The investment in sportsbook industry is very popular in Europe and United States but not yet in Asia. I tried to refer to Dixon and Coles (1996), Karlis and Ntzuofras (2005) and some others papers to complete my ®model ®γσ, Eng Lian Hu (2016)^[1st paper in [3. References]] but the return is not stable and I try to apply Kelly model and generates an impressive returns which is in section [1. Kelly Criterion].
The section [2. Comparison of Betting Strategy in Sportsbook Investment] will not only compare the staking model in betting model validation ®γσ, Eng Lian Hu (2016)^[2nd paper in [3. References]]. and also Kelly model in section 1 but also enhanced.
I have simulate a betting model on 13 bookmakers across 2 soccer seasons in English 2011/12 and 2012/13. Kindly refer to below techincal research.
- Application of Kelly model in English Soccer session 2011/12
- Application of Kelly model in English Soccer session 2012/13
| No | Category | With Spreads (2011/12) | Ratio (%) | Without Spreads (2011/12) | Ratio (%) | With Spreads (2012/13) | Ratio (%) | Without Spreads (2012/13) | Ratio (%) |
|---|---|---|---|---|---|---|---|---|---|
| 1 | No of Matches | 4,896 | 1 | 4,896 | 1 | 5,514 | 1 | 5,514 | 1 |
| 2 | Total PL | $353.96966 | 55.57% | $381.06299 | 53.98% | $448.8993 | 59.35% | $488.91841 | 58.60% |
| 3 | No of Bets | 2,268 | 46.32% | 2,404 | 49.10% | 2,570 | 46.61% | 2,697 | 48.91% |
| 4 | No of Won Bets | 1,531 | 31.27% | 1,584 | 32.35% | 1,765 | 32.01% | 1,824 | 33.08% |
| 5 | No of Voided Bets | 128 | 2.61% | 143 | 2.92% | 192 | 3.48% | 196 | 3.55% |
| 6 | No of Lose Bets | 609 | 12.44% | 677 | 13.83% | 613 | 11.12% | 677 | 12.28% |
| 7 | Staking | $636.98372 | 1 | $705.89203 | 1 | $756.2979 | 1 | $834.32032 | 1 |
| 8 | Won Bets Stakes | $453.43724 | 71.19% | $496.09555 | 70.28% | $563.6685 | 74.53% | $614.24795 | 73.62% |
| 9 | Voided Stakes | $19.13296 | 3.00% | $22.67241 | 3.21% | $27.1151 | 3.59% | $32.12999 | 3.85% |
| 10 | Lose Bets Stakes | -$99.46758 | -15.62% | -$115.03256 | -16.30% | -$114.7691 | -15.18% | -$125.32954 | -15.02% |
table 1.3.1 : Staking breakdown and result of the bets settlement.
| Company | PL (2011/12) | Ratio (%) | PL2 (2011/12) | Ratio (%) | PL (2012/13) | Ratio (%) | PL2 (2012/13) | Ratio (%) |
|---|---|---|---|---|---|---|---|---|
| Ladbrokes | $33.772411 | 9.54% | $38.25184 | 10.04% | $44.53507895 | 9.92% | $46.7763362 | 9.57% |
| Bet365 | $34.120624 | 9.64% | $37.19263 | 9.76% | $33.53743752 | 7.47% | $40.6766948 | 8.32% |
| Macauslot | $35.740062 | 10.10% | $40.23454 | 10.56% | $1.76408658 | 0.39% | $1.9329171 | 0.40% |
| X10Bet | $37.538487 | 10.61% | $41.64034 | 10.93% | $33.62892077 | 7.49% | $40.6921976 | 8.32% |
| X188Bet | $36.579289 | 10.33% | $38.25589 | 10.04% | $41.05668234 | 9.15% | $46.1156378 | 9.43% |
| SBOBET | $40.392461 | 11.41% | $41.90898 | 11.00% | $43.50915478 | 9.69% | $47.8308212 | 9.78% |
| Mansion88 | $31.219547 | 8.82% | $32.38999 | 8.50% | $42.44403404 | 9.46% | $43.9521665 | 8.99% |
| YSB88 | $13.167746 | 3.72% | $14.34128 | 3.76% | $45.92688667 | 10.23% | $46.8393963 | 9.58% |
| X12BET | $36.802466 | 10.40% | $38.19015 | 10.02% | $36.03065656 | 8.03% | $36.2449956 | 7.41% |
| VictorChandler | $24.391917 | 6.89% | $25.95763 | 6.81% | $45.13420638 | 10.05% | $46.2154620 | 9.45% |
| Canbet | $10.347393 | 2.92% | $10.97516 | 2.88% | $41.04019224 | 9.14% | $46.9617659 | 9.61% |
| Betinternet | $10.286812 | 2.91% | $11.18731 | 2.94% | $40.20594752 | 8.96% | $44.5435274 | 9.11% |
| Titanbet | $9.610441 | 2.72% | $10.53726 | 2.77% | $0.08604952 | 0.02% | $0.1364944 | 0.03% |
table 1.3.2 : Breakdown of Operators - Profit & Loss on the Odds Price with/without Overrounds.
By conduct above betting model and get a positive and impressive returns from the experiments, here I have try to retrive the betting model of British sportsbook consultancy firm A.
Besides, by refer to [3. References] I try to build a simple shinyApp for betting model prior to build up my own Scibrokes® business website...
betting-models shinyApp
Based on Betting-Strategy-and-Model-Validation, in order to test the risk of ruin, here I focus on English soccer leagues which will write as an shinyApp and set few elastic adjusters to test the efficiency of the sportsbook investment fund :
- the initial fund size
- betting stakes
- average follwed odds price (volatility of odds price, ets, arima and garch models.)
- missing followed bets
- investment fund portfolio management (markotwitz and Kelly criteria)
- regular investor refill or pump into initial fund pool
Secondly, application of own Rmodel Odds Modelling and Testing Inefficiency of Sports Bookmakers to test the efficiency and comparison.
- Odds Modelling and Testing Inefficiency of Sports Bookmakers : Rmodel by ®γσ, Eng Lian Hu (2016)
- Betting-Strategy-and-Model-Validation by ®γσ, Eng Lian Hu (2016)
- Systematic Investor Toolbox (SIT) by Michael Kapler (2012)
- MatchOdds.org by Simon Collins (2010)
- Bayesian statistics, health economics and random stuff by Gianluca Baio
- Sportsbook Pricing and Informed Bettors in the Early and Late Season in the NBA by Rodney Paul, Andrew Weinbach and Brad Humphreys (2013)
- The Kelly Criterion in Applied Portfolio Selection
- The Kelly Criterion in Applied Portfolio Selection – Part 2
- The Kelly Criterion — Does It Work?
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