The distribution of preserved skeletal injuries reflects behavior and perhaps the risks of activities such as hunting large prey. Here, we used Geographical Information Systems (GIS) to interpret injury patterns in two Pleistocene predators from pit 61/67 in the La Brea tar seeps, the sabertooth cat Smilodon fatalis (SF) and the dire wolf Canis dirus (CD). Using a previously diagnosed pathology collection, we mapped 1700 traumatic and chronic injuries on skeletons of CD and SF using ArcMap 10.2 (ESRI 2015) and analyzed their spatial distribution. The number of traumatic SF pathologies was 1.75x greater than that of CD. Optimized hotspot analysis revealed significant differences in injury distribution. Whereas SF had dense injury clusters on the scapula, lumbar and thoracic vertebrae, CD had clusters on the femur, olecranon, wrist, ankle, and cervical vertebrae. This distribution are consistent with hypothesized hunting modes. SF was an ambush predator that used a muscular back and forelimbs to pull down prey, whereas CD was a cursorial pack hunter that incurred limb injuries when in pursuit and neck strain during prey capture. Injury centroids were significantly more dispersed across the skeleton of Canis dirus than in Smilodon. Comparable numbers of each predator were found, thus differences in distribution likely reflect differing risks of each species’ hunting mode. Our results suggest that Smilodon suffered more trauma than dire wolves, possibly due to a larger typical prey size or a longer life span. As a visualization tool, GIS excels in making large volumes of spatially-associated data accessible. In addition, the representations can be instantaneously filtered to examine subsets of data and aid interpretation using free QGIS software.