Previously, we discussed Coach Bill Walsh’s book The Score Takes Care of Itself relates his experience of falling into the trap of a negative scoring system as well as how it affected himself and management of the San Francisco 49ers. We also took a look at Coach Walsh’s advice for avoiding the “zero points” situation.

In a previous entry we looked at a couple of poker examples of how failing to maintain our awareness in regards to managing expectations could turn good situations into negative ones.

So now that we understand the concept, how it can affect us, and how it can relate to poker we will continue to look at solutions. In this entry we will look at another way, beyond those provided by Walsh, to keep ourselves out of the negative scoring system.


AN ADDITIONAL SOLUTION
Probably the greatest pre-emptive “solution” to any negative scoring system is to generate realistic expectations. In order to do so we must first consider how and/or where we can gather the information necessary to assist us with this and then apply that information once we have it.

To look at this process in practice, let's consider how we can work to generate realistic expectations in relationship to our example of the sick heater turned downswing:

Understanding Variance:
One of the best ways to manage our expectations in regards to running well is to understand where we could be statistically both from session to session as well as at the end of the day. We can go a long way towards accomplishing this by understanding how “ugly” and “beautiful” variance can really be and how unrealistic our expectations can become if we allow them to go unchecked.

One very simple way to approach this task is to head over to the BBV Forum at 2+2 and look at some of the graphs that people are posting there. See how many people are running ridiculously behind in expectation and realize that these types of swings, while less probable are nowhere near impossible. Also, consider that the variance being shown here can go the other way and that just as someone may have a -45BI expectation, someone else may have a +45BI expectation graph running (though they are probably a lot less likely to show you their All-In Expectation line). Realize that both of these scenarios could be happening to us.

Another, much better but more time consuming way to understand variance would be to really understand probability and statistics. Unfortunately, I am miserable in the poker math area, but there are others who excel at it. We could seek them out for their recommendations as to where one can get a wider knowledge of how poker math really works and the types of deviations that one could both reasonably and unreasonably expect (while I am *meh* at math, I know that the unreasonable expectations happen more often than we would expect – most players never thought that they would run “so bad” multiple times or they never consider our sick upswings to be more than a “little” positive variance coupled with their vast storehouse of superior skill).

Understanding Winrates:
We could use the wealth of player information available to us on in our personal database as well as on the internet to see what realistic winrates are at our limits. Rather than looking at big name pros that are probably not playing anywhere near your limits, consider the winrates of players that you play against and whose skills you really respect. Take a healthy sample of the solid players at your limits and look how their lifetime winrates vary. Note well, that as poker is a “more is just enough game” we are not looking to ever allow the winrates that we find to make us complacent with ours, but rather to help us just how epic our 22PTB period is and that it cannot last forever.

When are We Close Enough?
With the exception of really getting into the details of poker math, none of the solutions that I provided are going to be 100% precise. For example, if we use internet data to determine a player's winrate we typically do not get to see their All-In Expectation Line, which means that the winrate could be skewed (either up or down). But, realistically, as long as the samples are large enough we should be able to get "close enough" as long as we look at information for several players. We will most certainly be closer to reality than if we opted to not use the information available to us.


ONE MORE TIME
Our final post on this topic will continue to work us through our poker example and take a look at a couple of tools that we can use to assist us in anticipating and correcting unrealistic expectations, which are a huge root component of a negative scoring system.