| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Kirkland Lake Gold Miners | NOJHL | 22 | 5 | 7 | 12 | 0.545 | 0.0777 | 0.0772 | 0.2271 | 0.2256 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Lake Forest | D3 | NCHA | SR | 8 | 0 | 1 | 1 | 0.125 |
| 2020-21 | Lake Forest | D1 | NCHA | JR | 3 | 0 | 0 | 0 | 0.000 |
| 2020-21 | Lake Forest | D3 | NCHA | JR | 3 | 0 | 0 | 0 | 0.000 |
| 2019-20 | Lake Forest | D1 | NCHA | SO | 13 | 1 | 1 | 2 | 0.154 |
| 2019-20 | Lake Forest | D3 | NCHA | SO | 13 | 1 | 1 | 2 | 0.154 |
| 2018-19 | Lake Forest | D1 | NCHA | FR | 2 | 0 | 0 | 0 | 0.000 |
| 2018-19 | Lake Forest | D3 | NCHA | FR | 2 | 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.