** Best tips and tips from hundreds every week: **

Many soccer (football with our American friends) choose and tips pages provide just a few clues / tips a week, some only one, with many paying big amounts for privilege. In this article, I will show you how to get the most out of hundreds of free and low cost and tips each week by answering these four questions.

What if you could choose absolute best choice from hundreds of weeks of choice / tips that increase your likelihood of success?

What happens if you choose to choose or tips are based on previous successes of similar popularity and recommendations and then select / tips are created using a combination of tested and tested statistical methods?

What if you could know if the forecasts, world forecasts or forecasts in advance are better in the Premier League, Italian Serie A, German Bundesliga or many other countries in Europe?

What if you could do it all for free or very low cost?

Well now you can. If you are interested please read.

** Some tips are better than others: **

Use well-known statistical methods as well as automated software that can create hundreds of football tips each week for multiple races, theoretically you can review all of the world's leading races. So what, why would you like to do that? Certainly, many of the suggestions will be roughly inaccurate, but many will be correct so how can you decide who will succeed and who not? It would be much better to concentrate only on one or two games and predict their outcome with a very accurate analysis.

Given that the above-mentioned answers I've seen over the years have some merit and comprehensively discussed, there is a good reason for the analysis of one match with the aim of trying to predict his departure. However, consider this when a scientist performs statistical analysis, how many data sources do they choose as a typical sample? One, two … or more? When statistical analysis is performed, the more data you need to work on the better the output. For example, if you wanted to calculate the average height of the elementary school of children, you could just take the first two or three as a sample. But if they are all six feet tall then they are becoming very unpretentious so obviously you would get all their heights and calculate the average from them, the result is a much more accurate answer. It's a simple example, but hopefully you see my point. Obviously, you can apply this argument to one match by comparing the last results for each side and performing statistical analytics using this data, but why does the analysis limit only one match?

We know that if we do hundreds of automated tips based on audited and tested statistical methods, some will succeed and others will not. So how do we aim for the best advice, who is most likely to be right and how do we do it week after week? Well, the answer is to keep a record of how every single tip works, some tips are better than others and we want to know who. At this point, if you think how can I figure out all this information for each game, in all the departments I want to accomplish, and do it every week, do not worry I'll show you how it's "# 39

** The results are not always the same: **

Simply keeping a record of how every hundred of the tips we actually made against the final result is not enough, what We now need a way to analyze that data and classify it logically to get the best results. The results are not always the same, in other words indicating that you can go to game A and the same possible passing in game B will not necessarily produce the same result (ie, correct prediction or false prediction.) Why is this? Well there are hundreds of reasons why you will never be able to calculate all of you, if you could be a millionaire. When you try to predict the outcome of games, you can review such qualitative items as the current injury list of each team, team team, player players, etc. We can also look at the magnitudes using statistical methods to predict the outcome of the game, so we can look at such things as previous performance, position in the league or more actually and tested statistical methods, such as the ratio form method. We can use all this information to predict the outcome of game A and the outcome of game B and not yet the same conclusion, partly because of this, as explained before, we can not explain all aspects of the game, it is impossible. But there is something else, something we can explain that we have not yet thought of.

Looking at one game in isolation, we only look at the factors that relate to each of the two teams in the game, but why not increase this to look at how other teams they have played are also performing? & # 39; Why do we want to do that? & # 39; I hear some of you say. Because the results are not always the same. Let's say our prediction for match A and match B is homework (forget about the suggested points at the moment). What can we take into account to improve your homework? We can look at the performance of all home-based tips that were made for the same game played and then judge based on new information. This is great as it gives us an additional benchmark to take into account that we were not before.

Looking over all the homework is predicting one league to give us a percentage of home-based work for this particular department, but we can further improve it. We can do this by doing the same exercise across many different departments and gaining a percentage of success in each league. This means we can now search for the league that produces the best overall world forecast predicting success rate and looking for a home working predictor for the upcoming fixtures. By default, we know that this division is more likely to be successful at the end of prophecy than anyone else. Of course, we can use this technology to work away and draw predictions too.

** How much is the league ?: **

Why is this difference between the wards? As we try to predict the outcome of one game there are many factors that make this phenomenon, but there are only a few key factors that affect why one department should produce more homes working with periods than the other. The most obvious of these could be described as density & # 39; in the league. What do I mean with density? In any league, the skills and abilities of these teams are constantly in the top of the league and at the bottom of the league it is often expressed as a difference in class. "This difference in class varies between different departments, as some divisions are much more competitive than others because more advanced skills are through the ward, "stuck ward." In the case of a permanent ward, examples of drawn games are more pronounced than with "not so dense league games & # 39; and home work will probably be lower frequency.

So, we say we're interested in predicting homework, armed with new information about our density & # 39; of the departments we could make predictions for games over the season for as many races as we can manage and look at how this forecast is in each league. You will find that the performance forecasts will almost match the density & # 39; of a particular league, so where a particular league game produces more homes, we will achieve more results with our world-wide forecast. Do not be wrong, this does not mean that just because it's more home we work to be more accurate, what I'm talking about is success in proportion to the number of world prophecies that has nothing to do with how many real homes work there. For example, we say that we make one hundred world forecasts in Division A and one hundred in Division B and say 70% are right in Division A but only sixty percent in Division B. have made the same number of predictions in each league with different results and This difference is most likely due to the weight & # 39; of each league. Division B will be "dense" with more teams with similar grades in the "class", but Division A has a higher grade in the team when it comes to the teams. Before we get the best results in the league at home and make our home selection from this league.

** We must be consistent: **

Of course, more than that. It's not good to just take each tip and pick up how it happens. We have to apply same rules for each tip made. You must make sure that the parameters you set for each prediction method you use (eg, ratio, incremental, etc.) is stable. Then, choose your best settings for each method and hold them. for every prediction, for the whole league and for the entire season. You must do this to maintain consistent predictions within the radar, between races and over time. are stopping you by using a few different sets of parameters as long as you keep the data produced from each one.

If you are wondering what the variables are then take the ratio as an example. Using this method, we produce an integer that represents the possible passing of a game (I will not go into details about the percentage rate here as it is the subject of my other articles). You can set break points that represent home work and off work, so if the output match rate is higher than the upper fraction, then this match may be considered as homework. Similarly, if the criterion target for game is lower than the lower fraction, then this match may be considered to be away. Anything that falls apart is thought to be a tie.

Footyforecast.com (now 1X2Monster.com) has delivered these types of information week to week on its website since 1999. It includes eighteen presentations in Europe including; English Premier League, Scottish Premier League, Italian Serie A, German Bundesliga, Dutch Eredivisie, Spain, France, to name a few. In total, seven different statistical methods are used to determine the outcome of each game played in each league and a comprehensive list of how each method is in each game. Regardless of how each tip within the relevant department Footyforecast also provides the league tables on how each league game has played successfully to see the success of games. The league charts predictive performance is produced for home predictions, draw predictions, away work predictions and for general predictions and are invaluable tools for football points when deciding where to target their European forecast.

So you have it. Hopefully, I've shown you how to target the best departments to increase your chances of success when looking for 1X2 results, and although I do not provide any insurance, I'm pretty sure this method will improve your profits.