Three Montana Legends to Enter Grizzly Sports Hall of Fame in 2026
The University of Montana has announced the Grizzly Sports Hall of Fame class of 2026, inducting three distinguished figures: basketball standout Will Cherry, decorated track athlete Loni Perkins-Judisch, and long-serving coach Kris Nord. Cherry, a two-time All-American and all-time steals leader, contributed to multiple championships, including three NCAA Tournament appearances. Perkins-Judisch holds records for the most Big Sky titles in track and field, while Nord has a legacy of coaching excellence in tennis and golf at Montana for over four decades. The induction ceremony is slated for September 11, coinciding with a football game against Utah Tech.
By the Numbers- Will Cherry ranks 12th in all-time scoring at Montana with 1,484 points.
- Loni Perkins-Judisch earned 12 Big Sky Championship titles, the most in Grizzly history.
- Kris Nord coached at the University of Montana for 42 years, impacting both tennis and golf programs.
- 87 inductees now form the Grizzly Sports Hall of Fame.
- The Hall was established in 1993 to honor significant contributions to Grizzly Athletics.
- The induction banquet will celebrate achievements and foster community connection among alumni.
The induction ceremony will highlight the legacy of these Grizzly legends, potentially inspiring future athletes. Anticipation builds for additional details about the banquet and how fans can participate. The event also serves as a reminder of the importance of recognizing athletic excellence within the Montana community.
Bottom LineInducting Cherry, Perkins-Judisch, and Nord underlines the University of Montana's commitment to honoring past athletic excellence and fostering a vibrant sports culture. This event not only celebrates individual achievements but strengthens ties within the university and the wider community.
Read more at University of Montana Athletics
The summary of the linked article was generated with the assistance of artificial intelligence technology from OpenAI

