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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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Side bets provide an exciting way to make Blackjack games more interesting whilst offering you a greater number of ways to win. So what are side bets, what side bets are available and are they worth it? Read on to find out.

Blackjack Side Bets Explained

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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A corner is one of the most inexplicably exciting events in soccer. Only around three per cent of them lead to a goal, but you can guarantee that the attacking team’s fans will roar their approval and encouragement if their team are awarded one. Read on to find out how you can benefit from betting on corners.

Corners betting in soccer: Value in a lesser-known market

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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Poisson Distribution: Predict the score in soccer betting

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.

How to Calculate Expected Value

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>.

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In general, indoor hard is the second quickest surface on the ATP Tour, behind grass, with outdoor hard and clay generally slower. The table below illustrates the impact that the general surface has on both service points won percentages, and mean aces per game figures, across the last three years (data correct at February 4, 2019).
<div class="table-holder-article-content">
<div class="table-modal">
<div class="table-modal-head">
<div class="table-modal-head-inner">
<h2>Indoor hard data</h2>
</div>
</div>
<div class="table-modal-content">
<div class="article-table-content">
<table class=" article-table">
<tbody>
<tr>
<td>
Surface
</td>
<td>
Service Points Won %
</td>
<td>
Aces Per Game
</td>
</tr>
<tr>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
</tr>
<tr>
<td>
Grass
</td>
<td>
66.1
</td>
<td>
0.63
</td>
</tr>
<tr>
<td>
Indoor Hard
</td>
<td>
64.2
</td>
<td>
0.58
</td>
</tr>
<tr>
<td>
Outdoor Hard
</td>
<td>
63.7
</td>
<td>
0.56
</td>
</tr>
<tr>
<td>
Clay
</td>
<td>
62.3
</td>
<td>
0.38
</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
Here we can see the consistency in rank of surface between service points won percentage and aces per game numbers, with grass being the highest for both, and clay being considerably the lowest across both metrics.
Indoor hard has only marginally higher figures than outdoors, but that doesn’t stop players being specialists in the area. Last year, several lower level ATP or Challenger players - such as Mirza Basic and Marius Copil - gave very good accounts of themselves in main tour events played on indoors, while Joao Sousa a few years ago had a magnificent record in 250 level tournaments under a roof.

<div class="articleV2 unordered-list">
<ul>
<li><a style="color: #f50;" id="articleLink" href="/betting-resources/en/tennis/how-to-bet-on-tennis/qrf267l88zejp4j4">How to bet on tennis: A beginner’s guide to tennis betting</a></li>
</ul>
</div>

<h3>Which players benefit from indoor conditions?</h3>
With this in mind, understanding which players have benefitted from conditions indoors across the last two years would be a useful exercise, and using a comparison between player service and return data is a good way to do so.
The table below looks at the two year service and return points won for players in the ATP Top 50, split by both indoor and outdoor hard (correct at January 31, 2019), with the players listed able to generate combined numbers indoors greater than or equal to 2.0% more than their outdoor figures. The players in this list could potentially yield some value in the coming weeks indoors.
<div class="table-holder-article-content">
<div class="table-modal">
<div class="table-modal-head">
<div class="table-modal-head-inner">
<h2>ATP Top 50 hard vs. indoor hard best players</h2>
</div>
</div>
<div class="table-modal-content">
<div class="article-table-content">
<table class=" article-table">
<tbody>
<tr>
<td>
Player
</td>
<td>
Rank
</td>
<td>
2 Year Service Points Won %
</td>
<td>
2 Year Return Points Won %
</td>
<td>
2 Year Combined Points Won %
</td>
<td>
2 Year Service Points Won %
</td>
<td>
2 Year Return Points Won %
</td>
<td>
2 Year Combined Points Won %
</td>
<td>
2 Year Combined Points Won %
</td>
</tr>
<tr>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
Indoor Hard
</td>
<td>
Indoor Hard
</td>
<td>
Indoor Hard
</td>
<td>
Outdoor Hard
</td>
<td>
Outdoor Hard
</td>
<td>
Outdoor Hard
</td>
<td>
Indoor Hard-Outdoor Hard
</td>
</tr>
<tr>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
</tr>
<tr>
<td>
Klizan
</td>
<td>
38
</td>
<td>
63.4
</td>
<td>
36.8
</td>
<td>
100.2
</td>
<td>
62.3
</td>
<td>
32.4
</td>
<td>
94.7
</td>
<td>
5.5
</td>
</tr>
<tr>
<td>
Simon
</td>
<td>
31
</td>
<td>
63.2
</td>
<td>
41.3
</td>
<td>
104.5
</td>
<td>
62.1
</td>
<td>
37.5
</td>
<td>
99.6
</td>
<td>
4.9
</td>
</tr>
<tr>
<td>
Monfils
</td>
<td>
33
</td>
<td>
68.3
</td>
<td>
38.1
</td>
<td>
106.4
</td>
<td>
63.4
</td>
<td>
38.1
</td>
<td>
101.5
</td>
<td>
4.9
</td>
</tr>
<tr>
<td>
Edmund
</td>
<td>
29
</td>
<td>
68.6
</td>
<td>
36.2
</td>
<td>
104.8
</td>
<td>
65.2
</td>
<td>
35.7
</td>
<td>
100.9
</td>
<td>
3.9
</td>
</tr>
<tr>
<td>
Khachanov
</td>
<td>
11
</td>
<td>
68.0
</td>
<td>
38.2
</td>
<td>
106.2
</td>
<td>
66.2
</td>
<td>
36.2
</td>
<td>
102.4
</td>
<td>
3.8
</td>
</tr>
<tr>
<td>
Verdasco
</td>
<td>
26
</td>
<td>
66.7
</td>
<td>
38.4
</td>
<td>
105.1
</td>
<td>
63.6
</td>
<td>
38.3
</td>
<td>
101.9
</td>
<td>
3.2
</td>
</tr>
<tr>
<td>
Basilashvili
</td>
<td>
22
</td>
<td>
64.3
</td>
<td>
37.0
</td>
<td>
101.3
</td>
<td>
60.8
</td>
<td>
37.4
</td>
<td>
98.2
</td>
<td>
3.1
</td>
</tr>
<tr>
<td>
Gasquet
</td>
<td>
27
</td>
<td>
66.2
</td>
<td>
37.4
</td>
<td>
103.6
</td>
<td>
63.0
</td>
<td>
37.8
</td>
<td>
100.8
</td>
<td>
2.8
</td>
</tr>
<tr>
<td>
Goffin
</td>
<td>
21
</td>
<td>
64.4
</td>
<td>
41.2
</td>
<td>
105.6
</td>
<td>
64.3
</td>
<td>
39.0
</td>
<td>
103.3
</td>
<td>
2.3
</td>
</tr>
<tr>
<td>
Raonic
</td>
<td>
14
</td>
<td>
77.9
</td>
<td>
29.7
</td>
<td>
107.6
</td>
<td>
71.8
</td>
<td>
33.8
</td>
<td>
105.6
</td>
<td>
2.0
</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
This data shows that ten players have been able to boast considerably better numbers indoors, with Martin Klizan leading the way. Last year, the Slovakian - a rather inconsistent competitor in general - reached the final indoors in St. Petersburg, beating Stan Wawrinka, Denis Shapovalov and Fabio Fognini on the way there - and won in Rotterdam in 2016. He’s also reached a semi-final indoors, and several quarter-finals, since the start of 2016.
We can also see that three French players - Gilles Simon, Gael Monfils and Richard Gasquet - have better data indoors, and with several French indoor events taking place in the next few weeks, this trio could be one to keep an eye on.
For example, this week’s indoor tournament in Montpellier has had eight tournaments held there this decade. In these events, there have been six French winners and six French runners-up - only four non-French players in eight years have made the final.
<h3>Which players perform worse in indoor tournaments?</h3>
As will have been anticipated, there will also be players who have considerably worse records indoors, and who may be worth avoiding or opposing in the betting markets when they play tournaments on that surface. The table below looks at the two year service and return points won for players in the ATP Top 50, split by both indoor and outdoor hard (correct at January 31, 2019), with the players listed able to generate combined numbers outdoors greater than or equal to 2.0% more than their indoor figures.
<div class="table-holder-article-content">
<div class="table-modal">
<div class="table-modal-head">
<div class="table-modal-head-inner">
<div class="table-modal-head">
<div class="table-modal-head-inner">
<h2>ATP Top 50 hard vs. indoor hard worst players</h2>
</div>
</div>
<div class="table-modal-content">
<div class="article-table-content"></div>
</div>
</div>
</div>
<div class="table-modal-content">
<div class="article-table-content">
<table class=" article-table">
<tbody>
<tr>
<td>
Player
</td>
<td>
Rank
</td>
<td>
2 Year Service Points Won %
</td>
<td>
2 Year Return Points Won %
</td>
<td>
2 Year Combined Points Won %
</td>
<td>
2 Year Service Points Won %
</td>
<td>
2 Year Return Points Won %
</td>
<td>
2 Year Combined Points Won %
</td>
<td>
2 Year Combined Points Won %
</td>
</tr>
<tr>
<td>
&nbsp;.
</td>
<td>
&nbsp;l
</td>
<td>
Indoor Hard
</td>
<td>
Indoor Hard
</td>
<td>
Indoor Hard
</td>
<td>
Outdoor Hard
</td>
<td>
Outdoor Hard
</td>
<td>
Outdoor Hard
</td>
<td>
Indoor Hard-Outdoor Hard
</td>
</tr>
<tr>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
<td>
&nbsp;,
</td>
</tr>
<tr>
<td>
Carreno-Busta
</td>
<td>
23
</td>
<td>
53.1
</td>
<td>
34.2
</td>
<td>
87.3
</td>
<td>
64.2
</td>
<td>
37.8
</td>
<td>
102.0
</td>
<td>
-14.7
</td>
</tr>
<tr>
<td>
Cecchinato
</td>
<td>
19
</td>
<td>
59.2
</td>
<td>
26.8
</td>
<td>
86.0
</td>
<td>
64.1
</td>
<td>
32.5
</td>
<td>
96.6
</td>
<td>
-10.6
</td>
</tr>
<tr>
<td>
Johnson
</td>
<td>
34
</td>
<td>
58.5
</td>
<td>
31.9
</td>
<td>
90.4
</td>
<td>
66.1
</td>
<td>
33.6
</td>
<td>
99.7
</td>
<td>
-9.3
</td>
</tr>
<tr>
<td>
Querrey
</td>
<td>
48
</td>
<td>
66.6
</td>
<td>
31.8
</td>
<td>
98.4
</td>
<td>
68.2
</td>
<td>
36.4
</td>
<td>
104.6
</td>
<td>
-6.2
</td>
</tr>
<tr>
<td>
Cilic
</td>
<td>
10
</td>
<td>
65.9
</td>
<td>
35.1
</td>
<td>
101.0
</td>
<td>
67.4
</td>
<td>
39.1
</td>
<td>
106.5
</td>
<td>
-5.5
</td>
</tr>
<tr>
<td>
Fritz
</td>
<td>
40
</td>
<td>
63.1
</td>
<td>
32.7
</td>
<td>
95.8
</td>
<td>
65.1
</td>
<td>
36.1
</td>
<td>
101.2
</td>
<td>
-5.4
</td>
</tr>
<tr>
<td>
Coric
</td>
<td>
13
</td>
<td>
65.2
</td>
<td>
34.0
</td>
<td>
99.2
</td>
<td>
66.1
</td>
<td>
37.7
</td>
<td>
103.8
</td>
<td>
-4.6
</td>
</tr>
<tr>
<td>
Jaziri
</td>
<td>
43
</td>
<td>
59.9
</td>
<td>
31.5
</td>
<td>
91.4
</td>
<td>
60.3
</td>
<td>
35.3
</td>
<td>
95.6
</td>
<td>
-4.2
</td>
</tr>
<tr>
<td>
Mayer L
</td>
<td>
49
</td>
<td>
65.1
</td>
<td>
30.4
</td>
<td>
95.5
</td>
<td>
64.9
</td>
<td>
34.3
</td>
<td>
99.2
</td>
<td>
-3.7
</td>
</tr>
<tr>
<td>
Thiem
</td>
<td>
8
</td>
<td>
64.7
</td>
<td>
35.5
</td>
<td>
100.2
</td>
<td>
66.2
</td>
<td>
37.6
</td>
<td>
103.8
</td>
<td>
-3.6
</td>
</tr>
<tr>
<td>
Isner
</td>
<td>
9
</td>
<td>
72.2
</td>
<td>
27.7
</td>
<td>
99.9
</td>
<td>
73.0
</td>
<td>
29.9
</td>
<td>
102.9
</td>
<td>
-3.0
</td>
</tr>
<tr>
<td>
Lajovic
</td>
<td>
42
</td>
<td>
58.8
</td>
<td>
36.7
</td>
<td>
95.5
</td>
<td>
63.2
</td>
<td>
35.3
</td>
<td>
98.5
</td>
<td>
-3.0
</td>
</tr>
<tr>
<td>
Shapovalov
</td>
<td>
25
</td>
<td>
65.7
</td>
<td>
33.0
</td>
<td>
98.7
</td>
<td>
64.8
</td>
<td>
36.5
</td>
<td>
101.3
</td>
<td>
-2.6
</td>
</tr>
<tr>
<td>
Fognini
</td>
<td>
15
</td>
<td>
62.2
</td>
<td>
36.8
</td>
<td>
99.0
</td>
<td>
61.8
</td>
<td>
39.7
</td>
<td>
101.5
</td>
<td>
-2.5
</td>
</tr>
<tr>
<td>
Millman
</td>
<td>
36
</td>
<td>
62.7
</td>
<td>
37.3
</td>
<td>
100.0
</td>
<td>
63.2
</td>
<td>
38.8
</td>
<td>
102.0
</td>
<td>
-2.0
</td>
</tr>
</tbody>
</table>
</div>
</div>
</div>
</div>
It is evident from this data that the worst players indoors deviate considerably more from their outdoor figures than the best players, and certainly, the likes of Pablo Carreno-Busta, Marco Cecchinato and Steve Johnson have really struggled during indoor conditions in the last couple of years.
<h3>What role does geography play?</h3>
The list generally comprises of return-orientated players and perhaps strangely to some, Americans. Very little professional tennis is played indoors in America, and perhaps this has some knock-on effect to their high profile competitors.
With the aforementioned Johnson, as well as Sam Querrey and John Isner all having a relatively serve-orientated game style, their failure to adapt to and thrive in slightly quicker conditions than average appears rather odd initially, but the lack of events indoors in America could be a logical explanation.
Hopefully the above article has given you some thoughts about how to evaluate players indoors during the next few weeks, and understanding which players are likely to thrive or struggle in the anticipated conditions is critical when entering the markets.

Tennis odds

With the indoor hard season getting underway, our resident tennis expert Dan Weston looks at which players have shown an upgrade in ability on the surface, compared to their outdoor data.