| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | Kirkland Lake Gold Miners | NOJHL | 0 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2021-22 | Kirkland Lake Gold Miners | NOJHL | 45 | 1 | 9 | 10 | 0.222 | 0.0371 | 0.0379 | 0.0925 | 0.0945 |
| 2022-23 | Iroquois Falls Storm | NOJHL | 20 | 1 | 2 | 3 | 0.150 | 0.0250 | 0.0245 | 0.0624 | 0.0610 |
| 2023-24 | New England Wolves | EHL | 14 | 1 | 1 | 2 | 0.143 | 0.0330 | 0.0320 | 0.0699 | 0.0678 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Anna Maria | D3 | MASCAC | FR | 19 | 0 | 0 | 0 | 0.000 |
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.