An example of Play tracer's output can be seen in Figure 1, which shows the state space for one level of an educational game we have been developing. Playtracer takes in a list of all of the states that the player visited and a distance metric that calculates the distance between states, and creates a graph where the states are vertices and player movements are directed edges. Here, the yellow state is the start state and the green state is the goal state. To identify which states are most commonly visited, the size of a state is proportional to how many players reach that state.
One useful way to analyze games is to find areas where a large proportion of players fail. If 90% of players who reach a similar set of states give up, then the designer should focus his or her attention on those states and the paths leading to it. To this end, Playtracer has an alternate color scheme, shown in Figure 2. Several players gave up on one or more attempts and are represented in red. Players that finished, on the other hand, are represented in blue. In addition, states are colored to reflect the probability that a player who ended up in that state went on to finish the level; bluer states are ones mostly visited by winning players, while redder states are ones mostly visited by losing players. Large red-hued states are of particular interest as they represent states visited by many people who mostly failed.
We include two additional features that might prove useful. One is to view only players that won or only players that lost in order to quickly see the differences between them, as shown in Figure 3. The second feature is that we can easily identify path cycles and show or hide them at will. Cycles, like in Figure 4, represent failed player hypotheses: the player started at a state, then went to several other states before returning. Viewing only cycles shows common ideas that players tried but later decided against, providing insight into how players think about the game strategy. Stripping cycles from the displayed paths, on the other hand, reveals the backbone of the path the player took to his or her final state; in essence, it is the last approach that players decided upon for that level.