вторник, 24 февраля 2015 г.

Assessing the follow-up results of tennis players after a big Grand Slam win

Upsets in tennis Grand Slams occur in most tournaments. As a tennis bettor it would be advantageous to know how the market reacts to these results. We assess how players who cause a big upset perform in their subsequent match. Are they over or undervalued by the market?

Grand Slam upsets

If tennis bettors were asked to name the most notorious Grand Slam upsets in recent years, one victim would probably be at the forefront of their opinions - Rafael Nadal. 

The Spanish legend has been on the receiving end of several gigantic shocks in the last three years, mostly at Wimbledon. Lukas Rosol stunned the tennis world by beating Nadal in five sets in the second round at SW19, in 2012, whilst Steve Darcis emulated the Czech, getting past Nadal in straight sets in the first round in 2013. 

These victories for Rosol and Darcis were the biggest priced wins in recent Grand Slam history, with Rosol’s coming at a price of 41.60, and Darcis was priced slightly shorter, at 35.52.  Both players’ progress in the tournament was swiftly curtailed following their wins.

Darcis incredibly awarded a walkover to Lukasz Kubot in round two, while Rosol, after being immediately backed into fifth favourite for the tournament, was easily ousted by Philipp Kohlschreiber in straight sets in the third round.

Shock wins like these frequently cause split opinions in the tennis markets.  Some bettors think that a big win heralds a player as a big contender and adept in the current conditions, while others chalk it down to variance, and look at a more long-term position with regards to their next match.

Generally speaking, in tennis betting, knee-jerk reactions should be avoided.

What the data suggests?

The following table illustrates the records of both the ATP and WTA players, ranked outside the top 50, following a win against a top 20 player in a Grand Slam, between 2012 and 2014. 

Only completed matches were used in the sample, as a win cannot be considered a shock if the opponent retired injured.  All prices used were Pinnacle Sports’ closing prices, and a hypothetical £100 bet was applied to each player’s subsequent match.

ATP:

Starting Price

Matches

Wins

Win %

Profit/Loss

ROI

<1.50

5

4

80

49

9.8

1.50-1.99

8

2

25

-290

-36.3

2.00-2.99

5

2

40

-87

-17.4

3.00+

18

3

16.7

-817

-45.4

Overall

36

11

30.6

-1145

-31.8

WTA:

Starting Price

Matches

Wins

Win %

Profit/Loss

ROI

<1.50

4

2

50

30

7.5

1.50-1.99

13

4

30.8

-629

-48.4

2.00-2.99

16

4

25

-718

-44.9

3.00+

28

3

10.7

-1113

-39.8

Overall

61

13

21.3

-2430

-39.8

While sample sizes were not huge, the results show clear issues for players in their next match after a big win, with only the heavy favourites, priced less than 1.50, having a positive profit and loss position.

This was the case for both the ATP and WTA, indicating that both tours have similarities in this respect. Win percentages of 30.6% and 21.3% respectively were very poor indeed.

As the starting price for a player grew bigger, the results generally got worse. A loss of -£1930 from 46 matches for ATP and WTA players priced over 3.00 is horrific, and generated a return on investment of -41.9%. 

These figures would have been even worse had Ekaterina Makarova - ranked 56 at the time - not defeated Serena Williams, when priced at 10.08, after she had defeated 7th ranked Vera Zvonareva in the previous round, at the 2012 Australian Open.

Dan Evans (ranked 179) provided the best result for ATP players priced over 3.00, backing up his defeat of Kei Nishikori at the 2013 US Open with a further success against Bernard Tomic in the next round.

CiCi Bellis provided the biggest shock, by ranking position, defeating Dominika Cibulkova (ranked 12 at the time). She was just over 15 years of age, and ranked 1,208 in the world at the time. 

Odds movement

Price movement was quite mixed following these big wins. While Rosol was backed significantly in the outright markets following his victory over Nadal, smart bettors backed opponent Kohlschreiber for the next match, pushing Rosol’s price from 2.43 (opening) to 3.18 (closing). 

Further drifts ensued in the following cases:

Valeria Savinykh drifted from 2.93 to 5.67 for her match with Kirsten Flipkens at the Australian Open in 2013, following her win over Dominika Cibulkova.

Jie Zheng drifted from 2.89 to 3.57 for her match with Madison Keys at the Australian Open in 2013, following her win over Roberta Vinci.

Jamie Hampton drifted from 2.90 to 3.47 for her match with Jelena Jankovic at the French Open in 2013, following her win over Petra Kvitova.

Kristina Mladenovic drifted from 1.64 to 1.81 for her match with Alison Riske at the French Open in 2014, following her win over Li Na.

Yanina Wickmayer drifted from 2.20 to 3.11 for her match with Silvia Soler-Espinosa at the French Open in 2014, following her win over Caroline Wozniacki.

Nick Kyrgios drifted from 2.89 to 3.51 for his match with Richard Gasquet at Wimbledon 2014, following his win over Rafael Nadal.

Ernests Gulbis drifted from 1.35 to 1.75 for his match with Jerzy Janowicz at Wimbledon 2012, following his win over Tomas Berdych.

However, many players’ prices also contracted following a big win, making it very difficult for bettors to find the best value when deciding whether to use early or late prices in these markets.

With that said because the data is so damning for follow-up matches, bettors can start to make an assessment that players priced over 1.50 in their subsequent match are over-valued by the tennis betting market, and should look to oppose them if their further research also backs that assertion up.

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