There have been several posts in this thread with a similar theme. That being, "I have played <a certain way> and have had <some degree of success>". This kind of anecdotal evidence does not really carry much weight in terms of establishing the effectiveness of a particular strategy. As with straight up AP play, one must collect data on many millions (preferably billions) of samples in order to approach a result which is statistically significant. Even if someone was to play a tournament every day for their entire life they would not collect enough data to establish the effectiveness of their particular strategy.
This is, most likely, the only way to collect a significant amount of data. Fortunately, I can shed some light on this. The end-game strategies are all pretty well documented and, for the most part, agreed upon. I began to wonder about effective strategies for the early and middle hands of blackjack tournament rounds, and I did exactly as you suggest. I created a simulator that can simulate subsets of actual tournament conditions that I have encountered, ranging from single hands to entire tournaments. Each tournament is populated by bots which employ different early/middle round strategies that I have either observed in real play or have come up with myself. All of the bots have the same level of skill when it comes to finishing. The bots play against one another and statistics are collected about their performance. The purpose is to see which tactics at which levels of aggression are most effective in setting one up for the end-game under particular tournament conditions.
The reason that this is relevant here is that some of the strategies lend themselves to variations in bet size and timing and for those I have included variants which consider the count. So there might be a bot which employs "strategy X" and another which uses "strategy X with counting". In every case, for every situation I have studied, the bot that uses counting either has the same performance as the variant which does not or performs worse. The reason is that these bots sometimes mistime their moves (in a strategic sense) because of the count. They either move too early or too late, or they make big move when out of position, so that their opponents can easily counter them.
Just some more fuel for the fire ....
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