Email: Tennistrades@gmail.com Skype: @TennisRatings SUBSCRIBE TO THE TENNISRATINGS YOUTUBE CHANNEL FOR THE LATEST TENNIS TRADING & TENNIS BETTING VIDEOS! For those of you who are not totally familiar with the betting markets, the game handicap market is a very popular area for betting, with bookmakers offering a game margin difference between the two players. The player who is favourite in the betting markets will be offered '-x games', where x is the number of games that they have to win by, for them to win on the game handicap. The screenshot below, from oddsportal.com, for last weekend's Dubai final between Andy Murray and Fernando Verdasco, illustrates this:-  Here we can see that Murray -5 games is a best priced 1.96 by the market. Therefore for this bet to win, Murray must win by at least 5.5 games, with a 5 game win being known as a 'push', which is money back. If Murray won by fewer than five games, any bet on him to win -5 games would be a losing bet. Eventually, Murray won 6-3 6-2 which equates to a seven game margin, so backing Murray -5 games would be a winner, and he would be said to have covered the handicap.  This sort of market is useful to find players who over or under perform on a regular basis. For example, some players win many matches but frequently do it the hard way, failing to cover the handicap, or some players may lose a lot of matches but lose tight clashes, covering their game handicap line as an underdog. You could also look at it a bit like a golf club competition, where players of varying ability levels have various handicaps taken into account to find a winner. A player with a handicap of 36 might hit 100 (net 64) and beat a player with a handicap of 10 who scored 80 (net 70). I analysed the data from 2015 and 2016 to see which players were best and worst at covering the game handicap closest to even money on the ATP Tour (only matches without a retirement were included, as bookmakers void this market upon retirement). A minimum 20 matches were required for a player to be included:-
The ten players above were the best players on the ATP Tour for covering game handicaps in 2015 and 2016 combined - effectively these players were under-rated by the bookmakers. Looking at the list, it's probably fair to say that the majority of the time, these players would be pre-match underdogs in the betting markets for their individual matches, and therefore bookmakers made mistakes in establishing how close these players would be able to keep matches, at least.  Conversely, the players below were the worst at covering game handicaps - essentially they were over-rated by the markets in this area:-
Most of these players were obvious under performers generally - in a number of cases there is age or injury related decline apparent also - but it's also interesting to see the likes of Elias Ymer and Taro Daniel in the list. These are younger players, and in the case of Ymer, someone who my model generally considers extremely over-rated in the last six months or so. I also obtained data on how a player performed against the game handicap line when they were favourite or underdog, so the next table shows the best performing players as favourite, with again a minimum 20 matches being required for a player to be included:-
Andrey Kuznetsov's data as a favourite was truly outstanding - he looks incredible at being able to easily beat those players considered worse than him, although as we will see later, he had less success when he faced a better quality of opponent. This was also the case for Philipp Kohlschreiber, whose ability to cover handicap lines as a heavy favourite is something I've been aware of for a while.  It certainly would be reasonable to make a case for many of the players on the above list - with the exceptions of Marcos Baghdatis and possibly Dusan Lajovic, who recorded underdog handicap win percentages of 50% or above - being a flat-track bully. Below is a list of those who performed worst at covering the game handicap line as a favourite, with a number of players being saved from this ignominy by the minimum 20 completed match sample size rule...
Probably to the surprise of very few readers, Benoit Paire was atrocious at winning easily while the likes of Ernests Gulbis, and the current flavour of the month, Grigor Dimitrov, were little better. Again, a number of declining veterans made it onto the list, and keeping an eye on age-related decline in the future is likely to yield rewards in this particular area. 
The table above illustrates those who performed best at keeping matches closer than bookmakers and the market anticipated when they were the pre-match betting underdog. There's a strange mix of return and serve orientated players on the list and it is difficult to judge whether there were any trends that could be taken from this particular group of players, or simply whether these players were under-rated by the market and/or tanked less than their peers. However, there were many players who performed very poorly as an underdog, with the likes of Roger Federer, Gael Monfils David Ferrer and Rafa Nadal saved from this next list due to the fact they hadn't played 20 matches as a pre-match underdog in this two-year period:-
Leonardo Mayer (remember him from the list of players who performed well as a favourite against the game handicap?) performed the worst here, and winning just over 20% in a market which is priced as a coin flip really is horrific. It would be fair to say these players above tend to under-perform on expectations when facing a 'better' opponent. Finally, I wanted to compare favourite to underdog records for each player, in an attempt to identify the ultimate in flat-track bullies (high game handicap covering percentage as favourite, low as underdog) and also those who perform best when the pressure of expectation is off them (higher game handicap covering percentage as underdog than favourite). The players below fitted into the flat-track bully dynamic, where they easily beat those players worse than them, but have huge issues being competitive against better opponents. A minimum of 15 matches as both favourite and underdog were required for a player to qualify for this filter:-
Certainly, based on this data, treating these players very differently when favourite or underdog is recommended. This would be particularly the case for Leonardo Mayer and Andrey Kuznetsov in particular, with extreme differences between their performance on the game handicap as favourite and underdog. Finally, the players below performed much better against the game handicap when underdog, compared to when they were favourites:-
Ricardas Berankis, who just missed out on the worst performing players list as favourite due to having smaller than 20 matches sample size is now included in this list where 15 matches for both favourite and underdog were required. Anyone familiar with tennis betting or trading is likely to be unsurprised that Dominic Thiem is also in this list - he frequently plays much longer matches than average when a heavy favourite - and as mentioned before, the inconsistent Paire and over-rated Dimitrov are also in this list. If you are interested in obtaining the full data for every player, you can do so via the PayPal link below:- | A Selection of TennisRatings Products Please visit the TennisRatings Products links for a full overview of our fantastic Tennis Trading tools, and the TennisRatings Subscription Packages link to see our great value range of discounted subscription packages! Please check out our testimonials page! The TennisRatings Daily Trading Spreadsheets have never been more popular! To find out more on how these can dramatically improve your Tennis Trading, check out the YouTube Video we made. The Challenger Daily Spreadsheets cover all ATP Challenger Events and include projected hold percentages (for traders) and model prices (for bettors and traders). Subscriptions are available for 3 months:- The Lead Loss/Recovery Data Spreadsheets have taken the Tennis Trading World by storm - discussed in detail in October 2015 at the Matchbook Traders Conference these incredible spreadsheets highlight lead loss & deficit recovery in individual sets, as well as how often a player loses/gains the first break of the second set based on whether they won or lost the first set! INCLUDES FREE REGULAR UPDATES - THIS IS A ONE-TIME PURCHASE! |