| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Collingwood Blues | OJHL | 35 | 0 | 4 | 4 | 0.114 | 0.0280 | 0.0292 | 0.0787 | 0.0822 |
| 2015-16 | Collingwood Blues | OJHL | 47 | 2 | 19 | 21 | 0.447 | 0.1095 | 0.1083 | 0.3076 | 0.3042 |
| 2016-17 | Collingwood Blues | OJHL | 54 | 10 | 36 | 46 | 0.852 | 0.2088 | 0.1971 | 0.5865 | 0.5538 |
| 2017-18 | Collingwood Blues | OJHL | 51 | 6 | 28 | 34 | 0.667 | 0.1634 | 0.1464 | 0.4590 | 0.4113 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Skidmore | D3 | SUNYAC | SR | 22 | 6 | 12 | 18 | 0.818 |
| 2020-21 | Skidmore | D3 | SUNYAC | JR | 0 | 0 | 0 | 0 | 0.000 |
| 2019-20 | Skidmore | D1 | SUNYAC | SO | 26 | 6 | 11 | 17 | 0.654 |
| 2019-20 | Skidmore | D3 | SUNYAC | SO | 26 | 6 | 11 | 17 | 0.654 |
| 2018-19 | Skidmore | D1 | SUNYAC | FR | 26 | 3 | 10 | 13 | 0.500 |
| 2018-19 | Skidmore | D3 | SUNYAC | FR | 26 | 3 | 10 | 13 | 0.500 |
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.