If it was strongly strategy-dependent, best-information would win predictably and consistently.
Regardless of your objective - hosting a contest like this or allocating to individual institutions and strategies - you'll always face this problem. Good allocation decisions are tactical, taking both the logic of the strategy and the broader portfolio into account. Bad allocation decisions chase returns.
[1] https://en.wikipedia.org/wiki/Multiple_comparisons_problem
[2] https://en.wikipedia.org/wiki/Regression_toward_the_mean
Not sure if you know, but that winning algorithm was taken offline within one month for poor performance. It was probably just overoptimised on past data to win the competition and then failed miserably out in the real market.
Same rules apply to your example.
Yes, but then... "Finance novice beats hedge fund pros, winning $100k in Quantopian trading contest"
https://pando.com/2015/03/05/finance-novice-beats-hedge-fund...
Thousands of brilliant people are out there undiscovered and I think quantopian does a great job leveling the playing field.