| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Kindersley Klippers | SJHL | 3 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2021-22 | Northern Manitoba Blizzard | MJHL | 52 | 7 | 11 | 18 | 0.346 | 0.0666 | 0.0612 | 0.2181 | 0.2004 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | University of Mary | ACHA_D1 | — | — | 38 | 8 | 25 | 33 | 0.868 |
| 2024-25 | Concordia | D3 | MIAC | GR | 2 | 0 | 0 | 0 | 0.000 |
| 2024-25 | Concordia (WI) | D3 | NCHA | JR | 2 | 0 | 0 | 0 | 0.000 |
| 2024-25 | University of Mary | ACHA_D1 | — | — | 38 | 8 | 25 | 33 | 0.868 |
| 2023-24 | Concordia | D3 | MIAC | SR | 7 | 0 | 1 | 1 | 0.143 |
| 2023-24 | Concordia (WI) | D3 | NCHA | SO | 7 | 0 | 1 | 1 | 0.143 |
| 2023-24 | University of Mary | ACHA_D1 | — | — | 38 | 8 | 25 | 33 | 0.868 |
| 2022-23 | Concordia | D3 | MIAC | JR | 12 | 0 | 0 | 0 | 0.000 |
| 2022-23 | Concordia (WI) | D3 | NCHA | FR | 12 | 0 | 0 | 0 | 0.000 |
| 2022-23 | University of Mary | ACHA_D1 | — | — | 38 | 8 | 25 | 33 | 0.868 |
| 2021-22 | University of Mary | ACHA_D1 | — | — | 38 | 8 | 25 | 33 | 0.868 |
| 2020-21 | University of Mary | ACHA_D1 | — | — | 38 | 8 | 25 | 33 | 0.868 |
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.