Bigdatatennis is a sports betting forecasting service based on bigdata solutions. Thanks to our database, we are posting forecasts for the winner of the ATP tennis match and challenger since 2016 with a sustained yield of 4%. A yield of 4% is not the same as a bank return or in investment funds where the ratios are reported with a return period of one year. In sports betting you can get a rotation period of less than 2 weeks, so that last year we managed to convert this 4% yield into a real return of 150%. We see it with an example: With an initial bank of € 1,000 and a moderate stakes strategy we were able to “turn around” those € 1,000 more than 37 times, which resulted in a total profit of € 1,500, calculated on a € 1,000 investment, we get a return of 150%. Now we will explain reliability, stakes, strategy and liquidity. Reliability is guaranteed by blogabet, which is the main sports betting marketplace, it is a website where betting tips are published and the web verifies them. https://bigdatatennisinvestmentsatp.blogabet.com/ Publishing more than 1,600 picks since August 2016 it seems that the reliability of the system is more than proven. Since we overcome some technical problems in April 2017 we have ended up positive 22 of 28 months.
More than 90% of the forecasts are published with Pinnacle odds, which ensures that the odds stay available when the customer makes his bet. A widespread problem in forecasting services is about dropping odds after posting picks because the market is not enough mature, or unstable oods based on a bookie mistake or is a very volatile market such as winning 2-0. The problem with this is that the client does not have time to take advantage over bookmakers. Thanks to the fact that we publish in Pinnacle and always to the ML market, this is not an issue.
We currently publish forecasts of 3 and 4 units (the majority stake 3). To establish your winning strategy you should keep in mind that according to our simulations our maximum theoretical drawdown https://www.andbank.es/observatoriodelinversor/que-es-el-drawdown/ is 38 units, that is, in all our simulations the maximum drop we have suffered is 38 units before returning to the previous maximum. (The drawdown is a concept used on the stock market to measure the risk of an investment). This means that You must make sure you are ready to lose 38 units. This allows you to establish a stake unit up to 1/50 (AGGRESSIVE STRATEGY) of your bank knowing that there will never be bankruptcy. Our recommendation is to have the unit somewhere between 1/50 of the bank, and 1/100 of the bank (strategy plus CONSERVATIVE). Example:Divide your total bank by 50 and the result must be the value of one unit. If you have a 1.000€ bank: 1.000 / 50 = 20€/unit. So stake 3 would equal € 20 x 3 = 60€, so in the more aggressive strategy you would bet 60€. For a more conservative strategy, you substitute 50 for a higher number. How about number of bets? it is usually between 35 and 50 each month and always between Wednesday and Sunday which makes the service more comfortable since you do not have to stay tuned every day. The reason for not betting at the beginning of the week is doubts about the commitment, motivation and fitness of a tennis player in his first week match and therefore it is not possible to find sustained benefit via Machine Learning. We only bet when the tennis player has already played a match in that tournament that same week.
No fixed time because there is tennis in all the time zones of the world, but we always publish with plenty of time for you to make the bet and usually all the picks are posted together once a day.
From simulations carried out using bigdata solutions we have discovered market inefficiencies in odds from 1.2 to 1.65. However, if we find value on a higher range, it would be taken advantage of. The reliability of this type of bets on favourite is very high and therefore we reduce the variance avoiding bad streaks. There are many good tipsters who get benefit during months, but very few who can keep the benefit for 2 or more years. Human factors such as fatigue, pressure, environment, make it almost impossible to maintain the advantage for a long period of time. However, our model does not understand these problems, re-trains with new games and keeps long-term benefit. These are the advantages of making decisions based on data.