JFPL Optimization

This is a program for selecting/planning Fantasy Premier League picks using mathematical optimization.

The code is a Julia implementation of a Python FPL optimization repository

The program relies on JuMP to easily swap between different solvers.

Installation

• Clone the repository

git clone https://github.com/TDRoss/JFPL-Optimization JFPL-Optimization

• Navigate to the run directory

cd JFPL-Optimization/run

• Launch Julia then enter the package REPL mode by pressing ]. Activate the project environment

activate .

(Note that on Windows launching Julia may start in your home directory. Check with pwd(). You may need to navigate back to JFPL-Optimization/run using cd())

• Install dependencies (this can take a while)

instantiate

• Download FPLReview projections and save it in the directory /data and rename the projections file to fplreview.csv

• Log in FPL from your browser and open https://fantasy.premierleague.com/api/my-team/MY_TEAM_ID/ after replacing MY_TEAM_ID with your team id. Copy the content of the page into data/team.json file, by creating one.

Note: HiGHS (default) is installed with this project. If you would like to try other solvers, please see the JuMP documentation on what is available and their installation dependencies.

Instructions

Multi-period GW optimization

• Edit content of data/regular_settings.json file

   {
   	"horizon": 8,
   	"decay_base": 0.84,
   	"ft_value": 0.8,
   	"ft_value_list": {},
   	"ft_use_penalty": 1,
   	"itb_value": 0.08,
   	"itb_loss_per_transfer": 0,
   	"no_future_transfer": false,
   	"no_transfer_last_gws": null,
   	"no_transfer_by_position": null,
   	"force_ft_state_lb": [],
   	"force_ft_state_ub": [],
   	"have_2ft_in_gws": [],
   	"randomized": false,
   	"xmin_lb": 2,
   	"ev_per_price_cutoff": 20,
   	"bench_weights": {"0": 0.03, "1": 0.21, "2": 0.06, "3": 0.002},
   	"banned": [],
   	"banned_next_gw": [],
   	"locked": [],
   	"locked_next_gw": [],
   	"single_solve": false,
   	"forced_chip_gws": {"bb": [], "wc": [], "fh": [], "tc": []},
   	"run_chip_combinations": {"bb": [], "wc": [], "fh": [], "tc": []},
   	"num_transfers": null,
   	"hit_limit": null,
   	"weekly_hit_limit": null,
   	"hit_cost": 4,
   	"ft_custom_value": null,
   	"use_wc": null,
   	"use_bb": null,
   	"use_fh": null,
   	"chip_limits": {"bb": 0, "wc": 0, "fh": 0, "tc": 0},
   	"no_chip_gws": [],
   	"allowed_chip_gws": {"bb": [], "wc": [], "fh": [], "tc": []},
   	"future_transfer_limit": null,
   	"no_transfer_gws": [],
   	"booked_transfers": [],
   	"only_booked_transfers": false,
   	"no_trs_except_wc": false,
   	"preseason": false,
   	"no_opposing_play": false,
   	"opposing_play_group": "position",
   	"opposing_play_penalty": 0.5,
   	"pick_prices": {"G": "", "D": "", "M": "", "F": ""},
   	"no_gk_rotation_after": null,
   	"max_defenders_per_team": 3,
   	"double_defense_pick": false,
   	"iteration": 1,
   	"iteration_criteria": "this_gw_transfer_in",
   	"iteration_target": [],
   	"report_decay_base": [0.85, 0.9, 0.95, 1.0, 1.017],
   	"datasource" : "review",
   	"data_weights": {"review": 40, "review-odds": 30, "mikkel": 30, "kiwi": 0},
   	"export_data": "final.csv",
   	"team_data": "json",
   	"team_id": null
   }

  • horizon: length of planning horizon
  • decay_base: value assigned to decay rate of expected points
  • ft_value: value assigned to the extra free transfer
  • ft_value_list: values of rolling FTs in different states, for example
    "ft_value_list": {"2": 2.1, "3": 1.8, "4": 1.5, "5": 1.1}
    assigns a value of 2.1 for rolling from 1FT to 2FTs, 1.8 value for rolling from 2FTs to 3FTs, etc...
  • ft_use_penalty: penalty on objective function when an FT is used
    this parameter ensures that no future transfer (excluding this GW) is scheduled unless the gain is above this threshold
  • itb_value: value assigned to having 1.0 extra budget
  • itb_loss_per_transfer: reduction in ITB amount per scheduled transfers in future
  • no_future_transfer: true or false whether you want to plan future transfers or not
  • no_transfer_last_gws: the number of gws at the end of the period you want to ban transfers
  • force_ft_state_lb: list of GWs and minimum number of FTs to force to have (format is (GW, state))
    "force_ft_state":[[4,3], [7,2]] will force solver to have at least 3 FTs in GW4, and 2 FTs in GW7
  • force_ft_state_ub: list of GWs and maximum number of FTs to force to have (format is (GW, state))
    "force_ft_state":[[4,4], [7,3]] will force solver to have at most 4 FTs in GW4, and 3 FTs in GW7
  • have_2ft_in_gws: list of GWs where you want to have 2 FTs, for example
    "have_2ft_in_gws":[38] will force solver to have 2 FTs at the beginning of GW38
  • randomized: true or false whether you would like to add random noise to EV
  • xmin_lb: cut-off for dropping players below this many minutes expectation
  • ev_per_price_cutoff: cut-off percentile for dropping players based on total EV per price (e.g. 20 means drop players below 20% percentile)
  • bench_weights: percentage weights in objective for bench players (gk and 3 outfield). Example: {"0":0.01,"1":0.3,"2":0.1,"3":0.05},
  • banned: list of player IDs to be banned over the entire horizon
  • banned_next_gw: list of player IDs to be banned for the next gameweek. Alternatively, you can supply an [ID, gameweek] list as an element of the list to ban a player just for one specific gameweek. E.g. [100, [200, 32]] bans player with ID 100 for the next gameweek, and bans player with ID 200 for gameweek 32
  • locked: list of player IDs to always have during the horizon (e.g. 233 for Salah)
  • locked_next_gw: List of player IDs to force just for the next gameweek. See banned_next_gw for extended usage
  • future_transfer_limit: upper bound how many transfers are allowed in future GWs
  • no_transfer_gws: list of GW numbers where transfers are not allowed
  • no_transfer_by_position: list of positions to not transfer in/out. Valid positions: ["G", "D", "M", "F"]. E.g. to block out goalkeeper transfers set this option to ["G"]
  • booked_transfers: list of booked transfers for future gameweeks, needs to have a gw key and at least one of transfer_in or transfer_out with the player ID. For example, to book a transfer of buying Kane (427) on GW5 and selling him on GW7, use
    "booked_transfers": [{"gw": 5, "transfer_in": 427}, {"gw": 7, "transfer_out": 427}]
  • only_booked_transfers: (for next GW) use only booked transfers
  • use_wc: GW to use wildcard (fixed)
  • use_bb: GW to use bench boost (fixed)
  • use_fh: GW to use free hit (fixed)
  • use_tc: GW to use triple captain (fixed)
  • chip_limits: how many chips of each kind can be used by solver (you need to set it to at least 1 when force using a chip)
  • no_chip_gws: list of GWs to ban solver from using a chip
  • allowed_chip_gws: dictionary of list of GWs to allow chips to be used. For example
    "allowed_chip_gws": {"wc": [27,31]}
    will allow solver to use WC in GW27 and GW31, but not in another GW
  • forced_chip_gws: dictionary of list of GWs to force chips to be used. Instead of 'allowing' chips, it makes sure that chips are used
  • run_chip_combinations: generates a list of chip combinations to be tried one-by-one, instead of leaving to the solver
  • num_transfers: fixed number of transfers for this GW
  • hit_limit: limit on total hits can be taken by the solver for entire horizon
  • weekly_hit_limit: limit on hits solver can take in a single GW
  • hit_cost: cost of a hit, 4 points by default but can be overriden to reduce hits suggested
  • ft_custom_value: value of keeping your 2nd free transfer before a GW. For example
    "ft_custom_value": {"35": 2, "38": 0.5}
    will set value of 2nd FT for GW35 to 2 EV, and for GW38 to 0.5 EV
  • preseason: solve flag for GW1 where team data is not important
  • no_trs_except_wc: when true prevents solver to make transfers except using wildcard
  • no_opposing_play: controls the level of cross-playing players in the lineup
    • true if you do not want to have players in your lineup playing against each other in a GW
    • false if you do not want to use this option
    • "penalty" if you want to penalize each instance with a static value
  • opposing_play_group: all if you do not want any type of opposing players or position if you only don't want your offense playing against your defense
  • opposing_play_penalty: if "penalty" is chosen in no_opposing_play option, this penalty is deducted from the objective for each cross-play
  • pick_prices: price points of players you want to force in a comma separated string For example, to force two 11.5M forwards, and one 8M midfielder, use "pick_prices": {"G": "", "D": "", "M": "8", "F": "11.5,11.5"}
  • no_gk_rotation_after: use same lineup GK after given GW, e.g. setting this value to 26 means all GWs after 26 will use same lineup GK
  • max_defenders_per_team: the maximum number of defenders and goalkeepers from one team in your squad, defaults to 3
  • double_defense_pick: forces solver to use either 0 or more than 2 defender/goalkeeper from each team
  • iteration: number of different solutions to be generated, the criteria is controlled by iteration_criteria
  • iteration_criteria: rule on separating what a different solution mean
    • this_gw_transfer_in will force to replace players to buy current GW in each solution
    • this_gw_transfer_out will force to replace players to sell current GW in each solution
    • this_gw_transfer_in_out will force to replace players to buy or sell current GW in each solution
    • chip_gws will force to replace GWs where each chip is being used
    • target_gws_transfer_in will force to replace players to buy in target GW (provided by iteration_target parameter)
    • this_gw_lineup will force to replace at least N players in your lineup
    • iteration_difference: number of players to be different (only available for this_gw_lineup criteria for now)
  • iteration_target: list of GWs where plans will be forced to replace in each iteration
  • report_decay_base: list of decay bases to be measured and reported at the end of the solve
  • datasource : review, kiwi, mikkel or avg specifies the data to be used.
    • review requires fplreview.csv file
    • review-odds requires fplreview-odds.csv file
    • kiwi requires kiwi.csv file
    • mikkel requires TransferAlgorithm.csv, file
    • mixed requires an additional parameter data_weights, and any corresponding files mentioned above under data folder to be present
  • data_weights: weight percentage for each data source, given as a dictionary, where keys should be one of valid data sources
  • export_data: option for exporting final data as a CSV file (when using mixed data)
  • team_data: option for using team_id value rather than the team.json file. Uses team.json by default, set value to ID to use team_id. Note that with this method, any transfers already made this gameweek won't be taken into account, so they must be added to booked_transfers
  • team_id: the team_id to optimise for. Requires team_data to be set to ID

• Run the multi-period optimization From the bash command line in the /run directory

   julia --project=.  solve_regular.jl

• Find the optimal plans under /data/results directory with timestamp

Sensitivity Analysis

If you want to run sensitivity analysis:

0. Make sure that /data/results directory is empty (doesn't include old files)

1. Go to the /run directory and enter:

julia --project=. simulations.jl

When called from the terminal, it will ask you to give the number of runs (how many times you want to solve) and the number of parallel jobs. If you are not sure, use 1 for parallel jobs.

You can also pass parameters from the command line as:

julia --project=. simulations.jl --no 10 --parallel 4

2. After optimizations are completed, run:

julia --project=. sensitivity.jl

to get a summary of results.

Similarly, you can give gameweek and wildcard parameters from the command line, such as

julia --project=. sensitivity.jl --gw 1 --wildcard Y

License

Apache-2.0 License