Elo-Point Example
[1]:
from ratingslib.datasets.filenames import dataset_path, FILENAME_NFL_2009_2010_FULLNAMES_GAMES_AND_PLAYOFFS
from ratingslib.ratings.elo import Elo
from ratingslib.utils.enums import ratings
filename = dataset_path(FILENAME_NFL_2009_2010_FULLNAMES_GAMES_AND_PLAYOFFS)
Elo(version=ratings.ELOPOINT, K=32, ks=1000, HA=0, starting_point=0).rate_from_file(filename, sort=True)
[1]:
| Item | rating | ranking | |
|---|---|---|---|
| 11 | Green Bay Packers | 58.825302 | 1 |
| 19 | Minnesota Vikings | 55.217485 | 2 |
| 21 | New Orleans Saints | 49.494602 | 3 |
| 23 | New York Jets | 47.215011 | 4 |
| 8 | Dallas Cowboys | 43.073833 | 5 |
| 2 | Baltimore Ravens | 40.357218 | 6 |
| 16 | Los Angeles Chargers | 39.973859 | 7 |
| 13 | Indianapolis Colts | 39.259961 | 8 |
| 20 | New England Patriots | 37.860373 | 9 |
| 27 | San Francisco 49ers | 33.188766 | 10 |
| 12 | Houston Texans | 18.446528 | 11 |
| 1 | Atlanta Falcons | 18.386510 | 12 |
| 25 | Philadelphia Eagles | 13.983536 | 13 |
| 26 | Pittsburgh Steelers | 9.130836 | 14 |
| 0 | Arizona Cardinals | 6.121626 | 15 |
| 4 | Carolina Panthers | 5.259553 | 16 |
| 9 | Denver Broncos | 4.100567 | 17 |
| 6 | Cincinnati Bengals | -0.750144 | 18 |
| 22 | New York Giants | -3.509664 | 19 |
| 18 | Miami Dolphins | -9.312180 | 20 |
| 30 | Tennessee Titans | -9.835065 | 21 |
| 5 | Chicago Bears | -16.050125 | 22 |
| 3 | Buffalo Bills | -23.286610 | 23 |
| 31 | Washington Redskins | -29.039372 | 24 |
| 15 | Kansas City Chiefs | -34.646617 | 25 |
| 28 | Seattle Seahawks | -35.149954 | 26 |
| 14 | Jacksonville Jaguars | -37.050120 | 27 |
| 7 | Cleveland Browns | -47.088786 | 28 |
| 29 | Tampa Bay Buccaneers | -54.373374 | 29 |
| 24 | Oakland Raiders | -62.651750 | 30 |
| 10 | Detroit Lions | -72.800257 | 31 |
| 17 | Los Angeles Rams | -84.351547 | 32 |