A tool to automate and optimize DraftKings and FanDuel lineup construction.
Project description
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 3.6.
pip install draftfast
Usage
Example usage (you can experiment with these examples in repl.it):
from draftfast import rules
from draftfast.optimize import run
from draftfast.orm import Player
from draftfast.csv_parse import salary_download
# Create players
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,
)
# 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 |
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
nhl_rules = rules.RuleSet(
site=rules.DRAFT_KINGS,
league='NHL',
roster_size='9',
position_limits=[['C', 9, 9]],
salary_max=50_000,
)
Settings
Usage example:
roster = run(
rule_set=rules.DK_SOCCER_RULE_SET,
player_pool=player_pool,
player_settings=PlayerPoolSettings(
locked=['Maxi Gomez'],
),
optimizer_settings=OptimizerSettings(
no_offense_against_defense=True,
),
verbose=True,
)
PlayerPoolSettings
locked
- list of players to lockbanned
- list of players to banmin_proj
max_proj
min_salary
max_salary
min_avg
max_avg
OptimizerSettings
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 (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 swanson, who authored this repo, which was the inspiration for this one.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.