| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | — | NAHL | 9 | 0 | 1 | 1 | 0.111 | 0.0395 | 0.0416 | 0.1172 | 0.1234 |
| 2022-23 | Olds Grizzlys | AJHL | 23 | 3 | 4 | 7 | 0.304 | 0.1021 | 0.1002 | 0.2807 | 0.2754 |
| 2023-24 | Notre Dame Hounds | SJHL | 55 | 14 | 18 | 32 | 0.582 | 0.1491 | 0.1413 | 0.4377 | 0.4148 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Lawrence | D3 | NCHA | — | 2 | 0 | 1 | 1 | 0.500 |
| 2024-25 | Lawrence | D3 | NCHA | — | 15 | 3 | 1 | 4 | 0.267 |
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.