True Count frequency distribution

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Let me introduce these three true counts, TC_p0, TC_p1, and TC_p2, representing TCs at the bet point p0, 1^st card arrival point p1, and 2^nd card arrival point p2, respectively. Here I only consider the probability of a player’s Blackjack, which is proportional to,

TC_p1 x TC_p2.

However, these two TC numbers are unknown, so player places a wager at p0 to approximate the situation. This wager amount is proportional to,

TC_p0 x TC_p0.

Here, there is a betting correlation problem. If p0, p1, and p2 are close together, as in a single-player table, the correlation is stronger and thus the profit is more.

For a multiple-player table, these three points p0, p1, and p2 are far apart. If we still assume TC_p0=TC_p1=Tc_p2 using the TC Theorem assumption, we oversimplify the TC function,

TC_p= 52 RC_p/(312-p),

especially at the later stages of a shoe when p is large. Therefore, we lose out higher TC opportunities for more rewarding bets. I am saying, the True Count Theorem is not applicable to a multiple-player blackjack table. Is this right?