Maximizing Values in Lucky7 ID: Adjusting Betting Weights

The Lucky7 ID tries to set a target cell to a specific value by modifying other cells. Solver is utilized for our purposes to discover the maximum achievable value for the return to risk ratio by adjusting the betting weights. Because Clarke and Katich are the only players with a positive expected return, the example in the screenshot below simply manipulates their weights. It should be noted that a limitation is placed so that the total of the weights equals.

Optimizing Risk-Adjusted Returns: Strategic Betting for 0.14 RRR

We have an expected return of 18% and a standard deviation of 131% by betting 48.5% on Katich and 51.5% on Clarke. This yields a return to risk ratio of 0.14, a significant improvement over 0.09 if we solely backed Clarke. We have dramatically decreased our risk while merely lowering our estimated return from 21% to 18%. This is a significant improvement over the previous technique of maximising expected return.

Based on the preceding example, our best option for $100 on this market is to put $48.50 on Katich and $51.50 on Clarke.