Return the column count of the dataframe to display.
Parameters parnet – (Default value = None)
data(index, role=0)
Return the data according to index passed.
Parameters
• index –
• role – (Default value = Qt.DisplayRole)
headerData(col, orientation, role)
Return the header data.
Parameters
• col –
• orientation –
• role –
rowCount(parent=None)
Return the row count of the dataframe to display.
Parameters parent – (Default value = None)
15FPL Statistics UI App, Release v1.6 16 Chapter 7. FPLModel module
CHAPTER
EIGHT
FPLVIEWER MODULE
Source file that holds the viewer of the application. All the GUI elements are structured here and ready to be picked
up and used by the controller.
Classes in the source file:
• MainWindow(): Class that holds the main window used in the application’s GUI.
class FPLViewer.MainWindow(parent=None)
Bases: PyQt5.QtWidgets.QMainWindow
Class that holds the main window used in the application’s GUI.
set_best15_players_template(gks, defs, mfs, fwds, stats)
Sets the players and stats of the best 15 players template.
Parameters
• gks – list of the goalkeepers
• defs – list of the defenders
• mfs – list of the midfielders
• fwds – list of the forwards
• stats – statistics of the optimisation
set_info_displays(gw, deadline)
Creates the information display of the main window. :param gw: :param deadline:
set_status_display_text(text)
Sets the display text to the status display.
Parameters text – Text to be set to the status display.
set_table_view(df )
Sets the dataframe model to the table view.
Parameters df – Dataframe to be set to the table view
17FPL Statistics UI App, Release v1.6 18 Chapter 8. FPLViewer module
CHAPTER
NINE
MAIN MODULE
Source file that holds the main application that instantiates the classes and runs the GUI.
Classes in the source file:
• main(): The main application that instantiates the classes and produces the GUI.
main.main()
The main application that instantiates the classes and produces the GUI.
19FPL Statistics UI App, Release v1.6 20 Chapter 9. main module
CHAPTER
TEN
INDICES AND TABLES
• genindex
• modindex
• search
21FPL Statistics UI App, Release v1.6 22 Chapter 10. Indices and tables
PYTHON MODULE INDEX
b
best_15_optimisation, 11
f
FPLController, 13
FPLModel, 15
FPLViewer, 17
m
main, 19
23FPL Statistics UI App, Release v1.6 24 Python Module Index
INDEX
B M
best_15_optimisation main
module, 11 module, 19
main() (in module main), 19
C MainWindow (class in FPLViewer), 17
calculate_best_15_players() (FPLCon- module
troller.Controller method), 13 best_15_optimisation, 11
columnCount() (FPLModel.TableViewModel method), FPLController, 13
15 FPLModel, 15
Controller (class in FPLController), 13 FPLViewer, 17
main, 19
D
data() (FPLModel.TableViewModel method), 15 O
display_most_valuable_position() (FPLCon- OptimizationValuesAllZeroError, 11
troller.Controller method), 13
display_most_valuable_teams() (FPLCon- P
troller.Controller method), 13 process_data() (FPLController.Controller method),
display_sorted_statistics() (FPLCon- 13
troller.Controller method), 13
R
F rowCount() (FPLModel.TableViewModel method), 15
find_best_15_players_by_value() (in module
best_15_optimisation), 11 S
FPLController save_database_to_file() (FPLController.Controller
module, 13 method), 13
FPLModel save_df_for_view_to_csv() (FPLCon-
module, 15 troller.Controller method), 13
FPLViewer save_useful_player_attributes_df_to_csv()
module, 17 (FPLController.Controller method), 14
set_best15_players_template()
G (FPLViewer.MainWindow method), 17
get_fpl_database_in_json() (FPLCon- set_info_displays() (FPLViewer.MainWindow
troller.Controller method), 13 method), 17
get_sep_data_from_results() (FPLCon- set_status_display_text()
troller.Controller static method), 13 (FPLViewer.MainWindow method), 17
set_table_view() (FPLViewer.MainWindow method),
H 17
headerData() (FPLModel.TableViewModel method), 15 show_player_statistics() (FPLCon-
troller.Controller method), 14
L
load_database_from_file() (FPLCon- T
troller.Controller method), 13 TableViewModel (class in FPLModel), 15
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