1 / 9

BetSmart

BetSmart. Ximing Yu Ying Jin Cai Chen. Business Model. Architecture. Data Mining. Logistic Regression: Probability of each class label Input Pool(23 input)

kaipo
Télécharger la présentation

BetSmart

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. BetSmart Ximing Yu Ying Jin Cai Chen

  2. Business Model

  3. Architecture

  4. Data Mining • Logistic Regression: Probability of each class label • Input Pool(23 input) week, h/a points4week, h/a points10week, h/a points30week, h/a teamhomeawaywinratio, h/a drawratio, h/a avggoalfor10week, h/a avggoalfor40week, hometeamhomewinratio, awayteamawaywinratio, hometeamhomedrawratio, awayteamawaydrawratio, h/a avggoalagainst10week, h/a vggoalagainst40week • Output: Result(hw-home win, aw-away win, draw-dr)

  5. Data Mining • Accuracy: 85% • Average Odds as benchmark • Predicted Probability V.s. Probability from odds

  6. Novelty • Google App Engine • Intelligent Spider • Data Duration: 12 Years • Quick Search Engine for Clubs and Players

  7. Competitor Analysis

  8. Team Contribution

  9. Thank you

More Related