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What Are Blackjack Side Bets?Side bets are bonus bets placed on a round of Blackjack on outcomes beyond whether the player or dealer will win. The majority are staked at the start of the round before the cards have been dealt alongside regular bets and many have fixed odds that usually offer greater payouts than the simple 2:1 rewarded for beating the dealer.Play Blackjack at Pinnacle Casino

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Finding a niche market in betting can often lead to value. This can be anything from specialist knowledge of handball betting to extensive experience in betting on Japanese baseball. Providing you know more than the bookmaker, there is money to be made.  &lt;Bet on soccer at Pinnacle&gt; They also make for interesting and potentially profitable bets, as they can be a little more reliable

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Poisson Distribution is a mathematical concept for translating mean averages into a probability for variable outcomes across a distribution. For example, if we know Manchester City average 1.7 goals per game, so by putting the Poisson Distribution formula tells us that this average equates to Manchester City&nbsp;scoring 0 goals 18.3% of the time, 1 goal 31% of the time, 2 goals 26.4% of the time and 3 goals 15% of the time.

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What is Expected Value?The amount a player can expect to win or lose if they were to place a bet on the same odds many times over, calculated through a simple equation multiplying your probability of winning with the amount you could win per bet, and subtracting the probability of losing multiplied by the amount lost per bet.A simple example of Expected Value (EV) put into practice -&nbsp;if you were

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The Expected Value of a bet shows us how much we can expect to win (on average) per bet, and as such is the most valuable calculation a bettor can make when comparing bookmakers' odds. How can you calculate Expected Value in sports betting in order to predict your winnings? Read on to find out.

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As an analyst and trader specialising in tennis, Dan uses statistical analysis to research and write about tennis pre-match and in-play betting markets. With a degree in Accounting &amp; Finance (BA), Dan devised his own pre-match pricing model and writes daily match previews and betting articles for his website, <a class="invisible-for-meet-authors" href="http://www.tennisratings.co.uk">www.tennisratings.co.uk</a>.

Dan Weston

The previous articles in this series looked at how to highlight players whose results were over or underperforming in comparison to their expected win-loss record. To conclude, this ﬁnal piece will proﬁle which players ﬁt this bracket, with a view to demonstrating potential proﬁtability from such an approach.
<h3>Ascertaining players undervalued by the market</h3>
As previously established, there is a noticeable relationship between a tennis player’s win percentage and combined service and return points won percentage, and a slightly weaker one between the latter and tiebreak success rate. These findings can be utilised to proﬁle players who performed better than their actual results indicated across the 2019 season.
The players listed below suffered an inferior win percentage in 2019 than many players with poorer combined service and return points won percentages. They also had poorer tiebreak records than expected, based on their ability level implied from their service and return points won percentage:
<div class="table-holder-article-content">
<div class="table-modal">
<div class="table-modal-head">
<div class="table-modal-head-inner"></div>
</div>
<div class="table-modal-content">
<div class="article-table-content">
<table class=" article-table">
<tbody>
<tr>
<td>
Player
</td>
<td>
Win rate (%)
</td>
<td>
Service points won (%)
</td>
<td>
Return points won (%)
</td>
<td>
Combined serve and return points won (%)
</td>
<td>
2019 tiebreaks contested
</td>
<td>
2019 tiebreaks won
</td>
<td>
Tiebreaks won (%)
</td>
</tr>
<tr>
<td>
Roberto Bautista-Agut
</td>
<td>
65%
</td>
<td>
66.7%
</td>
<td>
38.7%
</td>
<td>
105.4%
</td>
<td>
23
</td>
<td>
8
</td>
<td>
34.8%
</td>
</tr>
<tr>
<td>
David Goffin
</td>
<td>
57%
</td>
<td>
63.4%
</td>
<td>
39.8%
</td>
<td>
103.2%
</td>
<td>
24
</td>
<td>
12
</td>
<td>
50.0%
</td>
</tr>
<tr>
<td>
Grigor Dimitrov
</td>
<td>
50%
</td>
<td>
65.2%
</td>
<td>
37.4%
</td>
<td>
102.6%
</td>
<td>
30
</td>
<td>
9
</td>
<td>
30.0%
</td>
</tr>
<tr>
<td>
Hubert Hurkacz
</td>
<td>
51%
</td>
<td>
66.3%
</td>
<td>
34.9%
</td>
<td>
101.2%
</td>
<td>
24
</td>
<td>
11
</td>
<td>
45.8%
</td>
</tr>
<tr>
<td>
Ugo Humbert
</td>
<td>
43%
</td>
<td>
65.2%
</td>
<td>
35.1%
</td>
<td>
100.3%
</td>
<td>
21
</td>
<td>
8
</td>
<td>
38.1%
</td>
</tr>
<tr>
<td>
Fernando Verdasco
</td>
<td>
48%
</td>
<td>
63.8%
</td>
<td>
36.5%
</td>
<td>
100.3%
</td>
<td>
19
</td>
<td>
8
</td>
<td>
42.1%
</td>
</tr>
<tr>
<td>
John Millman
</td>
<td>
41%
</td>
<td>
63.6%
</td>
<td>
36.3%
</td>
<td>
99.9%
</td>
<td>
26
</td>
<td>
11
</td>
<td>
42.3%
</td>
</tr>
<tr>
<td>
Dusan Lajovic
</td>
<td>
43%
</td>
<td>
61.6%
</td>
<td>
36.9%
</td>
<td>
98.5%
</td>
<td>
15
</td>
<td>
5
</td>
<td>
33.3%
</td>
</tr>
<tr>
<td>
Federico Delbonis
</td>
<td>
41%
</td>
<td>
60.7%
</td>
<td>
37.6%
</td>
<td>
98.3%
</td>
<td>
21
</td>
<td>
6
</td>
<td>
28.6%
</td>
</tr>
<tr>
<td>
Steve Johnson
</td>
<td>
40%
</td>
<td>
64.7%
</td>
<td>
33.6%
</td>
<td>
98.3%
</td>
<td>
20
</td>
<td>
7
</td>
<td>
35.0%
</td>
</tr>
<tr>
<td>
Kyle Edmund
</td>
<td>
39%
</td>
<td>
63.8%
</td>
<td>
34.2%
</td>
<td>
98.0%
</td>
<td>
12
</td>
<td>
1
</td>
<td>
8.3%
</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
Many of these players had around a 50% win rate last season despite recording a service and return points won percentage of above 100%, or a win rate of approximately 40% despite performing only marginally beneath the 100% benchmark.
In addition, not a single one of these players won greater than 50% of the tiebreaks they contested, despite recording stats in line or above those expected of an average professional.
Essentially, this group of players incurred poor results despite achieving at least decent stats. Notably, already in the 2020 season their results thus far have shown that the group have positively mean-reverted, prompting the market to undervalue them based on their 2019 results as opposed to underlying performance levels:
<table class=" article-table">
<tbody>
<tr>
<td>
Player
</td>
<td>
Matches
</td>
<td>
Profit/Loss
</td>
<td>
ROI
</td>
</tr>
<tr>
<td>
Roberto Bautista-Agut
</td>
<td>
12
</td>
<td>
4
</td>
<td>
0.33
</td>
</tr>
<tr>
<td>
David Goffin
</td>
<td>
13
</td>
<td>
583
</td>
<td>
44.85
</td>
</tr>
<tr>
<td>
Grigor Dimitrov
</td>
<td>
14
</td>
<td>
-79
</td>
<td>
-5.64
</td>
</tr>
<tr>
<td>
Hubert Hurkacz
</td>
<td>
13
</td>
<td>
37
</td>
<td>
2.85
</td>
</tr>
<tr>
<td>
Ugo Humbert
</td>
<td>
17
</td>
<td>
428
</td>
<td>
25.18
</td>
</tr>
<tr>
<td>
Fernando Verdasco
</td>
<td>
8
</td>
<td>
-131
</td>
<td>
-16.38
</td>
</tr>
<tr>
<td>
John Millman
</td>
<td>
10
</td>
<td>
236
</td>
<td>
23.60
</td>
</tr>
<tr>
<td>
Dusan Lajovic
</td>
<td>
15
</td>
<td>
442
</td>
<td>
29.47
</td>
</tr>
<tr>
<td>
Federico Delbonis
</td>
<td>
14
</td>
<td>
-284
</td>
<td>
-20.29
</td>
</tr>
<tr>
<td>
Steve Johnson
</td>
<td>
19
</td>
<td>
-16
</td>
<td>
-0.84
</td>
</tr>
<tr>
<td>
Kyle Edmund
</td>
<td>
13
</td>
<td>
61
</td>
<td>
4.69
</td>
</tr>
<tr>
<td>
Overall
</td>
<td>
148
</td>
<td>
1281
</td>
<td>
8.66
</td>
</tr>
</tbody>
</table>
Blind-backing this group in their matches this season would have returned 8.66% ROI to a level £100 stake based on Pinnacle’s closing prices – a considerable proﬁt margin from the 148 matches in which they competed during the ﬁrst two months of the year.
<h3>Who is overvalued by the market?</h3>
We can also look at the inverse indicators, to try and establish those which the market could be over-valuing and should (in theory) mean-revert downwards having obtained better results last year than their underlying performance levels would suggest:
<div class="table-holder-article-content">
<div class="table-modal">
<div class="table-modal-head">
<div class="table-modal-head-inner"></div>
</div>
<div class="table-modal-content">
<div class="article-table-content">
<table class=" article-table">
<tbody>
<tr>
<td>
Player
</td>
<td>
Win rate (%)
</td>
<td>
Service points won (%)
</td>
<td>
Return points won (%)
</td>
<td>
Combined serve and return points won (%)
</td>
<td>
2019 tiebreaks contested
</td>
<td>
2019 tiebreaks won
</td>
<td>
Tiebreaks won (%)
</td>
</tr>
<tr>
<td>
Stan Wawrinka
</td>
<td>
63%
</td>
<td>
67.8%
</td>
<td>
35.3%
</td>
<td>
103.1%
</td>
<td>
37
</td>
<td>
22
</td>
<td>
59.5%
</td>
</tr>
<tr>
<td>
Guidi Pelia
</td>
<td>
58%
</td>
<td>
63.3%
</td>
<td>
37.9%
</td>
<td>
101.2%
</td>
<td>
25
</td>
<td>
17
</td>
<td>
68.0%
</td>
</tr>
<tr>
<td>
Felix Auger-Aliassime
</td>
<td>
60%
</td>
<td>
65.6%
</td>
<td>
35.5%
</td>
<td>
101.1%
</td>
<td>
29
</td>
<td>
20
</td>
<td>
69.0%
</td>
</tr>
<tr>
<td>
Marin Cilic
</td>
<td>
54%
</td>
<td>
64.9%
</td>
<td>
35.6%
</td>
<td>
100.5%
</td>
<td>
25
</td>
<td>
16
</td>
<td>
64.0%
</td>
</tr>
<tr>
<td>
Benoit Paire
</td>
<td>
55%
</td>
<td>
62.3%
</td>
<td>
37.6%
</td>
<td>
99.9%
</td>
<td>
31
</td>
<td>
18
</td>
<td>
58.1%
</td>
</tr>
<tr>
<td>
Christian Garin
</td>
<td>
58%
</td>
<td>
63.1%
</td>
<td>
36.8%
</td>
<td>
99.9%
</td>
<td>
29
</td>
<td>
16
</td>
<td>
55.2%
</td>
</tr>
<tr>
<td>
Fabio Fognini
</td>
<td>
57%
</td>
<td>
60.2%
</td>
<td>
39.5%
</td>
<td>
99.7%
</td>
<td>
22
</td>
<td>
14
</td>
<td>
63.6%
</td>
</tr>
<tr>
<td>
Radu Albot
</td>
<td>
55%
</td>
<td>
61.9%
</td>
<td>
37.3%
</td>
<td>
99.2%
</td>
<td>
27
</td>
<td>
18
</td>
<td>
66.7%
</td>
</tr>
<tr>
<td>
Egor Gerasimov
</td>
<td>
53%
</td>
<td>
64.2%
</td>
<td>
34.9%
</td>
<td>
99.1%
</td>
<td>
11
</td>
<td>
9
</td>
<td>
81.8%
</td>
</tr>
<tr>
<td>
Nick Kyrgios
</td>
<td>
60%
</td>
<td>
69.3%
</td>
<td>
29.6%
</td>
<td>
98.9%
</td>
<td>
29
</td>
<td>
18
</td>
<td>
62.1%
</td>
</tr>
<tr>
<td>
Lucas Pouille
</td>
<td>
50%
</td>
<td>
64.0%
</td>
<td>
33.3%
</td>
<td>
97.3%
</td>
<td>
27
</td>
<td>
14
</td>
<td>
51.9%
</td>
</tr>
<tr>
<td>
Alexander Bublik
</td>
<td>
48%
</td>
<td>
62.2%
</td>
<td>
34.6%
</td>
<td>
96.8%
</td>
<td>
21
</td>
<td>
12
</td>
<td>
57.1%
</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
Principally, the reverse is true for the players listed above – instead, they enjoyed a higher win percentage than their service and return points won percentage would ordinarily dictate, and all also produced better tiebreak records than expected.
Interestingly, blind-backing players from this group also produced a positive ROI, albeit not as high as those in the undervalued group:
<table class=" article-table">
<tbody>
<tr>
<td>
Player
</td>
<td>
Matches
</td>
<td>
Profit/Loss
</td>
<td>
ROI
</td>
</tr>
<tr>
<td>
Stefanos Tsitsipas
</td>
<td>
17
</td>
<td>
-102
</td>
<td>
-6.00
</td>
</tr>
<tr>
<td>
Stan Wawrinka
</td>
<td>
11
</td>
<td>
266
</td>
<td>
24.18
</td>
</tr>
<tr>
<td>
Guido Pelia
</td>
<td>
11
</td>
<td>
-230
</td>
<td>
-20.91
</td>
</tr>
<tr>
<td>
Felix Auger-Aliassime
</td>
<td>
22
</td>
<td>
-93
</td>
<td>
-4.23
</td>
</tr>
<tr>
<td>
Marin Cilic
</td>
<td>
11
</td>
<td>
51
</td>
<td>
4.64
</td>
</tr>
<tr>
<td>
Benoit Paire
</td>
<td>
16
</td>
<td>
227
</td>
<td>
14.19
</td>
</tr>
<tr>
<td>
Christian Garin
</td>
<td>
17
</td>
<td>
103
</td>
<td>
6.06
</td>
</tr>
<tr>
<td>
Fabio Fognini
</td>
<td>
10
</td>
<td>
-187
</td>
<td>
-18.70
</td>
</tr>
<tr>
<td>
Radu Albot
</td>
<td>
6
</td>
<td>
-600
</td>
<td>
-100.00
</td>
</tr>
<tr>
<td>
Egor Gerasimov
</td>
<td>
14
</td>
<td>
401
</td>
<td>
28.64
</td>
</tr>
<tr>
<td>
Nick Kyrgios
</td>
<td>
10
</td>
<td>
51
</td>
<td>
5.10
</td>
</tr>
<tr>
<td>
Lucas Pouille
</td>
<td>
0
</td>
<td>
0
</td>
<td>
N/A
</td>
</tr>
<tr>
<td>
Alexander Bublik
</td>
<td>
15
</td>
<td>
406
</td>
<td>
27.07
</td>
</tr>
<tr>
<td>
Overall
</td>
<td>
160
</td>
<td>
293
</td>
<td>
1.83
</td>
</tr>
</tbody>
</table>
<h3>What has happened to the overperforming players?</h3>
Of the players from this group who have continued to perform well this year, Wawrinka’s underlying data has improved, while Paire has overperformed by around 5% on saving break points compared to his service points won percentage.
Bublik is in a similar position to the latter, although performing worse on return. Elsewhere, Egor Gerasimov is running 8-3 on tiebreaks this season with an absurd break point overperformance on return.
<div class="articleV2 unordered-list">
<ul>
<li><a style="color: #f50;" id="articleLink" href="https://www.pinnacle.com/en/betting-articles/Tennis/How-top-tennis-players-perform-against-each-other/6UY2B93UB4RBGG64" target="_blank">How the top tennis players perform against each other</a></li>
</ul>
</div>
However, with the exception of Wawrinka, those continuing to perform superbly amongst this group still had variance on their side and will almost certainly mean-revert downwards in the near future.
Naturally, at the time of writing the current season is two months in, meanwhile the value may have eradicated on the undervalued players based on last season’s data. However, this type of research can be performed at any time during the season, enabling you to gain insight into the value of such an approach going forward.
You can read the first article in this series by Dan exploring whether the ATP top ten have ‘clutch’ ability <a style="color: #f50;" id="articleLink" href="/betting-resources/en/tennis/atp-top-ten-clutch-ability/34m2khblmjg8ckz5" target="_blank">here</a>, the second studying the relationship between points won and win percentages in tennis&nbsp;<a style="color: #f50;" id="articleLink" href="/betting-resources/en/tennis/analysing-links-between-points-won-win-percentages-tennis/8ekjmvcevwmz2nlx" target="_blank">here</a> and the third looking at the influence of tiebreak points <a style="color: #f50;" id="articleLink" href="/betting-resources/en/tennis/influence-tiebreak-points-tennis/7dtj9s5wgtwtwmdx" target="_blank">here</a>.

Tennis odds

Identifying tennis players undervalued and overvalued by the betting market

In the last of a four-part series, we look at luck, variance and the fine margins which can decide outcomes in professional tennis, concluding with identifying which players are undervalued and overvalued by the betting market.

Article

With this year’s tennis season now underway, it is a good time to take an alternative look at how success and failure can emerge on the court. In the final article of a four-part series analysing variants in professional tennis, Dan Weston identifies which players could be under or overvalued by the betting market during the coming season.