arbitrage betting.<\/strong><\/a><\/p>\n <\/div>\n <\/div>\n <\/li>\n <\/ul>\n <\/div>\n<\/div>\n\n\n The Home or Away record of a team has a considerable indicating value<\/strong> of whether 2.5 goals (so at least 3) or under 2.5 goals (so no more than 2) will be scored. Many teams play better in front of their own crowd and gain more points than in away matches. The numbers from the 2018\/19 Premier League season (when fans were present for all matches<\/strong>) prove this: Home teams score 1.57 goals on average, while Away teams only reach 1.25 goals on average.<\/p>\n\n\n The below example from the Premier League 2018-19<\/strong> season shows that these factors have a larger predictive value than the number of goals scored on average in the whole season (so Home and Away matches combined).<\/p>\n\n\n
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Example<\/p>\n <\/div>\n
\n Chelsea managed to score an average of 2.05 goals when playing in front of their home crowd at Stamford Bridge. Despite fielding a 4-3-3 in nearly each match, the choice of players and different match preparation for away games meant that they scored less goals on the run. In fact, Chelsea only managed an average of 1.26 goals scored when playing away. This difference in goal scoring frequency<\/strong> would not have been apparent if one was simply looking at the general average of goals scored per game by the Blues (1.66).On the flip side, Crystal Palace, under Roy Hodgson\u2019s lead, were approaching home matches with a more defensive-minded style of play<\/strong>, trying to concede as little space as possible to opponents and hitting hard on the counter attack. When playing away they were playing with a more adventurous style of play, open to scoring more goals however also open to conceding more goals too. In fact, the average of goals scored while playing home was 1.00 while the average of goals scored away was 1.68. When speaking about goals conceded, they succeeded in conceding less at home<\/strong> on average (1.21) than they conceded away (1.58).<\/p><\/div>\n <\/div>\n <\/div>\n\n\n\n Take Direct Encounters Into Account & What Not To Do\n <\/h3>\n \n\n
\n The results of direct encounters also let you assess whether you should bet on Over or Under 2.5 goals. It may quite possibly happen that teams play offensively and score many goals for the whole season, but in a direct encounter, almost no goals are being scored. This may be the result of the tactical line-up or the situation in the league<\/strong>. The opposite is also possible, with teams playing defensively without scoring any goals; a direct encounter might actually make for a goal fest.<\/p>\n\n\n Do not analyse matches that are too outdated\n <\/h4>\n \n\n
\n When analysing direct encounters, you should not go too far back in history. Encounters from the last 3 years are especially significant. If you go too far back, completely different teams, managers and thus, other tactical orientations would have dominated the match, thus affecting the result of your analysis.<\/p>\n\n
\n Do not analyse too few matches\n <\/h4>\n \n\n
\n Don\u2019t just take one or two encounters between the two teams into account – analyse at least 3 games. There are always clashes that are out of the ordinary and that represent outliers in the statistics. To avoid this, and to be able to make a better forecast, it is important to evaluate a good number of matches.<\/p>\n\n
\n Assess Frequency Instead of Averages\n <\/h3>\n \n\n
\n Goals scored by a team may be a useful value when you assess whether to bet on Over or Under 2.5 goals or not. At the same time, they may be a bit of an annoyance. If you only consider the average figure of goals scored in a match, outliers in your statistics<\/strong> might lead you to false conclusions.<\/strong> An example from the Bundesliga season of 2014\/15 serves to underline this important point:<\/p>\n\n\n
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Example<\/strong><\/p>\n <\/div>\n \n After 12 matchdays, games played by VfB Stuttgart, which amounted to an average of 3.33 goals per match, seemed to offer safe bets for over 2.5 goals to be scored. However, after analysing each match, it soon becomes clear that this statistic is misleading. Among these 12 matches, there were 7 matches with less than 2.5 goals (and only 5 with more than 2.5 goals). In the 5 games with more than 2.5 goals, the teams scored 8, 6, 5, 4 and 5 goals. So, although the average number of goals does appear to be high, you are actually more likely to lose an Over 2.5 Goals bet than win it.<\/p><\/div>\n <\/div>\n <\/div>\n\n\n
\n An example of Mainz 05 from the 2014\/15 season emphasises this further:<\/p>\n\n
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Example<\/strong><\/p>\n <\/div>\n \n Within the first 12 matches of the season, matches played by Mainz 05 displayed a goal average of 2.42 goals scored per match. At a surface glance, this seems to suggest that you should place an Under 2.5 Goals bet and expect to win it. However, if you take a closer look at each of Mainz\u2019s matches, you will find that less than 2.5 goals were scored only in 5 of their matches. In 7 matches, they actually struck more than 2.5 goals. Here, just as before, simply reviewing the individual matches can explain the supposed contradiction: among the matches with under 2.5 goals, 3 were draws without any goals scored. And, among the matches with more than 2.5 goals, there was no match where more than 4 goals were scored.<\/p><\/div>\n <\/div>\n <\/div>\n\n\n
\n Conclusion: When carrying out an Over\/Under goal analysis before placing your bet, you should refrain from mean values<\/strong> and instead include frequency in your calculations.<\/strong> Always ask yourself: in how many matches played by team X were more than (and less than) 2.5 goals scored?<\/p>\n\n\n Include More Than Just Goals in Your Statistics\n <\/h3>\n \n\n
\n Scored goals may carry significance for future results; however, you should work with more indicators<\/strong> for Over \/ Under bets to define the exact potential of a team<\/strong>. Keep in mind any shots on goal and opportunities allowed. Check the shot conversion rate: how many goalscoring opportunities does a team need to score a goal? How many goalscoring opportunities does the opponent need on average to score a goal against said team?<\/p>\n\n\n Goals might be the obvious indicator for an Over \/ Under bet. Statistically, however, goals are often volatile, and therefore do not serve as a strong enough indicator to make safe predictions for your bets.<\/p>\n\n