As we know, the key count is the running count at which we first have the advantage. Fortunately, in the K-O system the key count is a function only of the number of decks in play and little else. This is true for all sets of rules you're likely to encounter.

We can determine the key counts empirically by simulating the K-O system and looking at the expectation as a function of the running count. Consider Figure 6 derived via simulation.
Clearly, if your goal is to make money, the best strategy would be to avoid all hands with a negative expectation.

Just skip them altogether and play only when the playin's good! If adopting this strategy in, let's say, a 2-deck game, then we would count down the deck as it's being played. Whenever the running count got to + 1 (the key count) or more, we would jump in and play. If the running count was 0 or less, we would sit out the next round. In this way, we would be playing only in positive-expectation situations.

We can also estimate the relative value of a one-point change in the running count once we have the advantage. In such favorable situations. we find the results listed on page 99.
Some readers may be surprised by the magnitude of the change in a single-deck game. Remember that the K-O has no true-count conversion.

Thus, the change in expectation represents an average over the prevailing conditions. A typical card removed from a single deck will change the expectation by about 0.45%. A card removed from only half a deck will change the expectation by about twice as much, and so on. When these effects are averaged over a single-deck game with 6517~ penetration, we wind up with an average effect of 0.91/(. The same type of reasoning can be used to understand the rest of the table.