tfb-draftfast 1.0.0

A tool to automate and optimize DraftKings and FanDuel lineup construction.

Introduction

An incredibly powerful tool that automates and optimizes lineup building, allowing you to enter thousands of lineups in any DraftKings or FanDuel contest in the time it takes you to grab a coffee.

Installation

Requires Python 7.

pip install tfb-draftfast

Usage

Example usage

from draftfast import rules
from draftfast.optimize import run
from draftfast.orm import Player
from draftfast.csv_parse import salary_download

# Create players for a classic DraftKings game
player_pool = [
    Player(name='A1', cost=5500, proj=55, pos='PG'),
    Player(name='A2', cost=5500, proj=55, pos='PG'),
    Player(name='A3', cost=5500, proj=55, pos='SG'),
    Player(name='A4', cost=5500, proj=55, pos='SG'),
    Player(name='A5', cost=5500, proj=55, pos='SF'),
    Player(name='A6', cost=5500, proj=55, pos='SF'),
    Player(name='A7', cost=5500, proj=55, pos='PF'),
    Player(name='A8', cost=5500, proj=55, pos='PF'),
    Player(name='A9', cost=5500, proj=55, pos='C'),
    Player(name='A10', cost=5500, proj=55, pos='C'),
]

roster = run(
    rule_set=rules.DK_NBA_RULE_SET,
    player_pool=player_pool,
    verbose=True,
)

# Or, alternatively, generate players from a CSV
players = salary_download.generate_players_from_csvs(
  salary_file_location='./salaries.csv',
  game=rules.DRAFT_KINGS,
)

roster = run(
  rule_set=rules.DK_NBA_RULE_SET,
  player_pool=players,
  verbose=True,
)

You can see more examples in the examples directory.

Game Rules

Optimizing for a particular game is as easy as setting the RuleSet (see the example above). Game rules in the library are in the table below:

League	Site	Reference
NFL	DraftKings	DK_NFL_RULE_SET
NFL	FanDuel	FD_NFL_RULE_SET
NBA	DraftKings	DK_NBA_RULE_SET
NBA	FanDuel	FD_NBA_RULE_SET
MLB	DraftKings	DK_MLB_RULE_SET
MLB	FanDuel	FD_MLB_RULE_SET
WNBA	DraftKings	DK_WNBA_RULE_SET
WNBA	FanDuel	FD_WNBA_RULE_SET
PGA	FanDuel	FD_PGA_RULE_SET
NASCAR	FanDuel	FD_NASCAR_RULE_SET
SOCCER	DraftKings	DK_SOCCER_RULE_SET
EuroLeague	DraftKings	DK_EURO_LEAGUE_RULE_SET
NHL	DraftKings	DK_NHL_RULE_SET
NBA Pickem	DraftKings	DK_NBA_PICKEM_RULE_SET
NFL Showdown	DraftKings	DK_NFL_SHOWDOWN_RULE_SET
NBA Showdown	DraftKings	DK_NBA_SHOWDOWN_RULE_SET
MLB Showdown	DraftKings	DK_MLB_SHOWDOWN_RULE_SET

Note that you can also tune draftfast for any game of your choice even if it's not implemented in the library (PRs welcome!). Using the RuleSet class, you can generate your own game rules that specific number of players, salary, etc. Example:

from draftfast import rules

golf_rules = rules.RuleSet(
    site=rules.DRAFT_KINGS,
    league='PGA',
    roster_size='6',
    position_limits=[['G', 6, 6]],
    salary_max=50_000,
)

Settings

Usage example:

class Showdown(Roster):
    POSITION_ORDER = {
        'M': 0,
        'F': 1,
        'D': 2,
        'GK': 3,
    }


showdown_limits = [
    ['M', 0, 6],
    ['F', 0, 6],
    ['D', 0, 6],
    ['GK', 0, 6],
]

soccer_rules = rules.RuleSet(
    site=rules.DRAFT_KINGS,
    league='SOCCER_SHOWDOWN',
    roster_size=6,
    position_limits=showdown_limits,
    salary_max=50_000,
    general_position_limits=[],
)
player_pool = salary_download.generate_players_from_csvs(
    salary_file_location=salary_file,
    game=rules.DRAFT_KINGS,
)
roster = run(
    rule_set=soccer_rules,
    player_pool=player_pool,
    verbose=True,
    roster_gen=Showdown,
)

PlayerPoolSettings

• min_proj
• max_proj
• min_salary
• max_salary
• min_avg
• max_avg

OptimizerSettings

• stacks - A list of Stack objects. Example:

roster = run(
    rule_set=rules.DK_NHL_RULE_SET,
    player_pool=player_pool,
    verbose=True,
    optimizer_settings=OptimizerSettings(
        stacks=[
            Stack(team='PHI', count=3),
            Stack(team='FLA', count=3),
            Stack(team='NSH', count=2),
        ]
    ),
)

LineupConstraints

• locked - list of players to lock
• banned - list of players to ban
• groups - list of player groups constraints. See below

roster = run(
    rule_set=rules.DK_NFL_RULE_SET,
    player_pool=player_pool,
    verbose=True,
    constraints=LineupConstraints(
        locked=['Rob Gronkowski'],
        banned=['Mark Ingram', 'Doug Martin'],
        groups=[
            [('Todd Gurley', 'Melvin Gordon', 'Christian McCaffrey'), (2, 3)],
            [('Chris Carson', 'Mike Davis'), 1],
        ]
    )
)

• no_offense_against_defense - Do not allow offensive players to be matched up against defensive players in the optimized lineup. Currently only implemented for soccer, NHL, and NFL -- PRs welcome!

CSV Upload

from draftfast.csv_parse import uploaders

uploader = uploaders.DraftKingsNBAUploader(
    pid_file='./pid_file.csv',
)
uploader.write_rosters(rosters)

Support and Consulting

DFS optimization is only one part of a sustainable strategy. Long-term DFS winners have the best:

• Player projections
• Bankroll management
• Diversification in contests played
• Diversification across lineups (see draftfast.exposure)
• Research process
• 1 hour before gametime lineup changes
• ...and so much more

DraftFast provides support and consulting services that can help with all of these. Let's get in touch today.

Credits

Special thanks to Ben Brostoff, who authored this repo, which was the inspiration for this one.

Current project maintainers:

• BenBrostoff
• Drew