Playtraces are artifacts produced during playtesting that tell a story about how game systems operate and what actions players take at runtime. The playtrace contains relevant metrics in a game alongside the metrics’ rising and falling throughout player progression. These curves inform designers about their players’ experiences and open opportunities to implement player-adaptive design strategies. To help improve the iterative design process around playtrace analysis, we introduce the Playtrace Arc Search (PAS) tool. PAS allows designers to search through a large corpus of playtrace data to find the system metric curves that match their design intent by drawing a desired progression arc on a canvas and then using that to perform a curve-similarity search over all playtraces. PAS enables designers to see a set of playtraces as a summarized whole, then search against that whole to find specific, meaningful gameplay data that can confirm or reject their hypotheses about game and player performance. PAS showed success on an initial evaluation of 1,000 playtraces; this, combined with its game-and metric-agnostic capabilities, indicates that PAS might be a useful tool for designers to rapidly discover whether their design hypotheses are accurately played out in metric progression curves with desired levels of consistency.