How to find value on the lucky loser concept in tennis

How to find value on the lucky loser concept in tennis

By Dan Weston Feb 12, 2014

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Tennis bettors looking to find value in qualifying rounds should be aware of the lucky loser concept. This article looks at whether or not betting markets consider the top ranked player in qualifying’s potential for not necessarily giving their best as they know they will get a lucky loser spot in advance of their final qualifying match, and if there is value backing against them.

What is the lucky loser in tennis?

Wikipedia’s definition of a lucky loser is ‘a sports player who loses a match in the qualifying round of a knockout tournament, but who then enters the main draw when another player withdraws after the tournament has started because of illness, injury or other reason’.  This is a very fair assessment of the situation.

The concept of lucky losers is very relevant in Tennis, with almost all events having qualifying matches to give tournament berths (usually at least four) to qualifying players, who do not have a high enough rank for direct entry, but a high enough rank to participate in qualifying.

It’s worth taking some time to note the specific rules for lucky losers in Tennis – in general ATP or WTA tournaments, the top ranked player eliminated in the final round of qualifying is the first player to enter the draw following a withdrawal, and should more than one player withdraw, the second highest ranked loser in the final round of qualifying gains entry.

This has led to some controversy, as well as speculation on Tennis forums and social media, because it is obvious that in some cases, players may well be aware that they will gain entry to the tournament as a lucky loser prior to their final qualifying match.  Clearly, these players do not have the greatest incentive to perform to the best of their abilities, and are logically far less likely to fight for a match they don’t have to win.

The top ranked player only has an equal 25% chance of a lucky loser spot in Grand Slams

Because of this, Grand Slams changed their rules in 2006.  Since then, the top four ranked players that lost in qualifying participate in a ballot for the available space following a withdrawal – so the top ranked player only has an equal 25% chance of a lucky loser spot in Grand Slams.

Considering the vast majority of these players start their final qualifying matches as favourite, this article focuses on whether the betting markets take account of the top ranked player in qualifying’s potential for not necessarily giving their best, or whether there may be some viable angles to oppose the highest ranked player (and favourite) in the final round of qualifying.

The following table illustrates the results of backing the highest ranked player in the final round of qualifying in 2013:-

Events

Wins

Win %

P/L based on 100 stake

ROI

ATP

59

39

66.1

-489

-8.29

WTA

50

26

52

-1190

-23.80

COMBINED

109

65

59.63

-1679

-15.40

We can see from the table that backing the highest ranked player in the final round of qualifying was not a lucrative proposition.  A loss of -1679 from 109 bets at level 100 stakes was incurred from the sample, generating a horrific return on investment of -15.40%.

Interestingly, seven of the 25 WTA players that lost received lucky loser spots (28.00%) whilst in the ATP, an incredible 11 of the 20 players that lost made it into the main draw (55.00%).  These included Daniel Brands, Steve Darcis and Kenny De Schepper, who all lost when priced at 1.40 or below.  In the WTA, Elina Svitolina and Svetlana Kuznetsova also lost when priced under 1.40 and gained lucky loser spots.

Ryan Harrison was the top ranked player in qualifying four times, and won three of his matches.  However, Michael Russell lost both of his matches when the highest ranked player, and he gained a lucky loser spot in Memphis last year.

The next logical step, therefore, is to assess some various starting price brackets to see whether opposing players in certain odds ranges is viable.

COMBINED

Matches

Wins

Win %

P/L based on 100 stake

ROI

<1.25

23

19

82.61

-68

-2.96

1.26-1.50

42

26

61.90

-626

-14.90

1.51-1.99

35

18

51.43

-524

-14.97

2.00+

9

2

22.22

-461

-51.22

We can see here that heavy favourites generally did win their matches, only suffering a very small loss from the sample. This is logically the case because these players are more likely to feel that they can get past their final qualifying opponent without overly exerting themselves.

It was the players that were favourites, but were available at bigger prices, that struggled badly.

These players faced opponents much closer in ability to themselves, and clearly from the above sample did not thrive. Returns of investment of -14% and below were horrific, and it is without doubt that in 2013, the prices on the top ranked players in qualifying were not justified.

With such a high proportion of players receiving lucky loser spots after losing their final qualifying matches, the above data would appear to support the theory that there are some instances where players know they will get a lucky loser spot in advance of their final qualifying match, and therefore do not put their best efforts in.

Dan Weston is a freelance tennis writer who, along with producing expert content for Pinnacle Sports, also produces his own tennis rating system, and trading analysis, which can be found at www.tennisratings.co.uk.

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