World ranking of players is something that many bettors take into account, without necessarily understanding whether it is relevant or not to their betting. This article assesses whether there is an edge to be gained betting on Tennis favourites against higher ranked players.
Understanding tennis players ranking
A tennis player’s world ranking is a controversial subject. Calculated on a 52-week rolling basis, ranks tend to fluctuate significantly during the Tennis season.
A long-term injury - think Juan Martin Del Potro, Nicolas Almagro and Tommy Haas recently - will affect a player’s rank severely and may leave them unable to enter directly into tournaments without qualifying or receiving wild cards. Due to this, some observers feel that a 2-year (or 104 week) period would be fairer, and more representative of a player's actual ability.
Furthermore, world rankings tend to reflect the current predominant surface being played in the majority of tournaments, at that time of the season. For example, clay court experts are likely to be ranked higher, after the main clay season finishes, than they would prior to it. This means that rankings are often skewed and are not a true reflection of the all-surface abilities of players.
On this basis, the market may interpret player rankings incorrectly, with a player who has risen up the rankings recently due to several strong tournaments likely to be over-rated. So what does this mean for tennis bettors?
Are lower ranked favourites undervalued in the ATP?
An interesting angle would be to look at players who are favourites in the market, but are the lower ranked player. These players are perceived by the market to be the better player, but considered worse by the rankings by the ATP/WTA Tours. Logically, these players are likely to be under-rated despite being favourite, due to being the lower ranked player.
The following table assesses a sample of players on the ATP Tour throughout their career (main draw and qualifying matches) when they started the match as favourite, but as the lower ranked player.
A cross-section of players ranked from 1 to 100 were sampled, with two players around the midpoint of each ten ranking places included.
All prices used are Pinnacle Sports’ closing prices, and only matches where at least one set was completed were included:
Player
Rank
Matches
Wins
Win %
P/L
ROI %
Nishikori
5
23
12
52.17
-476
-20.70
Murray
6
13
8
61.54
-28
-2.15
Anderson
15
27
18
66.67
354
13.11
Bautista-Agut
16
30
19
63.33
252
8.40
Benneteau
25
32
21
65.63
109
3.41
Mayer L
26
45
33
73.33
945
21.00
Querrey
35
52
30
57.69
-181
-3.48
Mannarino
36
22
13
59.09
-70
-3.18
Sock
45
33
17
51.52
-333
-10.09
Seppi
46
12
9
75.00
326
27.17
Sousa
55
11
7
63.64
149
13.55
Young
56
39
27
69.23
757
19.41
Bellucci
65
41
27
65.85
83
2.02
Tomic
66
44
29
65.91
110
2.50
Jaziri
75
12
8
66.67
190
15.83
Haas
76
35
25
71.43
676
19.31
Berankis
85
46
30
65.22
277
6.02
Dodig
86
21
14
66.67
246
11.71
Kamke
95
23
14
60.87
-197
-8.57
Gojowcyzk
96
26
12
46.15
-504
-19.38
Overall
587
373
63.54
2685
4.57
As can be seen from the table, a significant sample of data was generated with 587 matches sampled. 373 wins came from this sample (a win percentage of 63.54%) and when a £100 hypothetical stake was applied to all matches sampled, a profit of £2,685 was generated (return on investment of 4.57%).
This ROI is very strong for a blind backed sample of a significant size, and can be treated as a huge edge in the market.
Andreas Seppi, Leonardo Mayer and Tommy Haas all recorded win percentages over 70% from this scenario, with Haas particularly interesting, as he recovered his ranking following a long-term injury in 2012. The same issue will affect Haas in the future, as he has been absent from Tour through injury since May 2014. Donald Young, with a win percentage of 69.23% and ROI of 19.41%, was also historically very strong.
Just seven players of the 20 sampled recorded negative ROI figures, with Kei Nishikori, Peter Gojowczyk and Jack Sock recording the worst figures of over -10% ROI. Interestingly both top ten ATP players sampled (Andy Murray was the other player) had negative figures, illustrating that both currently have poor records against elite level opponents.
Are lower ranked favourites undervalued in the WTA?
Player
Rank
Matches
Wins
Win %
P/L
ROI %
Ivanovic
5
29
20
68.97
346
11.93
Radwanska A
6
8
6
75.00
229
28.63
Jankovic
15
12
7
58.33
18
1.50
Safarova
16
26
18
69.23
403
15.50
Pavlyuchenkova
25
16
10
62.50
118
7.38
Svitolina
26
12
8
66.67
122
10.17
Keys
35
29
22
75.86
637
21.97
Garcia
36
13
8
61.54
10
0.77
Vinci
45
15
10
66.67
297
19.80
Koukalova
46
10
7
70.00
169
16.90
Beck
55
21
11
52.38
-337
-16.05
Jovanovski
56
11
6
54.55
-152
-13.82
Vesnina
65
24
18
75.00
766
31.92
Shvedova
66
41
26
63.41
234
5.71
Erakovic
75
30
18
60.00
-77
-2.57
Rogers
76
14
6
42.86
-381
-27.21
Vekic
85
12
9
75.00
308
25.67
Parmentier
86
22
11
50.00
-275
-12.50
Konjuh
95
30
23
76.67
545
18.17
Gibbs
96
20
14
70.00
385
19.25
Overall
395
258
65.32
3365
8.52
Interestingly, the WTA figures were even stronger, with a return on investment of 8.52% from 395 matches, as well as a slightly higher 65.32% win rate. These statistics are truly stellar numbers for a blind-backed scenario.
Of the players with a large sample, Madison Keys, Elena Vesnina and Ana Konjuh had win percentages of 75% or over, and these look like players whose rank is likely to be, or has been below their level of ability.
Quite incredibly, only four WTA players of the 20 sampled recorded negative figures - Annika Beck, Bojana Jovanovski, Shelby Rogers and Pauline Parmentier.
Overall, combining the ATP and WTA figures, profits of £6050 were generated from a stake of £98,200, giving a return of investment of 6.16%. From such a huge sample, this profit level is likely to be statistically significant, and it would appear that the market has underestimated this scenario in the extreme.
Bettors would be very strongly advised to consider this in their future tennis analysis.
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