In my article “Betting on grand slams vs. betting on non-grand slams. Analysis of an underdogs tennis bettor”, I was able to prove that betting on the underdogs in grand slams is a not always the best decision.
If you had bet on every underdog in the last 10 seasons, you would have ended up with a yield of -13.92% over 4,885 bets.
On the other hand, if you had bet on all the favourites, your yield would have been only slightly negative at -0.05%.
This data contrasts with that of the non-grand slams events (ATP 250, ATP 500, and Masters 1000 tournaments), where the favourites produced a -2.76% yield, and the underdogs a -2.95% yield, over a total of 19,356 bets.
We can also observe that the favourite-longshot bias is much more prevalent in grand slam matches than in non-grand slam matches, probably because bettors do not fully realise the impact of the ‘best of five sets factor’.
Now, I have taken it a step further and analysed the results in each of the four grand slams. I have added 13 more years of data (from 2010 to 2022) to increase the sample size. The results from these 13 seasons can be found below.
As you can see, betting on every favourite at Pinnacle’s closing odds would have generated a positive result, with a 0.1% yield over 6,522 bets.
The most positive results for the favourites - and the worst for the underdogs - would have been obtained on the clay of Paris, with a 2.0% yield over 1,631 bets if you bet on all the frontrunners, and a -22.0% yield if you had done the same for the outsiders.
The Australian Open (+0.8%) and Wimbledon (+0.7%) would have produced a positive and nearly identical performance for the favourites.
However, there is a difference of 10 percent for the underdogs (-20.7% vs -10.7%). You might think that this is an error, but it’s not.
We need to take into account that a few longshots can make the difference, even though the yield on the favourites is the same.
I have double-checked the results, and this is indeed what happened. Sergiy Stakhovsky beat Roger Federer in Wimbledon 2013 at 46.0; Lukáš Rosol beat Rafael Nadal in 2012 at 41.0; Steve Darcis beat Nadal in 2013 at 34.0, and Sam Querrey beat Novak Djokovic in 2016 at 31.3.
In Australia, the biggest upset was Denis Istomin beating Djokovic in 2017 at 26.22.
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Regarding the US Open, it has been undoubtedly the worst tournament for the favourites, with a -2.9% yield. Underdogs have “only” lost 5.6%. This is a remarkably low number considering:
1) the favourite-longshot bias with the average price of underdogs is 6.77, and
2) how poorly underdogs typically perform in grand slams. Indeed, they usually perform much worse than what this bias would suggest.
What is the reason behind the poor performance of the frontrunners in the US Open? It is a very difficult question to answer, but I will share my view.
I think that both the heat and humidity in New York, along with the fact that some players might be exhausted after a long season, may be factors that are not fully reflected in the odds.
Of course, this is only my personal and subjective view, and I have no proof to back up my claims.
Now let’s get back to Roland-Garros. How is it that you would have won 2% of what you bet if you had backed every favourite since 2010? Additionally, isn’t it shocking that you would have lost 22.0% of what you bet on the underdogs?
This huge difference of 24 points in a sample size of 1,631 bets cannot solely be explained by the favourite-long shot bias.
If we analyse the data year by year (126 matches), the following results emerge.
In nine out of the 13 years, you would have profited by betting on the favourites. The worst year for the favourites was 2020, with a -7.4% yield. However, this was a very unusual year, where the tournament was played in October instead of June due to the pandemic.
What is the reason for the strong performance of the favourites at Roland-Garros? What else - apart from the ‘best of five sets factor’ - justifies it?
The reality is that the difference between Roland-Garros and Wimbledon or the Australian Open is not statistically significant from a numerical standpoint. A difference of 1.2-1.3 points in yield over 1,500-1,700 bets can be attributed to variance.
Therefore, we can definitively state that not only at Roland-Garros, but also in Australia and Wimbledon, the prices on the favourites are higher than they should be, and you are likely to make money if you bet on them.
The overall figure in these three tournaments is a 1.20% yield over 4,889 bets in the last 13 seasons.
In summary, if you bet on the favourites at Roland-Garros, you are much more likely to win, while the opposite holds true for the underdogs.
A -22% yield since 2010 should not be overlooked. Of course, it’s possible to bet on every favourites at this year’s Roland-Garros and still lose, but the odds seem to be in your favour.
Looking at the data from all four grand slams, we can draw similar conclusions for the Australian Open and Wimbledon. The difference between Roland-Garros and the Australian Open or Wimbledon is not statistically significant.
Therefore, we cannot strongly assert that betting on favourites in Paris produces better results than in London or Melbourne.
What we can say is that these three tournaments exhibit a strong bias in favour of the favourites compared to the underdogs, which is much larger than what the favourite-longshot bias would suggest.
The reason is likely to be the ‘best of five sets factor’.
Overall, betting on favourites in these three grand slams since 2010 would have yielded a 1.20% return over 4,889 bets, while underdogs would have resulted in an 18.1% loss.
The US Open stands out as a unique tournament in this aspect. In New York, players face difficulties, possibly due to the weather conditions and the fact that the tournament is held towards the end of the season, when players may encounter more physical issues.
These specific factors might not be fully considered by bettors, and if they were, this could diminish the disparities between the favourites and the underdogs.
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