QuantOdds Consulting utilizes advanced computer models to calculate value propositions based on a probabilistic determinations.
While there is a lot of data currently available, and other firms are trying to replicate our models, where QuantOdds stands-out is in our proprietary inputs built on variables not commonly utilized.
It is quite easy to see the performance of a team home or away, for example, but what are the factors associated with the current line, and the associated variables?
Which is to ask the question - are there any specific and definable factors that establish causation and not simply correlation? How robust is a model built on these variables?
Our quantitative models incorporate our probabilistic estimates, and include market sentiment, asking the simple question - does the prevailing line differ from our analysis?
While there is no 'magic' model or system that can predict the future, we believe that our quantitative models and analysis can certainly add value and depth when looking at a given event.
How are we different?
That is a great question. The fact is that the majority of systems, both computer models and old-school human analysis, uses the same inputs. For example, what is a team's away/home record, points scored/allowed and so on. Everyone is looking at the same information, which leads to herding mentality.
We asked the question - is there a better way?
We believe that yes, there are alternative methods of analyzing sporting events to calculate probabilities. As you see, we are not trying to predict an outcome, since that is impossible, but analyzing data to determine what is the highest probability of an event occurring.
We actually start with a lot of these basic inputs that are freely available, but most of our analysis is quite different. We can't divulge exactly what we look for, but suffice it to say we try our best to avoid being just another sheep in the herd.