Six Nations Solver

🏉 Six Nations Solver is an optimisation tool for selecting the best fantasy team for the Six Nations Championship. It utilises Mixed-Integer Linear Programming (MILP) with Pyomo to maximise expected points while adhering to constraints such as budget, player positions, team balance, and special multipliers (captain, super-sub).

🏆 Features

• Optimised Team Selection: Selects the best 15-player squad plus substitutes while considering position and budget constraints.
• Customisable Constraints: Users can enforce specific players, exclude others, or set team-based limits.
• Captain & Super-Sub Multipliers: Includes special scoring rules such as captains (x2 points) and super-subs (x3 points).
• Data Filtering: Automatically excludes players outside specified cost bounds.
• Rich Output: Prints a formatted results table with player names, positions, teams, and expected points.
• Flexible Solver: Supports various solvers, including cplex, glpk, and gurobi.

📥 Installation

Ensure you have Python 3.8+ installed. Clone the repository and install dependencies:

$ git clone https://github.com/alexmgl/six_nations_solver.git
$ cd six_nations_solver
$ pip install -r requirements.txt

📊 Data Format

The input data should be in a CSV or DataFrame format with the following columns:

Column	Description
ID	Unique player ID
Name	Player name
Club	The Six Nations team (e.g., "France")
Position	Player's position (e.g., "PROP")
Value	Player cost (budget impact)
Points	Expected fantasy points

Players positions should be in the format: ["PROP", "HOOKER", "SECOND-ROW", "BACK-ROW", "SCRUM-HALF", "FLY-HALF", "CENTRE", "BACK-THREE"]

Example CSV (example_2025_gw1.csv):

ID,Name,Club,Position,Value,Points
74,A. Porter,Ireland,PROP,24,40
171,D. Fischetti,Italy,PROP,26,35
110,J. Marchand,France,HOOKER,27,45

🚀 Usage

1️⃣ Basic Usage (Custom Data)

from six_nations_solver import SixNationsSolver
import pandas as pd

# Load custom data
data = pd.read_csv("path_to_your_data.csv")

# Initialise solver
solver = SixNationsSolver(starting_budget=230, max_team_size=15, max_substitutes=1, max_same_team=4)

# Load player data
solver.load_data(data)

# Build optimisation model
solver.build_model()

# Solve the model
solver.solve(solver_name='cplex')

# Print results
solver.print_result()

2️⃣ Quick Test with Built-in Data (2025 gameweek 1 actual points)

from six_nations_solver import SixNationsSolver

# Initialise solver
solver = SixNationsSolver()

# Load built-in 2025 gameweek 1 data
solver.load_test_data()

# Build and solve the model
solver.build_model()
solver.solve(solver_name='cplex')

# Print results
solver.print_result()

3️⃣ Advanced Usage: Custom Constraints

solver = SixNationsSolver(
    starting_budget=225,         # Custom budget
    max_team_size=15,            # Limit team to 15 players
    max_substitutes=2,           # Allow 2 substitutes
    max_same_team=4,             # Max 4 players from the same country
    captain_multiplier=2,        # Captain earns double points
    super_sub_multiplier=3,      # Super sub earns triple points
    team_must_include=[101, 202], # Must include Sexton & Dupont
    team_must_exclude=[303]       # Exclude Maro Itoje
)

# Load player data
solver.load_data(data)

# Build optimisation model
solver.build_model()

# Solve the model
solver.solve(solver_name='cplex')

# Print results
solver.print_result()

🎛️ Configuration Parameters

The SixNationsSolver constructor allows customisation through various parameters:

Parameter	Default	Description
starting_budget	230	Maximum total team cost
max_team_size	15	Number of players in the squad
max_substitutes	1	Number of substitutes allowed
max_same_team	4	Maximum players per Six Nations team
captain_multiplier	2	Captain's points multiplier
super_sub_multiplier	3	Super-sub's points multiplier
team_must_include	None	List of player IDs required in the squad
team_must_exclude	None	List of player IDs to exclude
set_captain	None	Enforce a specific player as captain
set_super_sub	None	Enforce a specific player as super-sub

📜 Example Output

Upon solving, the solver prints a formatted table:

                 SIX NATIONS SOLVER (767.0 points)
┌───────┬───────────────────┬────────────┬──────────┬──────────────┐
│ Index │       Name        │  Position  │   Club   │    Points    │
├───────┼───────────────────┼────────────┼──────────┼──────────────┤
│  74   │     A. Porter     │    PROP    │ Ireland  │      24      │
│  171  │   D. Fischetti    │    PROP    │  Italy   │      26      │
│  110  │    J. Marchand    │   HOOKER   │  France  │      27      │
│  682  │    D. Jenkins     │ SECOND-ROW │  Wales   │      35      │
│  159  │    W. Rowlands    │ SECOND-ROW │  Wales   │      31      │
│  677  │ T. Reffell (SUB)  │  BACK-ROW  │  Wales   │ 87 (29 * 3)  │
│  351  │     R. Darge      │  BACK-ROW  │ Scotland │      52      │
│  150  │     T. Curry      │  BACK-ROW  │ England  │      50      │
│  118  │  G. Alldritt (C)  │  BACK-ROW  │  France  │ 142 (71 * 2) │
│  283  │  J. Gibson-Park   │ SCRUM-HALF │ Ireland  │      42      │
│  361  │     M. Smith      │  FLY-HALF  │ England  │      29      │
│  82   │     H. Jones      │   CENTRE   │ Scotland │      66      │
│  400  │   T. Menoncello   │   CENTRE   │  Italy   │      39      │
│  704  │ L. Bielle-Biarrey │ BACK-THREE │  France  │      41      │
│  686  │     C. Murley     │ BACK-THREE │ England  │      38      │
│ 1322  │   T. Attissogbe   │ BACK-THREE │  France  │      38      │
└───────┴───────────────────┴────────────┴──────────┴──────────────┘

• (C) → Captain (earns 2x points)
• (SUB) → Super Sub (earns 3x points)

🔧 Solver Options

The solver defaults to cplex, but you can use other solvers like:

solver.solve(solver_name='glpk')  # Open-source alternative
solver.solve(solver_name='gurobi')  # High performance commercial
# etc

Ensure the solver is installed on your system.

💡 Future Enhancements

• 📊 Graphical UI
• 🌍 Web App Version

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📌 Notes

• Ensure all dependencies are installed (pip install -r requirements.txt).
• The solver requires Pyomo and a compatible solver (e.g., CPLEX, GLPK, Gurobi).
• CSV input data should follow the format outlined above.