Dominic Thiem and Reversible Blowouts

A few weeks ago in Rome, Dominic Thiem got destroyed by Novak Djokovic, 6-1 6-0. It was a letdown after Thiem’s previous-round upset of Rafael Nadal, and it seemed to provide a reminder of the old adage that tennis is about matchups. Even someone good enough to beat the King of Clay might struggle against a different sort of opponent.

Those struggles didn’t last. On Wednesday, Thiem faced Djokovic again, this time in the French Open quarterfinals, and won in straight sets. In less than three weeks, the Austrian bounced back from a brutal loss to defeat one of the greatest players of all time.

I’ve written before about the limited value of head-to-head records: When the head-to-head suggests that one player will win but the rankings disagree, the rankings prove to be the better forecaster. More sophisticated rating systems such as Elo would presumably do better still, though I haven’t done that exact test. There are certainly individual cases in which something specific about a matchup casts doubt on the predictiveness of the rankings, but if you have to pick one or the other, head-to-heads are the loser.

What about blowouts? Going into Wednesday’s quarterfinal, my surface-specific Elo ratings suggested that Thiem had a 26% chance of scoring the upset. The recent 6-1 6-0 loss was factored into those numbers, but only as a loss–there’s no consideration of severity. Should we have been even more skeptical of Thiem’s chances, given the most recent head-to-head result?

As it turns out, Thiem is far from the first player to turn things around after such a nasty scoreline. The most famous example is Robin Soderling, who lost 6-1 6-0 to Nadal in Rome in 2009, then bounced back to register one of the biggest upsets in tennis history, knocking out Rafa at Roland Garros. Few recoveries are so dramatic, but there are hundreds more.

Most players who lose lopsided scorelines–for today’s purposes, I’m considering any match in which the loser won two games or fewer–never get a chance to redeem themselves. I found roughly 2250 such matches in the ATP’s modern era, and the same two players met again less than half of those times. The fact that the head-to-head continues is a signal itself: Mediocre players–the ones you’d expect to lose badly–don’t get another chance. Even some top-20 players rarely meet each other on court, so the sort of player who earns the chance for redemption might have already proven that his lopsided loss was just an off day.

Of the 951 occasions that a player loses badly and faces the same opponent again, he gets revenge and wins the next match 277 times–about 29%. Crazy as it sounds, if the only thing we knew about Djokovic and Thiem entering Wednesday’s match was that Djokovic had won the last match 6-1 6-0, our base forecast would’ve been pretty close to the 26% that the much-more sophisticated Elo algorithm offered us.

29% is much higher than I expected, but it is lower than the typical rate for players in this situation. I found all head-to-heads of at least two meetings, and for every match after the first, counted whether it maintained or reversed the previous result. In addition to isolating lopsided scores, I also considered matches in which the loser won a set, on the assumption that those might be tighter matchups. Finally, for each of those categories, I tracked whether the follow-up matches were on the same surface as the previous one. Here are the results, with all win percentages shown from the perspective of the player who, like Thiem, lost the first encounter:

Score     Next Surface  Matches   Wins  Win %  
Any loss  All             68128  26586  39.0%  
Any loss  Same            31084  11855  38.1%  
Any loss  Diff            37044  14731  39.8%  
Bad loss  All               951    277  29.1%  
Bad loss  Same              457    128  28.0%  
Bad loss  Diff              494    149  30.2%  
Won set   All             26075  11286  43.3%  
Won set   Same            11766   4974  42.3%  
Won set   Diff            14309   6312  44.1%

The chances of recovering from a bad loss are better than I thought, but they are considerably worse than the odds that a player reverses the result after a less conspicuous scoreline–39%. The table also shows that the player seeking revenge is more likely to get it if the opportunity arises on a different surface, though not by a wide margin.

It’s clear that players are less likely to recover from a bad loss than from a more typical one, but how much of that is selection bias? After all, most of the players who lose 6-1 6-0 aren’t of the caliber of Thiem or Soderling, even if they are good enough to stick around in main draws and ultimately face the same opponent again.

To answer that question, I looked again at those 950 post-blowout matches, this time with pre-match Elo ratings. After eliminating everything before 1980 and a few other matchups with very little data, we were left with just under 600 data points. In this subset, Elo predicted that the players who lost badly had a 33.6% chance of winning the follow-up match. As we’ve seen, the actual success rate was 29%. Players who won lopsided matches outperformed their Elo forecast in the next meeting.

It’s not a huge difference, but enough to suggest that the matchup tells a little bit about how the next contest will go. One match can make a difference in the forecast–as long as it isn’t against Dominic Thiem.

Digging into the cases when a player lost badly and then recovered, I found a couple of entertaining examples:

  • Former No. 7 Harold Solomon beat Ivan Lendl in their first meeting, 6-1 6-1. Later that year, they met again at the US Open, and Lendl won, 6-1 6-0 6-0. Lendl also won their six matches after that.
  • Over the course of four years, Phil Dent and Mark Cox played three lopsided matches against each other. Cox won the first, Dent got revenge in the second, and Cox reversed things again in the third.