Furman Women’s Lacrosse Academic Excellence: 12 Honor Roll Athletes
Furman University's women's lacrosse team has been recognized as an IWLCA Academic Honor Squad for the 2025-26 academic year. In addition, 12 student-athletes from the team have made it to the prestigious Academic Honor Roll, reflecting their academic excellence. To qualify, players must be juniors or seniors with a GPA of 3.50 or higher. The recognition emphasizes Furman’s commitment to academic and athletic achievement, highlighted by their overall team GPA of 3.2 or above.
By the Numbers- 12 student-athletes earned spots on the IWLCA Academic Honor Roll from Furman.
- Furman was one of 357 schools recognized as IWLCA Academic Honor Squads.
- 1,209 student-athletes from 122 institutions were named to the IWLCA Division I Academic Honor Roll.
While this recognition underscores academic success, it also highlights the pressure on student-athletes to balance rigorous academics with sports commitments. Some may argue that with the growing focus on athletics, achieving such high GPAs amidst demanding schedules can be increasingly challenging.
State of Play- The women’s lacrosse team maintained a remarkable team GPA of 3.2 or higher.
- Recognition by the IWLCA reflects a commitment to both athletics and academics for the 2025-26 year.
The continued academic success of the women's lacrosse team may pave the way for increased recruitment and scholarships at Furman, potentially attracting high-achieving student-athletes. This recognition could also set a precedent for future teams aiming for similar accolades.
Bottom LineFurman University’s accolades from the IWLCA reflect its emphasis on the dual importance of academics and athletics, serving as a model for other institutions. The achievement not only honors the individual students but also enhances the overall reputation of the university's athletic programs.
Read more at Furman University
The summary of the linked article was generated with the assistance of artificial intelligence technology from OpenAI

