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README.md

Betting-Strategy-and-Model-Validation

1. Summary

Betting Strategy and Model Validation, I analyse the staking model of a sportsbook agency which follow bets from consultancy firm A.

The rebates value inside the dataset doesn't count in Return and PL since it is not includes in win/loss profit but only awarded upon hit a certain amount of stakes. Rebates is a marketing strategy for bankers and also agent to fight for revenue and occupy the market shares.

  • Normally rebates only offers by credit market sportsbook makers.
  • The maximum stakes per bet of cash market normally only up to HKD10,000 while credit market can up to millions HKD1,000,000.
  • Normally only high volume agents, small bookmakers and also high volume sportbook consultancy firms will able to get the rebates.

2. Case Study

2.1 Section A

AI - Soccer team name filtering

2.2 Section B

Data analysis on soccer betting

2.3 Section C

3. Old File

I splited below file to be two part as list above since there are a lot of gragh and high volume dataset. The Return and PL columns suddenly noticed wrong figure and cause the profit of below files are not accurate. Secondly, the old files are not completed as it only stop at section 3 which just a breakdown display and summary of staking data but section 4 and so fort analyse the dataset.

Kindly refer to new files in section [2. Case Study] to know the profit and return of firm A from agent A.

<iframe width="560" height="315" src="https://www.youtube.com/embed/TEhmN-Of--Y" frameborder="0" allowfullscreen></iframe>

4. Future Work

5. Reference

  1. Odds Modelling and Testing Inefficiency of Sports Bookmakers : Rmodel by ®γσ, Eng Lian Hu (2016)
  2. Apply Kelly-Criterion on English Soccer 2011/12 to 2012/13 by ®γσ, Eng Lian Hu (2014)
  3. Creating a Profitable Betting Strategy for Football by Using Statistical Modelling by Niko Marttinen (2006)

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