Following the posts on the football match prediction system. we have reached the point whereby a chosen model based on certain variables will provide estimates for the probability of a home win, a draw and an away win in any match. What is left, is the small step of translating these probabilities into odds and a deciding whether a bet would be profitable (in the long run) or not.
Assuming that according to a model, the probability of a home win in a given match is estimated at 40%. That would mean that the "fair" odds for this event occurring would be 1 / 40% = 2.50 in decimal form or 6/4 in fractional form. [I'll be using the decimal form from now on as it's easier in algebraic expressions]. If a bookmaker offers odds of 2.20 then according to the model, this betting opportunity does not represent "value" and therefore should be avoided. This does not mean that the match will definitely not end in a home win, however, if an identical match is priced by the model again and again (and again), in the long run, a punter betting on this event will be losing money since the odds offered do not reflect the probability (according to the punter) of that event happening. On the other hand, if a rival bookmaker offers odds of 2.62 for this event, then it should be profitable (in the long run) to bet on a home win since after a number of bets, the punter will be making money because of the value found in these prices.
Essentially, it all comes down to two things: the first is the estimated probability of something happening. The bookmaker and the punter try to price up a match. They both have their subjective probabilities for HDA which are then translated to odds. Time will tell who is pricing the matches correctly (and thus making money off the other).
The second factor to consider is an advantage to the bookmaker. The bookmaker does not need to offer odds which when translated to probabilities sum up to 1. This means that the odds offered are lower than what should have been offered if the bookmaker was fair. This difference is what is called as the overround, and it represents the bookmaker's profit margin. Therefore, a punter will not only need to find value in the bookmaker's odds, but also to overcome his profit margin before actually making money in the long run.
However, the punter can also act for himself. By shopping around, finding the best prices offered by different bookmakers, the punter can almost eliminate the overround, thus start from a level-playing field. He can also use the available booking exchanges to find more competitive prices. These exchanges, in effect, give him the opportunity to become a bookmaker by setting odds for others to bet on, thus creating a market for odds which may be better than the odds offered by online bookmakers.
So there you have it: the system picks will depend on the estimated probabilities of each event (HDA) occurring and the best available prices offered by several bookmakers. Time will tell how accurate our predictions were, and how profitable (or disastrous) the developed model actually is. Fingers crossed!
Assuming that according to a model, the probability of a home win in a given match is estimated at 40%. That would mean that the "fair" odds for this event occurring would be 1 / 40% = 2.50 in decimal form or 6/4 in fractional form. [I'll be using the decimal form from now on as it's easier in algebraic expressions]. If a bookmaker offers odds of 2.20 then according to the model, this betting opportunity does not represent "value" and therefore should be avoided. This does not mean that the match will definitely not end in a home win, however, if an identical match is priced by the model again and again (and again), in the long run, a punter betting on this event will be losing money since the odds offered do not reflect the probability (according to the punter) of that event happening. On the other hand, if a rival bookmaker offers odds of 2.62 for this event, then it should be profitable (in the long run) to bet on a home win since after a number of bets, the punter will be making money because of the value found in these prices.
Essentially, it all comes down to two things: the first is the estimated probability of something happening. The bookmaker and the punter try to price up a match. They both have their subjective probabilities for HDA which are then translated to odds. Time will tell who is pricing the matches correctly (and thus making money off the other).
The second factor to consider is an advantage to the bookmaker. The bookmaker does not need to offer odds which when translated to probabilities sum up to 1. This means that the odds offered are lower than what should have been offered if the bookmaker was fair. This difference is what is called as the overround, and it represents the bookmaker's profit margin. Therefore, a punter will not only need to find value in the bookmaker's odds, but also to overcome his profit margin before actually making money in the long run.
However, the punter can also act for himself. By shopping around, finding the best prices offered by different bookmakers, the punter can almost eliminate the overround, thus start from a level-playing field. He can also use the available booking exchanges to find more competitive prices. These exchanges, in effect, give him the opportunity to become a bookmaker by setting odds for others to bet on, thus creating a market for odds which may be better than the odds offered by online bookmakers.
So there you have it: the system picks will depend on the estimated probabilities of each event (HDA) occurring and the best available prices offered by several bookmakers. Time will tell how accurate our predictions were, and how profitable (or disastrous) the developed model actually is. Fingers crossed!
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