Does the market take world ranking into account efficiently?
By Dan Weston Apr 24, 2014
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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 Sports’ closing prices.
Rank
Player
Vs. Higher Rank 12 Month W/L
Vs. Higher Rank Win %
Vs. Higher Rank P/L
Vs. 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.
Rank
Player
Vs. Lower Rank 12 Month W/L
Vs. Lower Rank Win %
Vs. Lower Rank P/L
Vs. 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.
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.
If you have feedback, comments or questions regarding this article, please email the author or send us a tweet on Twitter.
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