That is, if a system produces a 57% winning percentage over 2,000 games, mathematicians say that there is a 95% chance that the results are true (results will be better than 55% in the long-run). Please see Graph 1 for a plot of “Winning Percentage versus Sample Size.” Below 2,000 games, the results are good, but statisticians wouldn’t say that results are “significant” enough.
Note that there do NOT have to be hard and fast rules about statistics. Some mathematicians label results as “mildly” significant or “highly” statistically significant. Let’s just say that for us to consider a system, it should average greater than 57% or some other “hurdle-rate.” If the sample size is greater than 2,000, super! (If the sample size were a million games, just over 55% would be good enough!) Situs Judi Online Resmi
From Graph 1, we can see that at a sample size of 20, you would need to hit around 80% to prove statistical significance. If a decent system is connecting at 67%, it doesn’t mean that it’s “no good.” It just means that there is too much randomness in the small sample size and that the system should be tested over more games (a longer time period or larger sample size). Don’t throw it out! Just give it time and watch how it performs in the long-term.
At the 200-game sample size, you would need a winning percentage in the low 60% range to prove statistical significance. Again: you should use your judgment and consider variables such as luck (slow start for a system) and the long-term average.
Over time, we know that various systems and approaches will have ups and downs. “System A has gone 7-2 since I tracked it.” Based on Graph 1, a sample size as small as 50-100 can start to tell us a story (10-20 is too small a sample size, unless results are extraordinary) – but 200-500 is even better.
An important part of what we do is: maintain a clean database of the sports marketplace. We then analyze the data and try to help our members profit from the sports markets, just like investors profit from the stock market.
How does use “statistical significance?” Results for “Betting Against the Public” are fairly consistent across the major sports. Favorable results for some sports (that generate many games such as the NBA [2400 games] or MLB [4000 games]) can be shown to be statistically significant for that particular sport. When taken in total (our database includes more than 10,000 games!), we are pleased that Betting Against the Public results are robust and statistically significant. Smart Money methods also show good, robust, and statistically significant results, albeit over a smaller sample size.
We do not guarantee that the trends and biases we’ve found will continue to exist. It is impossible to predict the future. Any serious academic research in the field of “market efficiencies” recognizes that inefficiencies may disappear or fade over time. Once inefficiencies are discovered, it is only a matter of time before the market corrects itself. We do not guarantee our data is error-free. However, we’ve tried our best to make sure every score and percentage is correct.