Stetson Hatters at South Carolina Gamecocks

On Tuesday, November 3, 2026, South Carolina pulled away for an 81-55 victory over Stetson, handing our pick on the Hatters (+19.5) a clear loss. Stetson failed to stay inside the tracked number, missing the cover by 6.5 points as the Gamecocks dominated both ends of the floor.

Our statistical model was far too optimistic about the road underdog, projecting a competitive 78-74 finish and finding what looked like a massive 15.7-point edge. Instead, Stetson’s offense stalled from the opening tip. The Hatters managed just 55 points on the night, falling nearly twenty points short of their projected output against a stifling South Carolina defense.

Leaning on early-season baseline metrics without sufficient current-year data proved costly here. The model failed to account for the athletic mismatch and talent disparity between the two rosters in this matchup. It was a decisive miscalculation on our high-rated pick, and we will incorporate these early-season data points as we recalibrate future non-conference projections.

The South Carolina Gamecocks host the Stetson Hatters on Tuesday night in early-season action. Market oddsmakers have positioned the Gamecocks as decisive favorites, establishing a tracked spread of South Carolina -19.5 with an over/under game total set at 149.5.

Our statistical model forecasts a significantly more competitive contest than the market suggests. The baseline projection estimates a 78–74 victory for South Carolina. That 3.8-point projected margin yields a 15.7-point edge in favor of Stetson covering the +19.5 spread we took, earning this selection a high rating from the model.

Because early-season data remains a thin sample, the projection leans steadily on adjusted league baselines and baseline efficiency metrics. While South Carolina holds the clear talent and home-court advantage, our numbers indicate that Stetson has the tools to keep the final margin well inside the nearly twenty-point cushion. As always, these projections represent probabilistic data rather than certain outcomes.