Overperforming in Davis Cup

This is a guest post by Peter Wetz.

With the help of weighted surface specific Elo ratings we have a powerful new tool to measure player performance. The traditional conclusion of the tennis season, the Davis Cup final, provides us with an opportunity once again to examine which players thrive when competing for their nation and which players seem to suffer from the pressure. While we are at it, I don’t like the sound of the word offseason. After all, there are still ITF tournaments, not to mention the Australian Open Asia-Pacific Wildcard Play-offs.

As already hinted, Elo ratings have proven to represent a better picture of player quality than traditional ATP rankings. Hence, comparing expected wins based on Elo with actual wins provides us with a clearer picture of who outperforms expectations and who does not.

In this evaluation, I consider completed World Group and Group 1 Davis Cup live rubbers played since 1980. The data set contains around 5000 matches through this year’s World Group Quarterfinals, and I’ve limited my focus to players having played 15 or more matches.

Let’s first take a glance at the obvious stat, win-loss percentage. The following table shows the top ten win-loss records of all players under consideration. (The Active column denotes if the player is still an active player).

Name	        W	L	Perc	Active
Rafael Nadal	20	1	95%	1
Boris Becker	31	2	94%	0
Andy Murray	25	3	90%	1
Balazs Taroczy	23	3	89%	0
David Ferrer	20	3	87%	1
Andre Agassi	23	4	85%	0
Roger Federer	40	7	85%	1
Novak Djokovic	27	5	84%	1
Guillermo Vilas	16	3	84%	0
Andrei Medvedev	16	3	84%	0

As one would expect, the big four and other all time greats are included. However, this obviously does not tell the whole story. Rafael Nadal is expected to win most of the time and that is what he does. For such a player, it is hard to outperform expectations.

If we compute how much a player outperforms his expectations, we get a clearer picture, given we want to know who does especially well in Davis Cup. Expected wins are calculated based on a half-and-half mix of surface specific Elo and overall Elo as this, in general, provides close to the best results, as pointed out in a previous article.

The tables below show the top and bottom five among all (first table) and active (second table) players in terms of over and underperforming expected wins. It shows actual wins (W), expected wins (eW), the percentage of over or underperformance (+/-), and if a player is still active.

Name	         W	eW	+/-	active
Francisco Maciel 11	6	72%	0
Slobodan Zi'vic  20	11	72%	0
Vasek Pospisil	 9	5	71%	1
Adrian Ungur	 6	3	56%	1
Mahesh Bhupathi	 5	3	55%	0
Wally Masur	 7	10     -31%	0
Sebastien Lareau 7	10     -31%	0
James Blake	 7	10     -36%	0
Nicolas Kiefer	 6	10     -40%	0
Aqeel Khan	 2	4      -57%	0
Name	        W	eW	+/-	Active
Vasek Pospisil	9	5	71%	1
Adrian Ungur	6	3	56%	1
Andrey Golubev	13	8	46%	1
Di Wu	        14	9	45%	1
Steve Darcis	15	11	35%	1
Florian Mayer	7	8      -14%	1
Gilles Muller	9	10     -15%	1
Alejandro Falla	8	9      -17%	1
John Isner	9	11     -19%	1
Jurgen Melzer	20	25     -22%	1

The tables seem to overlap with some conventional wisdom floating through the tennis sphere. Namely, that Steve Darcis, despite his recent losses at the Davis Cup final, plays above expectations. Also, Jurgen Melzer is known for regularly disappointing Austrian Davis Cup fans. (In his defense, he created several moments of joy, too).

If we were to pick a Davis Cup hero for the active and inactive group of players, Slobodan Zivojinovic and Andrey Golubev seem to be good choices. Golubev has a record of 13-6 (68%) and outperforms expected wins by 46%. He provides a good combination of consistently beating players he should beat and scoring more than his share of exceptional upsets (Wawrinka 2014, Goffin 2014, Melzer 2013 and Berdych 2011).

Zivojinovic provides a similar pattern with a record of 20-8 (71%), 72% better than expected. He tallied six wins out of ten matches in which Elo assigned him a win probability of less than 25%. Further, he only lost one match in when his pre-match odds of winning were greater than 35%.

This post provides insight into how Elo ratings help in quantifying a player’s performance. We identified players who have (not) shown great improvement on what the algorithm expected based on results from the regular tour. For future research it would be interesting to delve into Davis Cup doubles heroes: Where there are no dead rubbers, stakes are always high.

Peter Wetz is a computer scientist interested in racket sports and data analytics based in Vienna, Austria.