“Q-Ant is SaaS for quantitative estimations of football player transfer fair value and performance.”
This is purely quantitative analysis. It means that it uses large player database, with historical values for more than 300 variables describing every player action, performance or physical characteristic. In data analysis, no biased football expert opinion is used to give estimation of variable importance or final estimation, but our algorithms are making those quantitative choices. On the other hand, every direct participant (negotiating teams) in football transfer leaves hidden imprint of their preferences and decisions in our dataset. Our quantitative model reveals those hidden imprints and gives us a way to quantitatively estimate football player transfer fair value in a way similar to one that direct participants of transfer negotiating process use. Of course, actual transfer price, when one occurs can be formed with different incentives so our estimation can be viewed as “fair value”.
“Player Rating” is quantitative estimation ofplayer performance quality. It groups players in 10 classes, with 10 being the highest rating. In this rating estimation, no biased football expert opinion is used to give estimation of variable importance or final rating estimation, but our algorithms are making those quantitative choices. Our quantitative model reveals hidden patterns in data which point us the way to quantitatively estimate football player rating.
We established quantitative model whose algorithms can estimate football indicators that can’t be measured by single variable value. “What really describes “Strength” or player “Pace”?” Well, our model can answer that question. Furthermore it gives fine measure of player performance in a form of “Performance index”. Beside estimation of time change of “Performance index”, we developed quantitative model that can give player’s “Performance index” for a single match. As all our models these are unbiased by “opinions”. They are fully quantitative.
“Football player performance and expertise (knowledge, experience and even intuition) of football experts directly involved in play and transfers (e.g. coaches, managers and their teams), leaves a hidden imprint in large statistical datasets. Our quantitative statistical approach reveals those hidden imprints in it.
That way it is possible to build quantitative engines that can give us precise, impartial and reliable estimations."
Q-Ant gathers experts whose goal is to build efficient, reliable and transparent quantities models, to boost creativity and out-of-the-box thinking, when it comes to application of quantitative approach. With experience in quantitative modelling for finance and corporate industry needs, we approached the football game and market and built quantitative models, aiming to provide football transfer market quantitative analytics tools as well as full quantitative performance indicators estimations.
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