While the FIFA World Cup is perhaps one of the soccer tournaments that attracts the most amount of betting and garners the most interest from fans, sponsors, and advertisers, it is also notoriously unpredictable and hard to bet on. This is partly due to the tournament only taking place once every four years, which means that teams and managers are subject to change. That said, there are certain strategies and approaches one can adopt to maximize one’s chances of making money by betting on the World Cup. Read on for a short list of some of the various tactics and strategies you can employ, all backed up with relevant statistics and useful data to help you decide how you’re going to bet in Russia in 2018.

In-Play Betting

The best strategy when it comes to such an unpredictable and emotional tournament as the World Cup is arguably to only place In-Play bets, a type of bet which is otherwise known as In-Game Betting. One of the reasons why the World Cup is so unpredictable can be determined by taking a look at the way the odds are calculated. One of the elements used is the Continental Advantage element. To put it simply, the host nation gets extra points when bookmakers are calculating their chances of success, and these points are attributable to the fervor and morale boost they get for being the hosts (see the table a bit further down showing which hosts have won the World Cup). A similar logic is applied to nations on the same continent as the host nation. While often a valid variable for measuring a team’s chances of success, as it often accurately reflects their determination, it can also prove to be a bit of a false friend.

To illustrate this point, let’s look at the end of the 2014 World Cup. After the Quarter-Finals, the South American teams had an overall positive success rate in regular time (90 minutes). They boasted a 0.78 rating in games played against teams from outside South America. European teams, in contrast, were only attributed a score of 0.57. Thus, logically, when we look at the Semi-Final match pitting the host nation, Brazil, against Germany, a European team, logic would suggest that the host nation should be on par with the German team, and perhaps even have an edge over them, and that this would be well reflected in the odds. It was to an extent, as can be seen by the odds below (which fluctuated a bit in the run up to the big day):

 

Brazil win odds

Germany Win Odds

Draw Odds

2.5

2.8

3.4

 

So, according to these odds, the smart money would have been on a narrow victory for Brazil. Well, Germany thrashed Brazil 7 – 1, in one of the most one-sided games of the tournament - and perhaps the worst defeat in the history of World Cup soccer - before going on to beat Argentina 1 – 0 in the Final. This result is, however, a tad atypical. Thus, using Poisson Analysis data might be the way to go when making your picks. Indeed, the way it uses big data means that such anomalies can be watered down a bit and not skew your statistics too much. With Poisson Analysis, also known as Poisson Distribution, you’re basically going to assign teams numbers based on your interpretation of data, converted into averages, using a rather complex mathematical formula (which roughly looks like this: P( x ; μ ) = ( e – μ ) ( μx ) / x! ). You don’t really need to understand the specifics pertaining to the formula for your purposes here, but it’s always good to read up on it as much as possible if you want to start doing some really advanced prediction models. For our purposes, suffice it to say that there are tons of spreadsheets and other mechanisms for applying the formula you can download after a quick search engine search, and for our purposes here, you’ll basically be taking the ready-made formula and inputting as much data as you can to help you make your picks. There are various calculators available online, using different variables depending on what you’re trying to calculate. A lot of the data here can be used for such models.

In-Play betting would have been ideal for that game, as when you realized that your initial goal estimate was wrong, you could have placed additional bets based on the number of goals after each goal was scored. For example, let’s say at the beginning of the game you placed a bet for there to be more than one goal. That’s a pretty safe bet. After the first couple of goals, you place an In-Play bet for there to be more than three goals. After the third goal, you place another bet for there to be more than four goals. And so on and so forth. If you’re good at anticipating an upcoming goal, then In-Play betting is definitely for you, as the odds are of course always slightly better before that goal is scored. Thus, it is usually more advantageous to bet on there being, say, more than four goals scored after the first goal is scored then waiting for the third goal to be scored to put your money down.

With an average of 2.75 goals (compared to 2.3 during the 2010 World Cup in South Africa) per game, you would be well served by betting on at least two or more goals per World Cup soccer match. Given that the number of goals scored during a World Cup has been holding steady over the last 50 years or so (only decreasing very slowly), chances are that the same will be true in Russia in 2018. Check out this table listing the average number and total number of goals scored during all the World Cup tournaments:

 

World Cup Host and Year

Total No of Goals

Average No of Goals

Uruguay 1930

70

3.89

Italy 1934

70

4.12

France 1938

84

4.67

Brazil 1950

88

4

Switzerland 1954

140

5.38

Sweden 1958

126

3.6

Chile 1962

89

2.78

England 1966

89

2.78

Mexico 1970

95

2.97

Germany 1974

97

2.55

Argentina 1978

102

2.68

Spain 1982

146

2.81

Mexico 1986

132

2.54

Italy 1990

115

2.21

United States 1994

141

2.71

France 1998

171

2.67

South Korea / Japan 2002

161

2.52

Germany 2006

147

2.3

South Africa 2010

143

2.23

Brazil 2014

171

2.7

 

Note that since the number of teams was increased in 1998 from 24 teams to 32 teams, the overall number of goals has been slightly higher than in previous decades, but the average number of goals per game continues to drop. Very slowly, but very surely.

Another great opportunity for In-Play betting in the World Cup has to do with the number of bookings that happen during the tournament. World Cups do indeed also have quite a high number of cards being dealt out to players. This makes sense, really, when you think about it. When is a soccer player going to be as stressed and under pressure as when he is playing for his country, and really mustn’t let his team and his nation down? When do people usually snap and go nuts, or simply make mistakes? When they are under pressure.

In 2014, an average 2.9 cards were given out to players every game. Although there were slightly less of them in 2014 compared to the 2010 World Cup (3.8 bookings per game), it is still worth your while to bet on at least 2 bookings per game. Take a look at the following statistics for bookings between 1982 and 2010:

 

Yellow Cards / Red Cards

Total

No of Matches

Average

South Africa 2010

245 / 17

64

3.83 / 0.27

Germany 2006

307 / 28

64

4.80 / 0.44

Korea/Japan 2002

272 / 17

64

4.25 / 0.27

France 98

258 / 22

64

4.03 / 0.34

USA 94

235 / 15

52

4.52 / 0.34

Italy 90

162 / 16

52

3.12 / 0.31

Mexico 86

133 / 8

52

2.56 / 0.15

Spain 82

98 / 5

52

1.88 / 0.12

 

Personally, I would avoid betting on Red Cards altogether, and opt for the far safer and far surer notion of betting on Yellow Cards. Based on the statistics above, you could quite safely bet on there being more than 2 Yellow Cards per game. You would win those bets the vast majority of the time. There is a caveat to this self-imposed rule, though. I watch every single World Cup soccer game religiously, and can usually sense when there is tension on the field. It is in those cases that I might allow myself a flutter and put something down on a Red Card, especially if there have already been a fair few yellow cards dealt out already. Take a look below at the top ten players to get Red Cards during a World Cup:

 

Player

Total

Time

Team

Svetoslav Dyakov

7

572

Bulgaria

Alexandru Gaţcan

6

716

Moldova

Yevhen Khacheridi

6

767

Ukraine

Savo Pavićević

5

477

Montenegro

Davide Simoncini

5

630

San Marino

Boštjan Cesar

5

719

Slovenia

Franz Burgmeier

5

720

Liechtenstein

Lorik Cana

5

810

Albania

Cristiano Ronaldo

5

900

Portugal

Varazdat Haroyan

4

343

Armenia

 

If I were to take away one important idea from the statistics above, it would be the following: Red Cards tend to be given around the same time, so this should inform your Red Card In-Play betting strategy. Indeed, they all seem to take place, according to the table above, when the game is in full swing and pivotal decisions need to be made; i.e. when players are feeling the pressure.

Another thing to keep in mind, of course, is the referee. Indeed, by analyzing their history, you can paint yourself a pretty good picture regarding their propensity to doll out punishment willy-nilly, or whether they usually opt instead to simply give more warnings. Or if they simply are bad referees and tend to miss lots of fouls! Take a look at the following table listing the 2014 World Cup refs and their respective stats. Some of them may not be at the 2018 Russia World Cup, but others no doubt will be:

 

Referee

Nationality

International Matches

Red Cards

Penalties

Averages Per Game (Yellow/Red/Pens)

Alioum

Cameroon

48

7

13

3.13/0.15/0.27

Daniel Bennett

South Africa

63

11

14

3.24/0.17/0.22

Noumandiez Doue

Ivory Coast

57

13

13

3.84/0.23/0.23

Bakary Gassama

Gambia

54

6

7

2.78/0.11/0.13

Djamel Haimoudi

Algeria

65

10

15

3.35/0.15/0.23

Alireza Faghani

Iran

58

19

22

4.62/0.33/0.38

Ravshan Irmatov

Uzbekistan

114

26

14

3.46/0.23/0.12

Yuichi Nishimura

Japan

91

13

18

3.59/0.14/0.20

Nawaf Shukralla

Bahrain

65

19

11

4.38/0.29/0.17

Benjamin Williams

Australia

77

27

18

4.16/0.35./0.23

Felix Brych

Germany

73

17

24

3.45/0.23/0.33

Cuneyt Cakir

Turkey

81

17

21

4.10/0.21/0.27

Jonas Eriksson

Sweden

89

16

16

3.16/0.18/0.18

Bjorn Kuipers

Netherlands

81

17

21

3.69/0.21/0.26

Milorad Mazic

Serbia

61

16

17

4.46/0.26/0.28

Svein Oddvar Moen

Norway

77

13

13

3.37/0.17/0.17

Pedro Proenca

Portugal

89

14

20

3.83/0.16/0.22

Nicola Rizzoli

Italy

74

10

24

3.93/0.14/0.32

Carlos Velasco Carballo

Spain

53

5

18

3.72/0.09/0.34

Howard Webb

UK

111

21

23

4.05/0.19/0.21

Joel Aguilar

El Salvador

89

29

17

4.28/0.33/0.19

Mark Geiger

USA

39

12

10

3.79/0.31/0.26

Walter Lopez

Guatemala

59

22

10

4.36/0.37/0.17

Roberto Moreno

Panama

96

20

8

3.60/0.21/0.08

Marco Rodriguez

Mexico

79

51

29

4.43/0.65/0.37

Norbert Hauta

Tahiti

45

12

9

2.53/0.27/0.20

Peter O'Leary

New Zealand

42

8

8

3.67/0.19/0.19

Victor Carrillo

Peru

75

32

31

4.67/0.43/0.41

Enrique Osses

Chile

80

20

19

4.66/0.25/0.24

Nestor Pitana

Argentina

38

9

7

5.03/0.24/0.18

Sandro Ricci

Brazil

38

17

11

4.55/0.45/0.29

Wilmar Roldan

Columbia

73

40

27

5.22/0.55/0.37

Carlos Vera

Ecuador

65

24

14

4.58/0.37/0.22

 

With all of these referees handing out well over 3 Yellow Cards per game, it is definitely, as previously stated, well worth your while to bet on Yellow Cards instead of Red Cards. Indeed, there is roughly a 20 % chance of their being a Red Card, or in other terms, one in every five games will see a player get a Red Card. Slim pickings! But, again, if there is just that kind of electricity on the field and you’re good at anticipating the fouls, by all means place a bet on a Red Card. Although it can help to know which teams are the rowdiest and therefore which ones are likely to attract the referee’s wrath. Check out the table below of the ten most sanctioned teams during the 2014 World Cup (note that this is based on yellow cards); will they also be the rowdiest in 2018?

 

Team

Yellow Cards

Red Cards

Brazil

14

0

Costa Rica

12

1

Netherlands

11

0

Greece

8

1

Uruguay

8

1

Argentina

8

0

Mexico

8

0

Belgium

7

1

Honduras

7

1

Chile

7

0

Ivory Coast

7

0

 

Based on the above data, it’s a safe bet to assume Brazil will get their fair share of Yellow Cards in 2018! As a matter of fact, if a team happens to be from South America, you should factor this in as an additional reason to be on them getting a Yellow Card… To further illustrate this point, before we move on, take a look at the most expulsions and Red Cards per country for all the World Cups:

11 - Brazil

10 - Argentina

9 – Uruguay

8 - Italy, Cameroon

7 - Netherlands, (West) Germany

6 - Mexico, Czechoslovakia/Czech Republic, France, Portugal

5 - Hungary, Yugoslavia/Serbia

4 - United States, Australia, Croatia

3 - Soviet Union, Denmark, Bulgaria, Sweden, England, Chile, Belgium

2 - Bolivia, Paraguay, Turkey, South Korea, Algeria, South Africa, Honduras

1 - Romania, Austria, Spain, Peru, United Arab Emirates, Ecuador, Northern Ireland, Canada, Iraq, Scotland, Saudi Arabia, China, Senegal, Slovenia, Jamaica, Zaïre, Ghana, Tunisia, Ukraine, Angola, Poland, Togo, Trinidad & Tobago, Côte d'Ivoire, Switzerland, Nigeria, Costa Rica, Greece

Three South American countries take the top three spots. This should also inform the way you’re going to bet on Red Cards during a World Cup.

Picking the Top Scorer

Picking the top scorers during a World Cup should be based on quite a few elements. Firstly, which players have scored a lot of goals in games leading up to the World Cup? How have they performed in their national leagues, or in tournaments such as the Champions League or the Europa League? Reading other articles on those tournaments and on national leagues should help you answer the first part of this question. Secondly, newcomers aside, which players kept their cool and managed to score a decent amount of goals in previous World Cups. Assuming they haven’t reached retirement age and are going to be participating in the 2018 Russia World Cup, the following data should come in handy when you’re making your picks. Note the table below listing the 2014 World Cup’s top scorers. Will the 2018 World Cup’s top scorer be someone from this list?

6 - James Rodriguez (Colombia)

5 - Thomas Muller (Germany)

4 - Robin van Persie (Netherlands)

4 - Neymar (Brazil)

4 - Lionel Messi (Argentina)

3 - Karim Benzema (France)

3 - Arjen Robben (Netherlands)

3 - Enner Valencia (Ecuador)

3 - Xherdan Shaqiri (Switzerland)

3 - Andre Schurrle (Germany)

Note: Numbers indicate numbers of goals scored. Subsequent players on this list scored 2 goals or less.

The following table listing the all-time record holders for number of goals scored during a World Cup. Those German strikers are to be watched out for:

 

Player

Country

No of Goals Scored During a World Cup

Miroslav Klose

Germany

16

Ronaldo

Brazil

15

Gerd Müller

Germany

14

Just Fontaine

France

13

Pele

Brazil

12

Jürgen Klinsmann

Germany

11

Sandor Kocsis

Hungary

11

Gabriel Batistuta

Argentina

10

Teofilo Cubillas

Peru

10

Grzegorz Lato

Poland

10

Gary Lineker

England

10

Thomas Müller

Germany

10

Helmut Rahn

Germany

10

 

Five players from Germany feature on this list, two from Brazil, and only one from other countries. Thomas Müller is indeed touted as a possible contender for the top spot at the next World Cup, as he is only 26 years old, and could thus quite feasibly exceed his compatriot Miroslav Klose. A good way to add newcomers to this shortlist would be to analyze the best passers. Those players who make the most passes that end up in goals. Here is a shortlist of some of the best passers in the last World Cup. Unsurprisingly, the top spot goes to a German, which supports the underlying logic herein:

 

Ranking

Player

Team

1

Toni Kroos

Germany

2

Wesley Sneijder

Netherlands

3

Iniesta

Spain

4

Xavi

Spain

5

Andrea Pirlo

Italy

 

Kroos is pivotal to the German team’s success, having completed around 2,000 successful passes in the Bundesliga for his club, Bayern München.

Picking the World Cup Golden Ball Winner

It is very hard to anticipate who will be the next Golden Ball Winner in the upcoming 2018 World Cup. The best way is to keep a close watch on the players who are the driving forces behind their team. My favorite examples is of course Oliver Kahn, the German captain during the 2002 World Cup. Only having been awarded in its current format since 1982, we’re only going to count Golden Balls back to 1982. Players of note who won it before 1982 include Pele. It’s not necessarily given to players who score the most goals. Rather it is given to noteworthy players who are credited with getting their nation at least into the final (goalkeeper Oliver Kahn won it in 2002). So if you enjoy watching every match, it may be interesting to jot down which players seem to be carrying their teams. Note the following table listing the players who have won the Golden Ball title:

 

Year

Host

Winner

1982

Spain

Paolo Rossi

1986

Mexico

Diego Maradona

1990

Italy

Salvatore Schillaci

1994

USA

Romario

1998

France

Ronaldo

2002

Japan/South Korea

Oliver Kahn

2006

Germany

Zinedine Zidane

2010

South Africa

Diego Forlan

2014

Brazil

Lionel Messi

 

Betting to Bite: The Improbable Might Just Pay Off Big Time

For a $ 5 bet, you could’ve won around $ 750 if you had bet for a 2014 Word Cup player to bite another player. Indeed, this infamous proved to be an accurate bet last time around, as Suarez bit Giorgio Chiellini during the oh so decisive Group D match between Uruguay and Italy.

By the same token, it may well be worth your while to place a bet following what a psychic octopus might predict is going to happen for the 2018 Russia World Cup. Paul the Octopus famously predicted all eight winners for the tournament, with a 1 in 256 chance of doing so correctly. Of course, many other animals also made ‘predictions’, but it just so happened, out of sheer coincidence or luck, that this is the one that was reported in the media. There have been studies that show an arguably causal link between predictions and their potential fulfilment. Simply put, if something is predicted, it increases the chances of it actually happening ever so slightly.

Reasons for this usually include the notion that people involved in said predictions might get wind of their ‘fate’, and thus be more comfortable and relaxed about fulfilling it. Of course, this is highly speculative, and statisticians looking at this conundrum with very serious studies haven’t quite nailed the underlying dynamics that drive such scenarios. Nonetheless, for a $ 1 bet, such outlandish payouts aren’t unheard of and could pay out big time. If you’re interested in unusual bets, why not bet on multiple octopuses’ predictions?!

Predicting the World Cup Winner

Picking the winner in any tournament is no easy feat, let alone if you intend to pick the winner before the competition has started, something I’m going to try and help you do here. With the World Cup, it is even harder, because every edition of the tournament is very different to the last. This, as is mentioned elsewhere, has a lot to do with the fact that the competition only takes place every four years, and a lot can happen in four years. Below, you’ll find a list of the countries which hosted the World Cup, as well as the countries that actually ended up winning the trophy. Note how many World Cup winners have been host nations:

 

Year

Host

Host confederation

Winner

Winner confederation

Runner-up

No. of participants

1930

Uruguay

CONMEBOL

Uruguay

CONMEBOL

Argentina

13

1934

Italy

UEFA

Italy

UEFA

Czechoslovakia

16

1938

France

UEFA

Italy

UEFA

Hungary

16

1950

Brazil

CONMEBOL

Uruguay

CONMEBOL

Brazil

13

1954

Switzerland

UEFA

W. Germany

UEFA

Hungary

16

1958

Sweden

UEFA

Brazil

CONMEBOL

Sweden

16

1962

Chile

CONMEBOL

Brazil

CONMEBOL

Czechoslovakia

16

1966

England

UEFA

England

UEFA

W. Germany

16

1970

Mexico

CONMEBOL

Brazil

CONMEBOL

Italy

16

1974

W. Germany

UEFA

W. Germany

UEFA

Netherlands

16

1978

Argentina

CONMEBOL

Argentina

CONMEBOL

Netherlands

16

1982

Spain

UEFA

Italy

UEFA

W. Germany

24

1986

Mexico

CONMEBOL

Argentina

CONMEBOL

W. Germany

24

1990

Italy

UEFA

W. Germany

UEFA

Argentina

24

1994

United States

CONCACAF

Brazil

CONMEBOL

Italy

24

1998

France

UEFA

France

UEFA

Brazil

32

2002

South Korea & Japan

AFC

Brazil

CONMEBOL

Germany

32

2006

Germany

UEFA

Italy

UEFA

France

32

2010

South Africa

CAF

Spain

UEFA

Netherlands

32

2014

Brazil

CONMEBOL

Germany

UEFA

Argentina

32

 

The above table lends credence to the notion that the host nation has a decent advantage, and is not to be underestimated when it comes to picking a winner for the tournament. By the same token, check out the chart below listing the 10 countries who have been runner-ups for the title the most times. This could help you on your eventual Paul the Octopus type quests:

 

Country

No of Times Runner-Up

Germany

4

Netherlands

3

Argentina

3

Czech Republic

2

Brazil

2

Czechoslovakia

2

Italy

2

Hungary

2

France

1

Sweden

1

 

That said, given that the tournament only happens once every four years, past performance data may not be as useful as with other, annual tournaments. Even so, with the data included in this article, one can nonetheless denote certain trends that tend to form. Likewise, one can also determine what type of bets one should place. Here is a probability chart for the 2014 World Cup, published just before the beginning of the competition. Note that Germany, the winners, are in third position:

 

 

Based on this, and on past performance data, it might well be worth your while to place an early bet on all eight favorite teams. The chances that one of them will be the winners are indeed quite high. Casting the net wide might also be preferable to placing a single bet on the final match based on statistics, big data, and algorithms touted by eminent mathematicians. Indeed, if you had done that, you would have been placing a bet on Brazil and Argentina to be in the final, with Brazil winning by a slight margin. How wrong you would have been! That is the magic of the World Cup. All bets are going to be off slightly (pun intended). Hence why the No 1 strategy listed here is to use In-Play Betting strategies. That said, for the 2018 World Cup, if you intend to pick a winner soon, I would be placing bets on the 12 following teams:

2018 World Cup Winner Odds – Average Calculated Based on Odds from 7 Different Bookmakers as of November 2015 for 12 National Teams

 

Country

Ladbrokes

Paddypower

Bet365

Betvictor

Betfred

William Hill

Skybet

Avg.

Germany

5.0

5.5

6

6

5

6

6

5.64

Argentina

6.5

8

9

9

6

9

8

7.92

Spain

9

9

9

8

8

10

9

8.85

Brazil

9

9

9

8

8

9

9

8.71

France

13

13

13

13

12

13

13

12.85

Netherlands

17

17

19

17

15

17

12

16.28

Belgium

17

19

21

17

15

21

17

18.14

Italy

17

17

17

21

18

15

13

16.85

England

26

21

21

21

25

21

21

22.28

Colombia

21

23

26

21

21

26

23

23

Portugal

31

21

26

34

31

34

29

29.42

Russia

26

21

34

34

26

34

21

28

Note: All odds have been converted to decimal odds

 

The chances are indeed high that at least one of these teams will be walking away with the trophy. It is even worth your while betting on Russia. Yes, Russia! While their past performances hardly inspire confidence in their abilities to lift the trophy, the host nations being victorious so often in the past means that you should include them in your pick. Or you could simply base your bets on how many World Cup trophies have been won by each nation. Being successful in the past means they’ll be that much more confident in their abilities to repeat their past successes. Check out the top World Cup winners listed below by number of trophies won:

 

Country

No of Trophies

Brazil

5

Germany

4

Italy

4

Uruguay

2

Argentina

2

England

1

Spain

1

France

1

 

Placing an early bet is not necessarily a bad idea. Although it may be a long shot, there is a rather high chance that the winner will be in the above lists. As we get closer to the beginning of the competition, odds will of course change, and they have a tendency to get less good as more details about the teams are revealed and as our prediction models get more accurate.

In a nutshell, this is what I will be doing: placing early bets based on statistics and prediction models, then adjusting my aim and rectifying misfires with In-Play betting. May fortune smile kindly upon you!

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