Introduction To Sheepshead Research

The goal of this blog is to distribute insights about the game of Sheepshead as learned from the data collected on the get61 Sheepshead site. Most of us grew up playing Sheepshead with our family and have carried a love of the game into adulthood. Through experience, we have created our own strategies for various scenarios we might find ourselves in, not the least of which being a way to determine whether we have a good enough hand to pick on.

Quite possibly the most important decision made in any hand is whether to pick. The decision of whether to pick boils down to only a few things: what cards do I have, where is my position in the picking order, and what is the penalty for picking and losing?

We will spend most of our time, at least at the beginning, studying the decision to pick. These are not intended to be scientific papers, inaccessible to people without a college degree in math, but there are some key concepts one should understand going into future writings.

For now, I will write this blog assuming its readers are Sheepshead players. Therefore, I won’t necessarily define Sheepshead terms like smear and schneider unless I feel there might be confusion even among long-time Sheepshead players. If you are new to Sheepshead and looking for a good resource to learn the game, visit the authority on Sheepshead.

Key Ideas


All of us feel we know what a strategy is, but it is necessary to be a bit more formal here. Our Sheepshead strategy is our rules that tell us what card to play, whether to pick or pass, and whether to smear. If Sheepshead were big business, we would create a system of rules that tell us what to do in any situation we might find ourselves in. We have already mentioned our picking strategy as the most important part of our system of rules, but over time, we will investigate things like what to do on defense when the picker leads fail.

When we use the word rules in referring to our strategy, we are not talking about the rules of the game itself. We are only talking about the rules that govern our course of action within the contraints, or rules, of the game.

Expected Value

An expected value is the average result of employing a strategy over the long-term. It is like saying, “If I find myself in this situation 10,000, what would the result be, in terms of points, if I employ Strategy A? What would the result be if I choose Strategy B.” In choosing between strategies, we are looking for the strategy which offers the best possible outcome for oneself.If Strategy A has an expected value of 1, that means every hand I employ Strategy A in the scenario we are talking about, I expect to gain 1 point. Similarly, an expected value of -0.25 means I expect to lose 1/4 of a point, on average, when I employ the strategy in question.

Lets look at an example. Suppose I am dealt the top 6 cards and pick can first. Further suppose the rules at my table are jack of diamonds partner, blitzes, cracks, and no double on the bump. If I pick and bury the two cards in the blind, I am guaranteed I will no trick the other team. For simplicity sake, suppose I know the jack of diamonds is not in the blind. I can do one of three things:

Blitz in (pick and double the points the hand is worth by showing my black or red queens). This strategy has an expected value of 24 since I am guarateed I will win 24 points by doing this.

Pick without blitzing. This strategy has an expected value of 12.

Pass. This strategy has an expected value of 0 since the cards will likely be passed around the table and a new hand dealt as a doubler.

Clearly, in this situation, we should blitz in. The decision of whether or not to pick depends solely on what we think our expected value is if we pick against what it will be if we pass. The data from the site will help us understand when we should pick and when we should pass.

Predictive Model

One might ask, “how can we say what the expected value of picking on a given hand is? Do you plan to take a hand, look it up in all the hands that have been played on the site, and check how well people did when they pick on that hand?” Even if that were possible, it would be a highly inefficient use of the data. Instead, we will build a predictive model that uses each of the hands that have been picked on, the picker’s position in the picking order, and the result of the hand. We will built a predictive model that allows us to score any hand that can come to us in the future, and we will be able to say what the value of that hand is if the player picks in the picking order they are in. We will also be able to estimate the expected value of not picking.