Following on from our analysis of the regular ATP tour events, we look towards the second Grand Slam of the year, which gets underway next week. Novak Djokovic and Naomi Osaka will be hoping to continue their strong start to the tennis season after winning the Australian Open, but who will come away with the 2019 French Open title and prize remains unknown. What we do know, however, is that the data can help us understand and perhaps even predict the performances on court this year.
How do court conditions affect play?
When looking at a tournament in advance, the first thing worthy of examination is always the anticipated conditions. To the untrained eye, when someone looks at a live score website, the surface is merely described as ‘clay’, but there are numerous nuances which determine the court speed of a particular venue.
This could be anything from the manufacturer/supplier of a particular surface (for example, there are several different suppliers of hard courts), the various types of balls used, and also climatic conditions, including altitude. Madrid, which is played at a high level, is typically the quickest clay court year on year, due to this reason, and therefore it is difficult to equate performances in the Spanish capital to most other clay venues, which are typically slower.
Across the last three years, data comparing Madrid and the French Open - both played on clay - are markedly different. In Paris, 76.6% of service games in the men’s singles have been held across the last three years, a figure which rises to 81.2% in Madrid. Given that the ATP clay mean over the time period is 77.1%, we can see that conditions at the French Open are likely to be medium-slow for clay, while in Madrid, they are traditionally quick, and more akin to hard court pace.
In fact, this percentage ranks the French Open as one of the 12 slowest venues on the ATP Tour, and we can look at how players of varying dynamics have performed at the French Open, and indeed, at the slower venues combined.
Interestingly, return-oriented players in Paris have been fairly well-handicapped by the market. From 2016 onwards, the most return-oriented notable players on tour - those with 23% difference or fewer between their service and return points won percentages (19 players in total) have played 118 matches at Roland Garros and generated profits of €431 if hypothetically blind-backing them for €114 in each match (ROI of 3.20%).
However, it’s worth pointing out that more players had negative market results than positive, and the sample was influenced by several heavy underdog victories. Across the 12 slow venues, these players performed worse, too, playing 541 matches and generating a loss of €3309 via the same staking method (-5.36% ROI). Given the bigger sample, there could be a reasonable argument made that the market over-rates these return-oriented players (usually clay-court specialists) and there frequently isn’t value on them in their preferred conditions.
On the flip side, I wanted to look at the French Open performances of players with a 30% or greater difference between their service and return points won percentages - the serve-orientated players on tour.
These players have performed atrociously compared to market expectations at the French Open, playing 157 matches from 2016 onwards, and yielding a loss of €2260 from the same staking strategy (ROI of -12.61%). In a bigger sample of slow tournaments in general, they produced an ROI of -6.26% (although largely derived from the French Open results), so with the standard bookmaker margin factored in as well, it looks they are also being overrated by the markets - and arguably even more so (even with lower expectations) than the return-oriented players.
This is likely to be based on reputation - there’s the likes of John Isner, Milos Raonic, Nick Kyrgios, Kevin Anderson, Jo-Wilfried Tsonga, Marin Cilic and Roger Federer among the serve-oriented players on the list - so it is vital that bettors are not influenced by a player’s ‘name’.
Where is the best betting value?
So with both serve and return players, as brackets, being a little over-rated by the markets, which type of players should we look at in these slower conditions as potential value? More balanced players performed better across this sample, and a number of higher profile players without clear serve or return oriented tendencies have yielded strong profits in slower condition tournaments, such as Karen Khachanov and Dominic Thiem. Some smaller names who have also done well include Marco Cecchinato, Guido Pella and Laslo Djere, and I think that the most important consideration is actually pretty simple - just judge a player on their actual merits on the surface.
Most of the time, this would just mean looking at either their service/return points won or hold/break percentages on the surface (I find 12 months data a useful guide with more reliable sample than shorter time-spans) and ignoring any considerations on a player’s reputation.
Other factors to consider when betting
The other consideration regarding the French Open that arguably applies more than other Grand Slams is accumulated fatigue for men’s players. The best of five set format is arduous enough for players, but at Roland Garros the effects of this are exacerbated further given the average number of shots required to win points (on hard courts, and particularly grass, points tend to be shorter with more aces served in the quicker conditions).
This is demonstrated by the performances of favourites in the tournament during the latter stages. From 2015 onwards (four tournaments) market favourites have won 50 of 60 matches (83.33%) and returned profits of almost 13% ROI based on best market closing price. In addition, 41 of 58 completed matches (matches which didn’t end in retirement) featured favourites who covered the -1.5 set handicap (70.69%) while 22/58 (37.93%) ended up in a 3-0 victory for the pre-match favourite.
In short, men’s favourites usually perform extremely well in the second week, and given the physical demands of players in this particular event, it’s not particularly a surprise, with fitness being one major driver towards a player’s ranking.
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