| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Collingwood Blues | OJHL | 13 | 1 | 0 | 1 | 0.077 | 0.0188 | 0.0198 | 0.0529 | 0.0557 |
| 2015-16 | Wellington Dukes | OJHL | 10 | 2 | 2 | 4 | 0.400 | 0.0980 | 0.0978 | 0.2754 | 0.2748 |
| 2016-17 | Collingwood Blues | OJHL | 51 | 19 | 17 | 36 | 0.706 | 0.1730 | 0.1649 | 0.4860 | 0.4632 |
| 2017-18 | Collingwood Blues | OJHL | 52 | 16 | 25 | 41 | 0.788 | 0.1933 | 0.1749 | 0.5429 | 0.4913 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | SUNY Cortland | D3 | SUNYAC | SR | 6 | 2 | 1 | 3 | 0.500 |
| 2019-20 | Cortland | D1 | — | SO | 6 | 1 | 0 | 1 | 0.167 |
| 2019-20 | SUNY Cortland | D3 | SUNYAC | SO | 6 | 1 | 0 | 1 | 0.167 |
| 2018-19 | Cortland | D1 | — | FR | 19 | 1 | 3 | 4 | 0.210 |
| 2018-19 | SUNY Cortland | D3 | SUNYAC | FR | 19 | 1 | 3 | 4 | 0.210 |
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.