After reading FiveThirtyEight's piece about how Serena Williams stacks up against all-time female greats using the Elo rating system, I attempted to apply the same rating system to men's tennis with Python. FiveThirtyEight applied the elo rating system to men's tennis as well.
The Elo Rating system was developed by Arpad Elo originally to estimate the strength of chess players. Each player's elo rating is based on their prior results. When two chess players enter a match, the system can calculate the expected outcome using each player's rating and then updates each player's rating once the match has concluded.
- Match and player data comes from Jeff Sackmann's ATP Results csv files
- Each player starts with an elo rating of 1500
- The paramaeters of the K factor (determines the fluctuation of a player's rankings) comes from the recommendation of FiveThirtyEight
| Rank | Player Name | Peak Elo | Peak Elo Date |
|---|---|---|---|
| 1 | Novak Djokovic | 2538 | 2015-05-24 |
| 2 | Roger Federer | 2536 | 2007-02-26 |
| 3 | John McEnroe | 2501 | 1985-04-01 |
| 4 | Rafael Nadal | 2495 | 2013-09-30 |
| 5 | Bjorn Borg | 2483 | 1980-08-11 |
| 6 | Ivan Lendl | 2467 | 1986-03-24 |
| 7 | Boris Becker | 2390 | 1990-03-05 |
| 8 | Andy Murray | 2382 | 2009-04-12 |
| 9 | Pete Sampras | 2381 | 1994-05-09 |
| 10 | Jimmy Connors | 2372 | 1978-10-31 |
Taking these top ten players, we will then look at their respective elo ratings throughout their careers.
