title: Use machine learning to analyze sports bets
body: <p>Lets say I have database with over 1 Million bets (all kinds of sports) made by couple thousands of users, over a period of 2 years (and still growing). </p>
  
  <p>These data are just lying around doing nothing, so I thought if it would be possible to use something like <a href="https://www.tensorflow.org/" rel="nofollow noreferrer">https://www.tensorflow.org/</a>, do a bit of tinkering and it would analyze all the bets in database and learn from it some patterns, whats good and whats not.</p>
  
  <p>The point being is we dont have resources to employ dozens of people for god knows how long to write some complicated software from the ground up. So I was thinking we could use some module from TensorFlow and go from there.</p>
  
  <p>So then I would feed the network with new open bets that are currently in the system (those would be bets that are on matches that are about to be played) and it would pick for me what I should bet on, for example there is a 90% chance this bet will win, because 10 very successful players made this bet, and they have very high success when betting on this particular sport.</p>
  
  <p>We have lots of experienced users, they make lots of money from betting. So the system could be trained on the data we have and then it would know, for example, if user A bets on this league/team, its very likely he will win.</p>
  
  <p>The question is, where do we go from here? Can anybody point us in the right direction? Or is this just too difficult to do, for 2 people in few months? Can we use some pre-programmed solutions, like TensorFlow?</p>