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Apr 24, 2014
Apr 24, 2014

Does the tennis market take world ranking into account efficiently?

Does the tennis market take world ranking into account efficiently?

Some bettors place faith in world rankings when assessing a pre-match betting position, whilst others consider them absolutely irrelevant, with some players having the ability to play well above or below their world ranking on a given surface. This tennis betting article examines whether the market takes account of world ranking information correctly, in the ATP.

The theory behind tennis world rankings

As was discussed in the article which assessed players defending ranking points, a Tennis player’s ranking is assessed on a 52-week rolling year basis with points being removed and added each week, depending on results.

Some tournaments offer vastly more ranking points than others.  For example, winning a Grand Slam awards 2000 points, whilst the winner of a Masters event will receive 1000 points.  Naturally, the winners of a 500 or 250 event will receive 500, or 250 points, respectively.  Interestingly, reaching the quarter finals of a Grand Slam will award 360 points, which is more than the tournament winner of a 250 event earns.

Therefore, it is reasonable to suggest that world rankings can be somewhat skewed based on a player’s success or failure in several big tournaments.  Just a couple of good runs into the latter stages of Grand Slams or Masters events will dwarf the ranking points received by regular participants of lower level tournaments.

This logical conclusion would support those bettors that disregard world rankings as a serious metric to consider when making a pre-match betting assessment of a forthcoming match.  However, those who believe that the world rankings are a fair illustration of a player’s ability will argue that to get to the latter stages of a high calibre tournament, a player must have a high level of ability, and therefore deserves those ranking points mainly derived from several events.

Performance against higher ranked players

The following table shows how selected ATP players performed against higher ranked opponents in the last 12 months (15th April 2013 until 15th April 2014).  A sample was used whereby two players at the midpoint of each ten place ranking bracket from 1 to 100 were assessed, which gives a solid sample size, and also a mix of ranking levels.  A hypothetical bet of £100 level stake was applied to each player’s match, to derive the profit and loss figure.  All prices used were Pinnacle’ closing prices.

RankPlayerVs. Higher Rank 12 Month W/LVs. Higher Rank Win %Vs. Higher Rank P/LVs. Higher Rank Best Win
5 Berdych 5-8 38.46 355 Novak Djokovic, 1
6 Ferrer 2-4 33.33 461 Rafael Nadal, 1
15 Youzhny 10-10 50.00 1060 David Ferrer, 3
16 Haas 0-7 0.00 -700 N/A
25 Kohlschreiber 5-14 26.32 -385 Richard Gasquet, 9
26 Verdasco 13-12 52.00 936 Richard Gasquet, 9
35 Seppi 3-16 15.79 -1090 Kei Nishikori, 11
36 Andujar 10-17 37.04 380 Marin Cilic, 11
45 Bautista-Agut 12-19 38.71 849 Berdych/Del Potro, 5
46 Nieminen 4-13 23.53 -1116 Juan Martin Del Potro, 7
55 Sijsling 10-17 37.04 -47 Raonic/Youzhny, 15
56 Kukushkin 19-18 51.35 -19 Andreas Seppi, 22
65 Klahn 6-12 33.33 -525 Daniel Brands, 57
66 Matosevic 14-19 42.42 -396 Milos Raonic, 13
75 Nedovyesov 6-13 31.58 -79 Robin Haase, 47
76 Hanescu 8-16 33.33 -178 Kevin Anderson, 19
85 Volandri 5-13 27.78 -664 Daniel Gimeno-Traver, 59
86 Mayer L 11-16 40.74 -294 Tommy Robredo, 16
95 Robert 10-12 45.45 75 Michal Przysiezny, 64
96 Struff 9-21 30.00 -1183 Mikhail Kukushkin, 64
Overall 162-277 36.90 -2540

As can be seen from the above table, ATP players did not fare well against higher ranked players, with a -£2540 loss being generated from 439 hypothetical bets (-5.79% ROI).

Quite interestingly, we can see that current top 50 players achieved much better results against higher ranked players than those ranked between 50 and 100.  64 matches were won by current top 50 players against higher ranked players with 120 matches being lost (34.78%) and although the win percentage was lower, the higher average back price ensured that a profit of £750 was generated from these players (ROI of 4.08%).

Therefore a loss of £3290 ensued from backing players currently ranked between 50 and 100 from 255 matches (-12.90% ROI), and this figure shows that there are effectively two levels of the ATP, with the lower ranked players finding it much harder to get wins over their more illustrious opponents.  This is also illustrated by the fact that only 4 out of 8 players sampled ranked outside the top 60 had wins over top 50 players, and just three had wins over top 40 players.

Performance against lower ranked players

The following table shows how selected ATP players performed against lower ranked opponents in the last 12 months (15th April 2013 until 15th April 2014, with the same rules as the previous sample applied.

RankPlayerVs. Lower Rank 12 Month W/LVs. Lower Rank Win %Vs. Lower Rank P/LVs. Lower Rank Worst Defeat
5 Berdych 51-16 76.12 -471 Thiemo De Bakker, 104
6 Ferrer 57-22 72.15 -741 Alex Bogomolov Jr, 83
15 Youzhny 26-12 68.42 241 Bjorn Phau, 358
16 Haas 42-15 73.68 866 Steve Johnson, 142
25 Kohlschreiber 31-14 68.89 34 Ruben Bemelmans, 176
26 Verdasco 23-11 67.65 -213 Thiemo De Bakker, 162
35 Seppi 26-16 61.90 225 Grzegorz Panfil, 288
36 Andujar 16-12 57.14 263 Miroslav Mecir, 240
45 Bautista-Agut 23-6 79.31 466 Alexandre Kudryavtsev, 270
46 Nieminen 27-16 62.79 -428 Felip Peliwo, 355
55 Sijsling 23-16 58.97 -615 Thanasi Kokkinakis, 570
56 Kukushkin 30-8 78.95 151 Andreas Beck, 557
65 Klahn 47-12 79.66 741 Felip Peliwo, 554
66 Matosevic 9-8 52.94 -234 Ryan Harrison, 132
75 Nedovyesov 49-29 62.82 1017 Maximo Gonzalez, 370
76 Hanescu 14-11 56.00 34 Thiemo De Bakker, 162
85 Volandri 39-15 72.22 135 Pavol Cervenak, 322
86 Mayer L 16-9 64.00 -119 Somdev Devvarman, 188
95 Robert 29-12 70.73 170 Farrukh Dustov, 263
96 Struff 37-11 77.08 994 Simone Bole, 321
Overall 615-271 69.41 2516

Interestingly, this table shows the polar opposite of the sample on players facing opponents ranked higher than them.  Naturally the win percentage for players facing lower-ranked opponents will be much higher than when they face higher-ranked opponents, and the 69.41% win percentage is almost double that of the first sample.

More relevant is the profit and loss figure from the sample.  A £2516 profit was generated from 886 bets (2.84% ROI) and this is a pretty solid return on investment for a blindly-backed scenario.

Quite conversely, those ranked outside the top 50 enjoyed much more success against lower-ranked players than they did against higher-ranked players.  The vast majority of the sample’s profit, £2274, was earned from these players.  This was from 424 bets and generated an ROI of 5.36%.  These figures would go towards indicating that there are almost three ‘divisions’ in Tennis, with the top 50, 50-100 rank and the 100+ rank needing to be treated as different entities.

Finally, it is also worth noting some stats on individual players.  Mikhail Youzhny, Pablo Andujar, Roberto Bautista-Agut and Stephane Robert enjoyed profits over both higher and lower ranked players, indicating that they are generally under-rated by the market.  However, the opposite can be argued against Jarkko Nieminen, Igor Sijsling, Marinko Matosevic and Leonardo Mayer.  These players are generally over-rated by the market, as they have negative returns against both ranking brackets.

Overall, the stats in the article would indicate that the world ranking of a player is something that should be taken into account in select circumstances, as part of a balanced betting strategy.

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