Soccer Betting Resources

Friday Max betting tips & analysis

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31.08.2018 Friday Max betting tips & analysis Our predictions for matches are based on a large number of factors such as direct meetings, last matches, lineup, standings and so on. By visiting our website betpluswin.com you will increase your winning chances. Friday Max betting tips & analysis Solobet Betting analysis & tips today and tomorrow predictions 1×2 Solobet football prediction for tomorrow, victor prediction, accurate football prediction, best football prediction site free, solo prediction, topbet prediction tomorrow predictions, prediction tomorrow, soccer 13 predictions for tomorrow, top bet prediction, topbet predict, all soccer predictions tomorrow, correct score tomorrow tomorrow prediction, top prediction, tomorrow football prediction, victor predict, accurate football predictions for free, best,predicte, betloy prediction football prediction tomorrow, football prediction.com, prediction football tomorrow, predictions for tomorrow soccer matches, sure wins for tomorrow tomorrow matches predictions, tomorrow soccer prediction Villarreal – Girona 31.08.2018 |Tip of the Day Over Under, Free Daily betting tips & analysis, H2H Statistic Predictions, Bet and Win Predictions Football, top btts predictions for today | Villarreal is ranked on the 13th place in the standings with 1 points, 1 goals scored and 2 goals received in the last 2 leaguegames. Girona is ranked on the 16th place in the standings with 1 points, 1 goals scored and 4 goals received in the last 2 leaguegames. H2H Statistic and Predictions Last 5 matches played for: Villarreal & Girona 2018-03-03 Villarreal Girona 0 : 2 / 2017-10-15 Girona Villarreal 1 : 2 / Last 5 matches played for: Villarreal 2018-08-26 Sevilla Villarreal 0 : 0 D 2018-08-18 Villarreal Real Sociedad 1 : 2 L 2018-05-19 Villarreal Real Madrid 2 : 2 D 2018-05-12 Deportivo La Coruña Villarreal 2 : 4 W 2018-05-09 Barcelona Villarreal 5 : 1 L Last 5 matches played for: Girona 2018-08-26 Girona Real Madrid 1 : 4 L 2018-08-17 Girona Real Valladolid 0 : 0 D 2018-05-19 Las Palmas Girona 1 : 2 W 2018-05-12 Girona Valencia 0 : 1 L 2018-05-05 Girona Eibar 1 : 4 L Last 15 Matches (Win, Lose, Draw, Over/Under 2.5, BTTS YES/NO, Scored/Failed to score ) Villarreal Won Draw Lost (5/15)(7/15)(3/15) Over 2.5 Under 2.5 (8/15)(7/15) BTTS YES BTTS NO (12/15)(3/15) Scored Failed to score (13/15)(2/15) Girona Won Draw Lost (4/15)(7/15)(4/15) Over 2.5 Under 2.5 (6/15)(9/15) BTTS YES BTTS NO (5/15)(10/15) Scored Failed to score (7/15)(8/15) Friday Max betting tips & analysis, Statistic and Best Tips, Best Daily betting tips and analysis for match between Villarreal – Girona Solo Prediction Mathematical football predictions Villarreal – Girona 1×2 Both Teams to Score Under/Over 1 / Over 2.5 31.08.2018 Friday Max betting tips & analysis Our predictions for matches are based on a large number of factors such as direct meetings, last matches, lineup, standings and so on. By visiting our website betpluswin.com you will increase your winning chances. Friday Max betting tips & analysis Solobet Betting analysis & tips today and tomorrow predictions 1×2 Solobet football prediction for tomorrow, victor prediction, accurate football prediction, best football prediction site free, solo prediction, topbet prediction tomorrow predictions, prediction tomorrow, soccer 13 predictions for tomorrow, top bet prediction, topbet predict, all soccer predictions tomorrow, correct score tomorrow tomorrow prediction, top prediction, tomorrow football prediction, victor predict, accurate football predictions for free, best,predicte, betloy prediction football prediction tomorrow, football prediction.com, prediction football tomorrow, predictions for tomorrow soccer matches, sure wins for tomorrow tomorrow matches predictions, tomorrow soccer prediction AC Milan – AS Roma 31.08.2018 |Tip of the Day Over Under, Free Daily betting tips & analysis, H2H Statistic Predictions, Bet and Win Predictions Football, top btts predictions for today | AC Milan is ranked on the 17th place in the standings with 0 points, 2 goals scored and 3 goals received in the last 1 leaguegames. AS Roma is ranked on the 5th place in the standings with 4 points, 4 goals scored and 3 goals received in the last 2 leaguegames. H2H Statistic and Predictions Last 5 matches played for: AC Milan & AS Roma 2018-02-25 Roma Milan 0 : 2 / 2017-10-01 Milan Roma 0 : 2 / 2017-05-07 Milan Roma 1 : 4 / 2016-12-12 Roma Milan 1 : 0 / Last 5 matches played for: AC Milan 2018-08-25 Napoli Milan 3 : 2 L 2018-05-20 Milan Fiorentina 5 : 1 W 2018-05-13 Atalanta Milan 1 : 1 D 2018-05-05 Milan Hellas Verona 4 : 1 W 2018-04-29 Bologna Milan 1 : 2 W Last 5 matches played for: AS Roma 2018-08-27 Roma Atalanta 3 : 3 D 2018-08-19 Torino Roma 0 : 1 W 2018-05-20 Sassuolo Roma 0 : 1 W 2018-05-13 Roma Juventus 0 : 0 D 2018-05-06 Cagliari Roma 0 : 1 W Last 15 Matches (Win, Lose, Draw, Over/Under 2.5, BTTS YES/NO, Scored/Failed to score ) AC Milan Won Draw Lost (5/15)(5/15)(5/15) Over 2.5 Under 2.5 (6/15)(9/15) BTTS YES BTTS NO (8/15)(7/15) Scored Failed to score (10/15)(5/15) AS Roma Won Draw Lost (7/15)(5/15)(3/15) Over 2.5 Under 2.5 (8/15)(7/15) BTTS YES BTTS NO (8/15)(7/15) Scored Failed to score (12/15)(3/15) Friday Max betting tips & analysis, Statistic and Best Tips, Best Daily betting tips and analysis for match between AC Milan – AS Roma Solo Prediction Mathematical football predictions AC Milan – AS Roma 1×2 Both Teams to Score Under/Over 1 Yes Over 2.5

Saturday Free H2H betting tips & analysis

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25.08.2018 Saturday Free H2H betting tips & analysis Our predictions for matches are based on a large number of factors such as direct meetings, last matches, lineup, standings and so on. By visiting our website betpluswin.com you will increase your winning chances. Saturday Free H2H betting tips & analysis Solobet Betting analysis & tips today and tomorrow predictions 1×2 Solobet football prediction for tomorrow, victor prediction, accurate football prediction, best football prediction site free, solo prediction, topbet prediction tomorrow predictions, prediction tomorrow, soccer 13 predictions for tomorrow, top bet prediction, topbet predict, all soccer predictions tomorrow, correct score tomorrow tomorrow prediction, top prediction, tomorrow football prediction, victor predict, accurate football predictions for free, best,predicte, betloy prediction football prediction tomorrow, football prediction.com, prediction football tomorrow, predictions for tomorrow soccer matches, sure wins for tomorrow tomorrow matches predictions, tomorrow soccer prediction Salernitana – Palermo 25.08.2018 |Tip of the Day Over Under, Free Daily betting tips & analysis, H2H Statistic Predictions, Bet and Win Predictions Football, top btts predictions for today | Salernitana is ranked on the 12th place in the standings with 0 points, 0 goals scored and 0 goals received in the last 0 leaguegames. Palermo is ranked on the 14th place in the standings with 0 points, 0 goals scored and 0 goals received in the last 0 leaguegames. H2H Statistic and Predictions Last 5 matches played for: Salernitana & Palermo 2018-05-18 Salernitana Palermo 0 : 2 / 2017-12-28 Palermo Salernitana 3 : 0 / Last 5 matches played for: Salernitana 2018-05-18 Salernitana Palermo 0 : 2 L 2018-05-12 Foggia Salernitana 1 : 0 L 2018-05-05 Salernitana Virtus Entella 1 : 0 W 2018-05-01 Perugia Salernitana 1 : 1 D 2018-04-28 Salernitana Brescia 4 : 2 W Last 5 matches played for: Palermo 2018-05-18 Salernitana Palermo 0 : 2 W 2018-05-12 Palermo Cesena 0 : 0 D 2018-05-05 Ternana Palermo 2 : 3 W 2018-04-30 Palermo Bari 1908 1 : 1 D 2018-04-27 Venezia Palermo 3 : 0 L Last 15 Matches (Win, Lose, Draw, Over/Under 2.5, BTTS YES/NO, Scored/Failed to score ) Salernitana Won Draw Lost (5/15)(6/15)(4/15) Over 2.5 Under 2.5 (5/15)(10/15) BTTS YES BTTS NO (9/15)(6/15) Scored Failed to score (10/15)(5/15) Palermo Won Draw Lost (6/15)(6/15)(3/15) Over 2.5 Under 2.5 (6/15)(9/15) BTTS YES BTTS NO (7/15)(8/15) Scored Failed to score (10/15)(5/15) Saturday Free H2H betting tips & analysis, Statistic and Best Tips, Best Daily betting tips and analysis for match between Salernitana – Palermo Solo Prediction Mathematical football predictions Salernitana – Palermo 1×2 Both Teams to Score Under/Over 2 / Under 2.5 25.08.2018 Saturday Free H2H betting tips & analysis Our predictions for matches are based on a large number of factors such as direct meetings, last matches, lineup, standings and so on. By visiting our website betpluswin.com you will increase your winning chances. Saturday Free H2H betting tips & analysis Solobet Betting analysis & tips today and tomorrow predictions 1×2 Solobet football prediction for tomorrow, victor prediction, accurate football prediction, best football prediction site free, solo prediction, topbet prediction tomorrow predictions, prediction tomorrow, soccer 13 predictions for tomorrow, top bet prediction, topbet predict, all soccer predictions tomorrow, correct score tomorrow tomorrow prediction, top prediction, tomorrow football prediction, victor predict, accurate football predictions for free, best,predicte, betloy prediction football prediction tomorrow, football prediction.com, prediction football tomorrow, predictions for tomorrow soccer matches, sure wins for tomorrow tomorrow matches predictions, tomorrow soccer prediction Carlisle – Crewe 25.08.2018 |Tip of the Day Over Under, Free Daily betting tips & analysis, H2H Statistic Predictions, Bet and Win Predictions Football, top btts predictions for today | Carlisle is ranked on the 6th place in the standings with 7 points, 6 goals scored and 6 goals received in the last 4 leaguegames. Crewe is ranked on the 16th place in the standings with 4 points, 6 goals scored and 7 goals received in the last 4 leaguegames. H2H Statistic and Predictions Last 5 matches played for: Carlisle & Crewe 2018-01-13 Carlisle United Crewe Alexandra 1 : 0 / 2017-09-23 Crewe Alexandra Carlisle United 0 : 5 / 2017-03-25 Carlisle United Crewe Alexandra 0 : 2 / 2016-12-26 Crewe Alexandra Carlisle United 1 : 1 / Last 5 matches played for: Carlisle 2018-08-21 Carlisle United Port Vale 2 : 1 W 2018-08-18 Cheltenham Town Carlisle United 0 : 1 W 2018-08-11 Carlisle United Northampton Town 2 : 2 D 2018-08-04 Exeter City Carlisle United 3 : 1 L 2018-05-05 Carlisle United Newport County 1 : 1 D Last 5 matches played for: Crewe 2018-08-21 Colchester United Crewe Alexandra 6 : 0 L 2018-08-18 Crewe Alexandra Milton Keynes Dons 0 : 0 D 2018-08-11 Newport County Crewe Alexandra 1 : 0 L 2018-08-04 Crewe Alexandra Morecambe 6 : 0 W 2018-05-05 Crewe Alexandra Cheltenham Town 2 : 1 W Last 15 Matches (Win, Lose, Draw, Over/Under 2.5, BTTS YES/NO, Scored/Failed to score ) Carlisle Won Draw Lost (8/15)(4/15)(3/15) Over 2.5 Under 2.5 (8/15)(7/15) BTTS YES BTTS NO (9/15)(6/15) Scored Failed to score (13/15)(2/15) Crewe Won Draw Lost (5/15)(5/15)(5/15) Over 2.5 Under 2.5 (5/15)(10/15) BTTS YES BTTS NO (5/15)(10/15) Scored Failed to score (8/15)(7/15) Saturday Free H2H betting tips & analysis, Statistic and Best Tips, Best Daily betting tips and analysis for match between Carlisle – Crewe Solo Prediction Mathematical football predictions Carlisle – Crewe 1×2 Both Teams to Score Under/Over 1 yes Over 2.5

The principles of Poisson Distribution

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Soccer Betting Resources The easiest and simplest way to calculate the most likely score in soccer is to use the Poisson Distribution and bettors can use this method to make a reliable bet. The calculation of the Attack/Defence strength is in detail explained below and it is used to get the Poisson Distribution values. The concept behind the Poisson Distribution is purely mathematics and it turns the mean averages into a probability. If we use this method to calculate the probability of Manchester City scoring a goal, when their average is 1.7 goals per game, we will get that City will score 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. How to calculate the score-line probabilities using the Poisson Distribution After we are done calculating the “Attack Strength” and “Defence Strength” for each team and after comparing them by calculating the average number of goals that are likely to be scored by each team during that game, we can calculate the score-line that we are most likely to get in a match. In order to calculate the Attack Strength and Defence Strength, a representative data range is crucial. If the data range is too long, then it will be useless because it will not represent the current strength of the team. Too short data range on the other hand will skew the data. Ideally, the Poisson Distribution will make the best use of the data of the 38 games played by each team in the 2015/16 EPL season. Calculating the Attack Strength We need to determine the average number of goals scored per team, per home game and per away game, using the last season’s results, and by this we can start calculating the Attack Strength. Therefore: total number of goals scored last season divided by the number of games played, as shown below: Total goals in a season scored at home divided by the number of games (in one season) Total goals in a season scored away divided by the number of games (in one season) For example, in the English Premier League of 2015/16, there were 567/380 at home and 459/380 away, and this equals to an average of 1.492 goals per game at home and 1.207 goals away. Therefore, “Attack Strength” is the ratio of a team’s average and the league average. Calculating Defence Strength The next value that we need is the average number of goals a team concedes. This value we already have because the number of goals a team scores is actually the number of goals the opposite team concedes. Therefore: Average number of goals conceded at home: 1.207 Average number of goals conceded away: 1.492 The Defence Strength is the ration of a team’s average and the league average. Attack Strength and Defence Strength of Tottenham Hotspur and Everton Case 1: Tottenham’s goals Tottenham’s Attack Strength Number of goals scored at home last season by the home team (Tottenham: 35) divided by the number of home games (35/19): 1.842. 842 divided by the season’s average home goals scored per game 1.492 equals 1.235 and this is the Attack Strength. (35/19) / (567/380) = 1.235 Everton’s Defence Strength Number of goals conceded away by the away team (Everton) last season (25) divided by the number of away games (25/19): 1.315. 315 divided by the season’s average goals conceded by an away team per game (1.315/1.492) equals 0.881 and this is the Defence Strength. (25/19) / (567/380) = 0.881 In order to calculate the likely number of goals Tottenham might score, we can use the formula as follows: 1.235 x 0.881 x 1.492 = 1.623 where: Tottenham’s Attack Strength is multiplied by Everton’s Defence Strength and the average number of home goals in the Premier League. Case 2: Everton’s goals In this case, we will just replace the average number of home goals with the average number of away goals: Everton’s Attack Strength: (24/19) / (459/380) = 1.046 Tottenham’s Defence Strength: (15/19) / (459/380) = 0.653 The likely number of goals Everton might score is done in the following way: Everton’s Attack Strength multiplied by Tottenham’s Defence Strength and the average number of goals in the Premier League: 1.046 x 0.653 x 1.207 = 0.824 Using Poisson Distribution to predict various outcomes A 100 % of probability is distributed across a range of goal outcomes for each side by using this mathematical formula created by the French mathematician Simeon Denis Poisson. Poisson Distribution Formula: P(x; μ) = (e– μ) (μx) / x! There is an easier way to calculate by using a Poisson Distribution Calculator. All we need to do is enter the different event occurrences – in our case goals outcomes from 0-5 – and the expected occurrences which are the likelihood of each team scoring – in our example Tottenham at 1.623 is their average rate of success, and Everton 0.824; the calculator will output the probability of the score for the given outcome. Tottenham vs. Everton – Poisson Distribution   Goals 0 1 2 3 4 5 Tottenham 19.73% 32.02% 25.99% 14.06% 5.07% 1.85% Everton 43.86% 36.14% 14.89% 4.09% 0.84% 0.14% According to this, Tottenham will fail to score with a chance of 19.73, but there is a 32.02% chance they will score a single goal and a 25.99% chance they’ll score two. On the other hand, Everton, has a chance of 43.86% not to score, 36.14% to score one and 14.89% to score two. The probability one team to score five goals is 1.85% for Tottenham or 0.14% for Everton – or 2% for either team to score five goals. In mathematical terms, both scores are independent from each other. We can see that the expected score is 1-0 – pairing the most probable outcomes for each team. If we multiply those two probabilities together, we will get the probability of the 1-0 outcome – (0.3202*0.4386) =0.1404 or 14.04%. The above mentioned … Read more

What are the limitations of a predictive model in Soccer betting?

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Predictive model Soccer betting Predictions based on probabilities contain many restrains and these should always be taken into account when using predictive models to place bets in soccer. Below you may read more on the limitations that models contain. One of the disadvantages of the probabilistic predictions when they are made to guess the outcome of one match is the fact that they one can never know how correct is the prediction. Not even after the result is known. Initially it was planned to apply statistical analysis to baseball and this was written by Nate Silver, which became very popular in 2008 at the presidential election because he correctly forecast the results of 49 out of 50 states. Swings towards one candidate or party are mostly universal and consistent throughout a country; however, this feat was impressive. Therefore, if the trend is correctly identified, constituencies or states can fall as predictably as dominoes. In recognising this, few if any bookmakers would be prepared to accept accumulative bets on a single party to win multiple seats at a general or presidential election. At the World Cup in Brazil, Silver much confident that the hosts Brazil will win the World Cup much more than the betting public. However, they started loosing confidence even more at the start of the competition and this confidence was decreasing even more during the tournament because of certain events like Neymar getting injured and Thiago Silva getting suspended. After Germany won over Brazil with 7-1, Silver’s predictions about Brazil winning the cup were characterised as a disaster. In 2013/14 Premier League when Liverpool nearly won the title in that season, this was considered to be a failure of predictive models. In the middle of February, with the Reds just three-points off top spot, they were still regarded as 17.000 outsiders – a chance of just 5.88% – having begun the campaign at 34.000. They were expected to gain an average of 76 points over the 38 games, but instead finished with 84 and missed the title by two points. One thing to always keep in mind is that all of these prediction models did is giving the probabilities of a win, but they never state precisely that it will happen. According to Silver, Brazil had a 65% chance of arriving to the final. But it also allowed for a 35% probability that Germany would find its way too. 2013/14 Premier League Season: Liverpool Each of the 38 matches gave Liverpool a chance to get 0, 1 or 3 points and the weighted calculations of these expected points from their 38 games gave a sum of 76 points. However, there are always three possible outcomes for the 38 matches and all of them have some likelihood of occurring. Therefore, bettors should always be aware that no single result is a certainty. Range of points won by liverpool in simulations of 2013/2014. Based on quoted match odds for all 38 game. predictive model Soccer betting The graph above suggests that Liverpool would typically gain 76 points in 2013/14. Although this may not be correct, and even with the season completed, the system can only give probabilistic expectations of the assessment of Liverpool’s 2013/14 team. The uncertainty of any predictive process is not only present in the prediction, but also in the data which is used by the bettors to make those predictions. Taking everything into account, bettors should always use the predictive models with care, never rely on them completely and always use them as a balanced betting strategy. predictive model Soccer Betting Resources

Is the first goal in soccer of crucial significance for the final outcome?

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first goal soccer After scoring the first goal at a soccer match, it is easier to predict the final outcome of the match. This is due to the fact that soccer is a game in which not a lot goals a scored per match. Therefore, the first goal should not be considered as invaluable. But, how can bettors use this information to place valuable bets? In order to bet accordingly, bettors are always able to use historic data in order to predict how likely it is for a team to win a match. Naturally, the most important event in soccer is a goal and in live soccer betting, bettors are able to place money on events they already have background knowledge about and the first goal therefore is of utmost importance for this prediction. Understanding the bet odds and knowing how to bet is the primary skill every bettor should posses. Once these skills are acquired, bettors may move towards learning how to bet on Over/Under and use a Handicap soccer betting strategy. Does the first goal as a rule lead to a win? Not all the teams are equal, but if we look at the last seven seasons from the Premier League, we can see that in 69 % of the matches, the team that scored the first goal also won the match. In 19 % the match ended up in a draw and in 12 % of the games, the team managed to win although was not the first one to score. These stats can be seen in the table below: Proportion of Premier League gamew won, drawn or lost when scoring first by strength of team. 2009/10 to 2015/16 first goal soccer The table shows that if a team from the top four gives the first goal soccer, that team will win the matches in 4 out of 5 occasions. On the contrary, a team from the bottom four will have very bad chances of winning. How important is the team ability in regard of chances for a comeback? If we break down the total percentages of wins, draws or losses we can see that they are completely flipped when a team concedes first: Proportion of Premier League gamew won, drawn or lost when conceding first by strength of team. 2009/10 to 2015/16 According to the table, one team which is among the top four teams will lose in only 6.1 % of the games in which they gave the first goal. On the contrary, a team from the bottom four teams will only win in 6.4 % of the matches in which it leads with the opening first goal. Having all this information in mind, bettors may make reliable predictions about the outcomes of the match based on the first opening goal. Various odds and probabilities after the first goal The odds in a life soccer match are variables which are continuously changing throughout the match and due to different situations within the match. The table below shows the odds that were offered immediately after the first goal. Having this into consideration, we will see the difference between what was predicted to happen after the first goal and the actual outcome of the match. The table shows that a team which was in the first four teams had a difference of only 3 %. This means that the odds that were given to it to win, after it scored the first goal, were 72 % possibility of victory. It turned out that it won in 75 % of the matches. As the best and worst teams are always the easiest to predict, the smallest amount of variations is always within them. If we are seeing this from a bettor’s point of view, it is the most advantageous to bet on a team between the 5th and 8th place, and which lost after they scored the first goal. This is so because the odds implied a probability of 5.9 % higher than the amount of times it actually happened. However, this only happened six times last season and thus it is always very difficult to predict when it will happen. Namely, four of the six times were played away and the two home defeats (for Southampton) were against Manchester United and Chelsea and taken altogether, all these results were expected. What more to have in mind? The most important factors to consider, besides the statistics above, before placing a bet in live soccer betting, based on a first goal, are numerous and they include: whether the side which scored the first plays at home or away, when was the goal scored and how far is the season, because the later in the season, the more risks are taken by the trailing teams. However, relying only on the statistics is not the most reliable option for bettors. However, as with everything, there are always exceptions and the exceptions cannot be predicted. The odds for the home team when it first scored a goal, in the matches between Arsenal and Sawnsea and Tottenham and Newcastle, were 90 % chance of winning. However, a turnover happened, and the other side won in both of the cases. All the information listed above are only one way to help you as a bettor place a valuable bet and they should be always compared to the odds that are offered immediately after the first goal has been scored. first goal soccer Soccer Betting Resources

How to make a live soccer betting strategy?

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How to make a live soccer betting strategy? How can bettors know where to look for reliable opportunities which may have big returns within soccer matches in progress? Bettors have to always take advantage of market inefficiencies. This means that they should always calculate when the odds do not reflect the true probability. When it comes to live betting, bettors should try and discover those specific areas and exploit these inefficiencies. The notion very often used by commentators ‘it only takes a second to score a goal’ is pretty accurate. Because of the great number of potential goals during a soccer match, the life of a live soccer bettor is quite interesting. Quite the opposite, the number of scored goals from these opportunities is relatively small. According to statistics, goals never come in series and this makes them random also. Therefore, we can never expect one goal to be the trigger for a next one. The job that live bettors need to do is to predict something which is both rare and even more random. Complex statistical models are used by professional bettors and bookmakers. These try to predict goal distribution. However, as football is played by living beings, and not robots, and humans as they are, show various tendencies. The bettor must be able to understand and quantify the impact of those and to recognise when the outcomes that are estimated are not in line with their impact. The data for the Premier League season of 2011/12, over six intervals of 15 minutes, will be analyzed in terms of goal distribution. How to make a live soccer betting strategy? When scoring of goals is more likely to occur? According to Graph 1, goals are more likely to occur as the match progresses and in the period that leas to half time, there is a slight increase. In the final, sixth, interval, the chances of scoring a goal are the highest and almost double that of the first interval. Graph 2 below contains the same data for Reading (up to February 11th 2013).   In the final 15 minutes of the match, the rate of scoring increased three times compared to the first 15 minutes and over four times compared to the period between 46-60 minutes. This data show that Reading plays in a slightly different mode than an average teams and therefore it is of great significance to know this information. The information above may affect the live bettor in two completely opposite ways. On the one hand, if a bettor watched Reading play all the time, he may be forced to over-estimate the number of times a team scores near the end of the match. If a bettor has not watched Reading play at all, they may make wrong estimation of how Reading will perform near the end of the game, if they want to place a bet on Reading. Later in the season Reading may start regressing to the mean values of the other teams, but there is still an opportunity to exploit and see what is nehind it, whether it is only a minor deviation from the average or something more significant. Intensity of the game Bettors can access a lot of available data while the game is on, such as 5 possession, shots (on and off target) and corners, which may held define the game intensity. Therefore, they are able to make good assessment of who is leading. However, as they are freely available to everyone, these data should always be used in combination with subjective analysis. A professional bettors should be able to sense where certain odds are over-valuing one team which is playing at an unsustainable pace. Case 1 In the Copa del Rey semi-final between Real Madrid and Barcelona on January 30th at the Bernabeu, in the El Clasico meeting of 2013, Real was superior over Barca in the first half. However, the pace that Real adopted was simply unsustainable. It would have been a huge mistake to bet on Real and to predict the final outcome in the first 45 minutes of the match. Case 2 Champions League 2012 final between Bayern Munich and Chelsea is another example. It also gave misleading stats based purely on possession and interaction. Bayern were superior on one hand, but the other important element was Chelsea’s tactical intention to call for pressure and try to land a lucky counter-punch. They made a game plan, followed it, and won on penalties. If bettors were only following the statistics of the game would have never placed a bet on Chelsea to win the trophy. As seen from everything above, what bettors should always keep in mind is that the intensity of a game is something that is never a constant. The balance of possession can be altered by things like crowd intensity, adrenalin and situational factors, such as: ⦁ Derby games ⦁ Cup games ⦁ Relegation/Promotion battles ⦁ Tournaments Under the above mentioned circumstances, the best thing a bettor could do is to see the game as two separate halves. Even the relatively simple concepts for live soccer betting should encourage bettors to upgrade their knowledge further in order to become more informed in the future. making a live soccer betting strategy

Do bookings have effect on live soccer betting?

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Soccer Betting Resources One of the most significant events at a soccer match is the red card. The article below shows the importance of both red and yellow card (bookings), how the game is affected by them, what are the adjustments the managers do and how are teams put in disadvantageous positions because of bookings. How does a red card change the game? The immediate effect of a red card is undoubtedly the loss of a player. But, statistics show how this affects negatively and to which extend a team is affected when one player receives a red card. In a sample of 60 Premier League games in 2012, where a team received a red card, in 20 % of the games teams had a decrease in points compared to their predicted points which were based on the score before the player was given a red card. In a sample of 20 teams in the Premier League, which were in a draw at the time of receiving the red card, 65 % lost the game in the end, 30 % ended up in a draw and only 5 % of them managed to win. In a study by Titman et al. (2012) treats the matter of what are the benefits that teams that play against a team which has received a red card. The findings from the study are that the rate of goals scored by the team without a red card earned increases for 64.5 %. Other studies treating this matter in the Premier League seasons show that if a team loses a player in the first minute, due to a red card, their average goal difference in the game would be reduced by about 1.5 goals. This decreases to 0.85 if a red card is given to a player at half time and to 0.62 at 60 minutes. This means that the longer a team is without a player, the worse off they will be. Taking the above into consideration, a bettor is able to measure if live odds have been adjusted to reflect the red card events and also to measure the effects of yellow card, which the most common indicators to red cards. What is the significance of the yellow card? The bettors should acknowledge the importance of the yellow card because a yellow card is one step to a red one. Therefore, the probability that a player will get a red card grows as more and more yellow cards are given in the course of a game and according to Titman et al. (2012), a yellow card to any of the player on a team in the Premier League more than doubles the hazard of a straight red card to any other player on that team. Another curious fact, according to Titman, is that a team’s booking rate increases by 25 % if the opposing team receives a yellow card and this reinforces the notion that referees have a tendency to ‘even up’ decisions during the game. How do managers change tactics after cards? The situation when a team loses a player due to a red card requires reaction by the manager to change his tactics. In this way, the bettors should be able to think like the manager and correctly weigh the situation to determine how important is the player that was sent off to the team, how the card affects the shape of the team, what can be done to smooth the situation and how the red card will affect the rival. If we analyze the last 16 Champions League second-leg game between Manchester United and Real Madrid in 2013, we can see how a red card makes impact on the game. United were controlling the game and nullified Madrid’s potent attack by using Danny Welbeck to restrict Madrid’s most creative player Xabi Alonso, after the score of an own goal made by Sergio Ramos. This put Manchester United in a leading position with 2-1. However, in the 56th minute, the winger Nani was sent off and besides having one man less, United also had to move Welbeck to left midfield so that they are able to preserve their second bank of four – and this allowed Alonso to roam free and become more creative. In just four minutes, Madrid’s manager Jose Mourinho made a substitution where he replaced Arbeola with Luka Modric and swapping Sami Khedira to right back. All of these events changed the game and with Modric controlling the centre of midfield with passing sequences and delivered the equaliser, collecting a pass some 20 metres from goal. After the equalisation, Real retained the ball and scored their second goal within 13 minutes of Nani’s red card. Does being away place teams at a disadvantage? As we have already written about the Home Field Advantage, home teams are always in a slight advantage than the away teams. But, is it possible that they also get help by the referees? Statistics from the Champions League, from 2002-2007, show that in only 24.3 % of games, the home team received more yellow cards than the away team. This suggests that perhaps the probabilities of yellow and red cards are different for home and away teams. In that period between 2002-2007, home teams received red cards in 6.42 % of games, whereas the away teams received them in 11.82 % of games. Therefore, in percentages, away teams earned red cards 84 % more often than home teams. On the other hand, in 82.89 % of the games, there no red cards. According to Anders & Rotthoff from 2004 to 2009, the effect of cards on the home team is different to that of the away team. Titman et al. (2012) found that a home red card increases an away teams’ scoring rate by 60 % and decreases the home sides’ scoring rate by 17 %. Increase by 69 % in scoring is evident for the home team after a red card for the … Read more

How important are corner kicks in soccer live betting?

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Soccer Betting Resources Live soccer bettors should know that corners kicks are not worthless in live soccer betting so that they are able to place a good bet.   World Cup 2014 Corners There were 474 corner situations in the initial group stage, out of which 19 were turned into goals. This was slightly higher conversion rate of 4 %. But, this conversion rate has an extremely big effect on the qualification for the knockout stages. In the group games, 14 teams scored at least one from a corner and 11 of those went into the Round of 16. In Group A, all four sides scored at least once from a corner, so two teams were bound not to advance and the overall progression rate for corner scoring teams was even more impressive. In figures, nearly a quarter of the total goals scored by these 14 sides were from corners. In order to be able to calculate the possibilities, we should focus on how likely is a side to convert a corner into a goal, when given an average number of corners. If we use the more common 3 % conversion rates from corners and applying them to the group format of Brazil 2014, there was around a 7 % chance that a side would convert exactly two goals from corner kicks in their three group stage matches. Thus, individually, one side may score at least one goal from a corner n around 15 % of their games and in one match there will be at least one such goal scored by either side 25 % of the time. The likelihood above are not to be disregarded, especially is the goals that one side may concede from a corner are taken into account. This is a better way to calculate than to concentrate only on goals that may be scored in this way, which is mostly used in such studies. In the group stages of the World Cup Finals which consist of 32 teams and in the USA, Mexico and Colombia, we should have expected between two or three teams to have scored exactly two goals from corners. Playing against Italy, Uruguay managed to turn the situation in its favour when they scored from a corner. Therefore, from a 15 % chance of qualifying for the Round of 16, in the last 10 minutes in the group stage, they managed to increase this chance to 90 %. Brazil needed a similar goal to win over first Chile in the initial knockout game and then Colombia in the quarter final. Surprise qualifiers, Mexico and USA also owed their progression partly to finely executed goals from a corner kick. Should corners be considered worthless? As the situation in soccer is, goals are scarce and when it comes to goals scored from corners, no matter how surprising they may be, they have a great effect. But, how to define their effectiveness? This has always been considered as a matter where subjective opinion prevails. Diego Godin’s emphatic first contact header for Uruguay against Italy was the definitive example of a goal scored from a corner delivery. But less clear cut was Liverpool’s equally dramatic last minute winner at Blackburn in 2012. Agger flicked on a 40 yard punt from halfway and Carroll headed home a last minute winner, so the goal originated from a pass 50 yards from goal, but the defensive confusion in Blackburn’s defence and Liverpool’s temporary attacking set up comprising their two central defenders owed everything to the corner kick that had immediately preceded the goal. Whether the goal originated from a corner kick or not should be looked into carefully and a cut-off point may be required. However, to define that a corner is the initial point and three subsequent passes is merely a convenience for the data collector. It is not something that is firmly based in reality. A corner kick disrupts the whole order of the game. Namely, the defence has to be reordered and players who normally play attack, now have to play the defence. Furthermore, players with aerial talents have to be included and these players may be more usable on the ground in other phases of the match. Barcelona and Spain have recently used mixed strategies to one dimensional approach. Therefore, corner kicks and the threat they pose mean more than just the action that they create in the goalmouth. How much a corner is worth? There is nothing that we can use in order to compare goals from corners to other forms of scoring. Corners have a low conversion rate of 3-4 % and therefore they are dismissed very often. If they, together with their subsequent passes are considered as another passing sequence, then they take up 5 % of such on-field actions. But in any case, they account for 15 % of the goals that are scored in one season. If we use data from the EPL, 50 final third entries are necessary to score a goal which is not a goal scored from a corner. Therefore, these goals that are scored in final third entries may be suitable comparison to corners. However, even if we manage to compare goals scored from corners to other methods of scoring, we will see that the efficiency at which corner kicks are converted to goals is again extremely low. On the other hand, we should never disregard corners just because their conversion rate is very small. If we look at this from another perspective, we will also see that other on-field actions almost always fail to end in a goal. If we compare corner kicks to penalty kicks, we can conclude that the conversion rate of penalty kicks is about 80 %, compared to 4 % of corner kicks. But, the penalty kicks is an event which is very rare in football, whereas corner kicks happen very often. In order one corner to be successful, two players have to connect in a well practiced routine. … Read more

How to calculate the home field advantage a team has in soccer?

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The article below explains the home field advantage (HFA) a team has and how to calculate it for greater benefit and even better than the bookmakers. Since 1888, every football season has shown the evident fact that teams perform better when they play at home, than on a neutral pitch or away. Throughout one season, home teams have scored more goals than away teams. However, soccer teams are highly unbalanced and not all of them have manage to earn the same home-field advantages than other and therefore it is very difficult to come up with one general home-field-advantage handicap. What bettors should always take into account is to know which data is relevant. Namely, would it be relevant to take Chelsea’s and Manchester City’s home field advantage which has increased significantly after their purchase by rich owners? Does Arsenal’s form of pre-2005 be taken into account even if it plays at another stadium? Calculating home field advantage Home field advantage may be calculated by the following equation: HFA = (HF – HA) / 19 where: HF is the number of goals scored at home per season HA is the number of goals conceded at home In the end (19) divide by the number of home games played in a season. How to use home field advantage with Asian Handicaps? When the home handicap is less than the home field advantage for one team, it might make a sensible bet. However, this is just one factor to consider when making a balanced betting strategy. What influences on home field advantage? Certain factors influence on the home field advantage and they are as follows: –       Home crowds –       Stadium Familiarity –       Style of Soccer –       The Referee Home crowds influence the home field advantage a lot. For example, before 2013/13 season, Liverpool majorly underperformed for a club of their size. They finished at the 7th, 6th, 8th and 7th place. The Reds had a better HFA than Tottenham in all but one season despite finishing below them in the league. Does this imply that how Liverpool performs at home is affected by home field advantages more than others? Before Arsenal moved to the Emirates Stadium for the 2006 season, they had great success in 1997/98 when they won five Premier League seasons, before the end of 2005. In the course of this period, their average home field advantage was 1.51. But, after moving to the Emirates Stadium, their average home field advantage dropped to 1.23. However, gradually over time, they showed signs of progress which only signifies that they were getting accustomed to the new pitch and started feeling at home at the Emirates Stadium. Another important factor is the style of soccer one team adopts. In 2013/14 Liverpool’s HFA increased from 0.89 in 2012/13 to 1.84. In this period they had the same manager and relatively similar team. However, manager Brendan Rodgers adopted a more attacking strategy and this increased the goalscorring opportunities. This resulted in almost a goal per game increase in HFA. The last, but the most influencing factor for the HFA in soccer, according to Scorecasting written by Moskowitz and Wertheim, is the referee. Their findings show that home teams always receive small preferential treatment by the referees. Although this preferential treatment is given unconsciously, the referees are always emotionally affected by the home crowd and sometimes make subconscious decisions in favour of the home team. Moreover, according to the Harvard Research Assistant, Ryan Boyko, after studying 5,000 Premier League games from 1992 to 2006, concluded that for every 10,000 home team fans, home team advantage increased by 0.1 goals.   His study further showed that referees, especially inexperienced ones, often give penalties to home team players. Therefore, it is very important to include the referee profiling in the overall soccer betting strategy. 

What to make of possessions in soccer and what statistics say about them?

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Live match analysis lately regularly quote possessions statistics and the general assumption is that more possessions is a positive thing. This article treats the matter of possessions, is there any truth in the assumption that the more possessions, the better and to what extent should bettors use possession statistics when making predictions of the teams ability to win a game. The manager of at the time, Brendan Rogers, often repeated the following: if you can dominate the game with the ball, you have a 79 % chance of winning. This is taken as a support of the possession based football.   But, if we look at the recent competitions from a statistical view point, we can see that the numbers we get for the short passing, possession oriented approach are mixed and not always in its favour. In 2014 World Cup, Spain bowed out oat the group stage although they had over 60 % of the possession in defeats, first to Netherlands and then to Chile. At the Euro 2012, they succeeded due to their semi-final penalty shootout against Portugal, where Portugal only had a minority share of possession throughout the tournament. In 2008/09 and 2010/11 Barcelona managed to be first in Europe with tournament possession figures in the mid to high 60% and pass numbers averaging around 700 per game. But sandwiched in between were wins for Inter Milan, 45% overall possession in the competition, barely a third in the final and just 400 passes per game in 2009/10, followed by Chelsea’s 47% overall possession in 2011/12. In situations involving head-to-head meetings, more often the side that avoids possession is the winner. For example, Chelsea’s aggregate win over Barcelona in 2011/12, where Chelsea gained just 20 % of the ball and in the case of Real Madrid’s 5-0 aggregate trouncing of Bayern Munchen at the UCL semi-final stage in 2014, where they had less than 30 % overall possession. All of the above seems to be very contradictive to the assumptions made by Rogers that the most chances of winning a side has is if they keep the ball for longer than the opponent team. When possession stats are combined with other key stats Possession is a useful indicator if used in combination with other more fundamental primary stats because raw possession is a secondary statistic and is only a constituent of the primary ones. If they are good at tackles or interceptions, teams get possession and the only way to keep it is if they pass well. Furthermore, possession is then used to create good chances and when these chances are well converted, a goal is scored. If more goals are scored in this way than the other side, then a game is won. Therefore, as we can see from this interdependence of events, possession is a strong indicator only if the side knows how to make the best use of it and how to create the best passes and chances to score a goal. But, on its own, a possession is not a good indicator of how strong one side is. What are the shortcomings of Possession? The tiki taka style of play is characterized by short passing and movement of the ball quickly from one player to the next, short passes and maintaining possession of the ball for the most of the game. So, while Barcelona was playing in a tiki taka style to create chances for its players, Swansea did have a moderate amount of possession. They stayed firmly in their own half of the pitch, doing backward passes in a defensive tactic to prevent the opponent from scoring. That same season 2011/12 in which Swansea created 472 chances with the third best possession stats in EPL, Barcelona created 626 chances while being at the top of La Liga’s possession charts. The four sides surrounding Swansea in the EPL possession chart had similar level of ball retention and created an average of 681 chances throughout the season, which is almost 50 % higher. Swansea finished a worthy 11th. Swansea was a recently promoted team and thus they decided to more use possession to defend themselves, rather than to attack. They did this in order to protect a game start point and this was in the same fashion as when more successful teams use possession to protect their lead. How Mourinho approaches Possession? When faced with more superior teams, teams managed by Jose Mourinho have always chosen to adopt defensive solidity by sacrificing the ball, in roder to score from counter attacks or set plays. Mourinho believes that the team who possesses the ball is often more likely to make mistakes and sometimes, a game can be won by an opponent’s mistake. But, at the same time, he is trying to keep the game in a stalemate. Chelsea under Mourinho in 2014 used this tactic of possession, at Anfield, where they had just 27 % of possession, but anyway won over Liverpool with 2-0. The goals were scored following Gerard mistake and a swift counter attack. The likely possession stats for the game between Liverpool and Chelsea were determined even before the game and therefore, the bettors should have already anticipated them. Pragmatism according to Pulis Sometimes, the best chance for one side to get a good result is to play ‘without’ the ball. This is often negatively perceived by the public, but it is a good way for the team to reach what they aim for. An extremely defensive play at home and away, together with long balls into the half of the opponents and followed by brief pressing attacks, was a pragmatic approach by Stoke City under Tony Pulis. Stoke City were technically inferior against many of their Premier League opponents. In all of their 56 victories under Pulis, they had less than 50 % of the possession. As said before, possession on its own has a very low impact on the overall game. However, possession combined with other primary events that happened … Read more

The new betting scheme in soccer: betting on cards

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Lately bettors have found a new way to place money in soccer betting and this new way is betting on cards. It is a drift from the classical 1X2, Handicap or Total betting. Below, you may find out how to bet on cards and which data can you use to place better and reliable bets. It is always useful and handy to find a relatively unknown sport, develop a good knowledge and reap the benefits from betting in it. Or, just discover a specialist market in more popular sports. When finding a specialist market is in question, then corners betting in soccer can be taken into account. What successful bettors do is getting information less known to other bettors and make use of them for their own benefit. This is especially true when talking about the bookmakers odd. When a bettor knows something a bookmaker doesn’t, then the bettor is able to take advantage of that knowledge. However, even without that extra info, one can find something valuable to bet in, like cards betting. What is the benefit of cards betting? When we talk about learning the information that bookmakers don’t know about, it is worth noting that we don’t imply that bookmakers are uninformed about certain stuff happening in the betting world. However, all the energy and resources are put in the more popular markets mentioned above, like 1X2, Handicap or Total, so that bookmakers don’t have enough time to spend on the cards betting market. And this is the opportunity to be taken as an advantage by bettors who want to explore new betting markets. Also, the more reliable method for betting on cards is the analytical approach, compared to the other markets, due to the fact that soccer sees less scoring. How to bet on cards? There are various markets for betting on cards in soccer. Just as in the other  markets, here the Handicap and Total cards markets are offered for the Champions League, Premier League, La Liga, Bundesliga and Serie A and all of them use a points system. A booking (yellow card) is worth 1 point and a red card is worth 2 points because two yellow cards result in a red, this is worth 3 points (one for the yellow card and 2 for the red after a second yellow was shown). In Totals cards betting, he bookmaker sets a figure for the combined cards points and then the bettor is able to choose to place the bet on the actual figure which is over or under the bookmaker’s figure. If Tottenham Hotspur was playing against Crystal Palace, the total might be 4.5. Here we have two bookings for Tottenham (2 points) and three bookings for Crystal Palace (3 points) and this will be an over bet on the Totals would win – anything less and the bet would be a loss. The Handicap card betting is the same as in the other handicap markets. Here one side is offered a + and the other side a – to counter a perceived bias. An example for this would be Tottenham Hotspur -1 and Crystal Palace +1. According to this, Tottenham would have to accumulate 2 more cards points than Crystal palace for the Handicap bet to be successful. Therefore, if Palace accumulated the same cards points or even more, the bet put on them would win. If Tottenham scored one more point than palace, the result would be a push). Analysis of cards betting Bettors must consider various of factors before placing a bet on cards. Taking into account the data from the Premier league from the season 2013/14 until now, we can see that some of the most useful statistics are the tackles per game (TPG), fouls per game (FPG) and the average number of cards per game (CPG). Below we can see these statistics for each team in the Premier League 2013/14. Keep in mind that these table do not show the accumulation of these fouls and cards (for example, if a team is an underdog, if they are the favourite, if they are losing or winning). Teams Average TPG Average FPG Average CPG Arsenal  18.8 9.6 1.5 Bouremouth  16.9 9.8 1.4 Burnley 15.9 10.9 1.8 Chelsea 19.3 10.6 1.8 Crystal Palace 19.7 12.5 1.8 Everton  18.9 10.1 1.6 Hull City 18.7 11.1 1.7 Leicester City 19.9 11.6 1.5 Liverpool 21.4 10.7 1.6 Manchester City 18.9 12.1 1.9 Manchester United 18.9 12.1 1.9 Middlesbrough 20.4 12.2 2.0 Southampton  20.2 11.7 1.6 From the data we can see that Manchester United and Tottenham Hotspur have an above average number of FPG and receive an above average number of CPG. It is worth noting that these teams are possession-centric. On the other hand, teams like WBA and West Ham make fewer TPG, make less FPG and get less CPG. These teams are more defensive. There are however some teams which make their opponents commit more FPG and therefore receive more CPG. The table below gives evidence of this, using the same sample of data as above: Teams OFPG Average OCPG Arsenal  11.3 2.0 Bouremouth 12.2 1.9 Burnley 11.1 1.8 Chelsea 12.5 2.4 Crystal Palace 11.6 1.7 Everton 11.8 1.7 Hull City 11.1 1.6 Leicester City 9.4 1.6 Liverpool 11.3 1.9 Manchester City 10.1 1.8 Manchester United  11.1 1.8 Middlesbrough 10.8 1.7 Southampton  10.7 1.4   In these cases, underdogs usually have to chase the ball and make more TPG and FPG and the side that is losing will be forced to do the same the later it gets into a game. Most of the cards are usually given for fouls and bettors should always keep this in mind. Other times when fouls are given is for simulation, taking of jersey during celebration and getting onto the pitch without permission. And all of these situations account for less than 1 percent of cards. The role of the referee Although all the referees follow the same rules for giving cards, some referees give more … Read more

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