No junior season data found for this player.
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Minnesota | D1 | WCHA-W | GR | 31 | 40 | 26 | 66 | 2.129 |
| 2024-25 | Minnesota | D1 | WCHA-W | SR | 42 | 33 | 32 | 65 | 1.548 |
| 2023-24 | Minnesota | D1 | WCHA-W | JR | 39 | 33 | 29 | 62 | 1.590 |
| 2022-23 | Minnesota | D1 | WCHA-W | SO | 39 | 29 | 21 | 50 | 1.282 |
| 2021-22 | Minnesota | D1 | WCHA-W | — | 0 | 0 | 0 | 0 | 0.000 |
| 2020-21 | Minnesota | D1 | WCHA-W | — | 20 | 8 | 10 | 18 | 0.900 |
How to read this: NCAAe and D3e factors convert a player's junior PPG into expected NCAA scoring at the D1 or D3 level. Harder conferences → lower projected PPG for the same player. A strong junior player (e.g. USHL 0.90 PPG) will project much higher in NESCAC than Big Ten because the D3 scoring environment is lower-difficulty.
Strength factor: conferences above 1.0 are harder than average; below 1.0 are easier. The formula is: Base NCAAe PPG ÷ Conference Strength = Projected PPG.