| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | New York Bobcats | EHL | 9 | 1 | 5 | 6 | 0.667 | 0.1540 | 0.1676 | 0.3262 | 0.3550 |
| 2014-15 | Battlefords North Stars | SJHL | 36 | 3 | 5 | 8 | 0.222 | 0.0569 | 0.0587 | 0.1675 | 0.1727 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Hamline | D3 | MIAC | — | 23 | 5 | 1 | 6 | 0.261 |
| 2020-21 | St. Thomas | D3 | CCHA | — | 4 | 4 | 0 | 4 | 1.000 |
| 2019-20 | Hamline | D1 | MIAC | FR | 24 | 11 | 12 | 23 | 0.958 |
| 2019-20 | Hamline | D3 | MIAC | — | 24 | 11 | 12 | 23 | 0.958 |
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.