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About paparainbow

  • Birthday 11/08/1982

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  1. Is anyone familiar with simulationg basketball matches play-by-play? any good resource?
  2. Basketball prices are usually sharper than in soccer, that's why
  3. You can try and bet 1.000$ on 1.02 price everyday.. but i think that if you do so 1 or 2 times every 1000 bets will probably lose...
  4. Of course! But it's not about the software rather than the methodology
  5. you have to create a correct score model. keep in mind that expected goals are not the only variables needed. you should need also something like correlation or draw factor. then you reverse enginer your model based on the true probabilities that come out of bookies' prices
  6. Try to understand what odds are and their connection to implied probabilities and true probabilities. then check what value bet is
  7. You just repeated your first post, it doesn’t make sense. in any case i suggest getting raw data and making your cleaning/ wrapping ad hoc
  8. You should get raw data and have some data wrapping yourself. my dataset of choise is footystats (paid). with some simple querries you cAn isolate draws of the league you are interested. from there, for each team you have the time of each goal scored. They offer a column for each team, so for a game ended up draw let's say 2-2 you would have something like home/ 13, 33 away/ 35, 88 so you would have to read each like and clean it with some regular expressions in order to get what you want for your modelling.
  9. It's not about market rather than probabilities and margin applied to them. you have to understand that bookies rely on source markets in order to derive all other markets, hence they are all following the correct probabilities (provided their models are correct). additionally the most of them rely on pricing feeds so they all have same odds. You might find an edge for matches proced early, where market (asian) is not yet balanced and bookies copy each other with limited knowledge on what is going on. avoid top leagues since they usually are well studied.
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