Do you bet on the outcome of sports matches just for fun or to win? If it’s for fun, the chances are that you bet with your heart. Provided that you don’t care too much about losing, there is no harm at all in that. But if you are serious about winning, you must at least put your own brain to work on the matter, if nothing else. What else will work better? Using a worthwhile Selection System!
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You may now be thinking how impossible it would be for you to do that for yourself easily. Well, the truth is you’re right, unless you severely limit the extent of the coverage. Properly compiling and updating the data for something like all the UK main soccer Divisions is a time consuming task, and to do it to a good standard requires a great deal of commitment and probably more hours than you would possibly care to put in. Fortunately though, there are a handful of reasonable Tipster Services out there on the Internet that do the job properly, and yet will charge you very little for their services. You’ve just got to find them!
First of all, what should you be looking for? Well, any worthwhile Selection System for team-based sports must determine the prime selections in an orderly and methodical manner. There is only one way to achieve that, and that is to ensure that the output is based on statistics that are as unbiased as possible. Anything else is a sham, because the same level of success can’t be replicated or validly adjusted for changed or changing circumstances, as there would be no principled way to adjust the predictive mechanism.
As an example of a typical non-statistical method of selection, let’s imagine that the last time you put money on a certain team to win it rained, and that team lost. So, as rain is forecast for tomorrow, should you therefore bet on that team losing this time around? Perhaps surprisingly, the answer is not an obvious ‘yes’ or ‘no’; it all depends on the circumstances.
Let’s suppose that you had sufficient data to tell you that out of the last 200 matches played in the rain, that team had lost 90% of its matches. Maybe then you would have good cause for thinking that it will most likely lose tomorrow’s match. But that wouldn’t apply if all you knew was that it had lost the last, say, 5 matches played in the rain. You would then need to know a whole range of other key indicators, such as – but certainly not limited to – (i) whether or not it had been ”expected” to win against those previous teams (regardless of the weather) and (ii) whether or not it is ”expected” to win tomorrow. You would also need to have faith in the way the ”expectations” were compiled and, of course, faith in the weather forecaster’s abilities!
Some so-called Selection Systems available on the Internet do no more than tell you the likely probabilities of the occurrence of the output for each match (for example: for the A v B match, Home Win 55%, Draw 27%, Away Win 18%). Most of those that offer this type of information don’t even bother to give you a rating of any sort for the teams or any other data to enable you to prioritise the advice. So if there are 10 matches with the same output possibilities, then you won’t have a clue from the limited amount of data they give you which ones stand the better chance of coming good. These are not true Selection Systems and aren’t worth subscribing to.
Further, if that deficiency is compounded by the fact that the promoters don’t bother to update their databases quickly enough (thus failing to include current performance in their predictions), then it renders such Systems even more useless. All you would be paying for is very pretty graphics that at best tell you nothing and, instead, will most likely lead you very badly astray.
For a Selection System to be worthwhile it must provide you with enough data for you to be able to readily check the validity of its output for yourself. With soccer, for example, the absolute minimum amount of data you should be looking for is the following for each Team (overall, at home for the Home Team and when away for the Away Team):
(a) their Win Quotients (the measure of their chances of winning);
(b) their Scoring Abilities (the average number of goals scored by them on a running basis); and
(c) their Vulnerabilities (the average number of goals scored against them on a running basis).
Ideally, all the above information should be given as ”start of season” data and ”current” data, to enable you to judge how a team’s performance has changed during the course of the season. In addition, a worthwhile Selection System would also provide you with the following data for each and every match:
(a) the probabilities for each of the possible outcomes;
(b) the probable score line; and
(c) the details, where applicable, of the result and score line for the last time the two teams met within the previous 12 months.
Remember this too – a Selection System’s output is not much use to you if you still lose money. It may boast an average 60% success rate for its top 10 Home Win predictions, but if all it has done is identify the most obvious Home or Away Wins, then it means you will be betting on favourites, with very poor odds. The likelihood is, therefore, unless you are clairvoyant and manage to skip betting on ”let-down” weeks, long-term you will always lose by betting on such poor value tips.
And finally, make sure that you can get to see what the track record for the System looks like, with week-by-week ”drill down” checkability, for at least one whole season.
If a Selection System can’t give you all the above data and satisfy your need for more ”quality” winners, then it just isn’t good enough. It really is that simple to make a judgement call about it!
Woz Salmon is a specialist in risk analysis and mitigation techniques, whose primary aim is to help the average football bettor significantly improve his/her chances of winning more money from the Bookies. Woz Salmon runs Predict A Win.
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