| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Haliburton County Huskies | OJHL | 5 | 0 | 1 | 1 | 0.200 | 0.0559 | 0.0627 | 0.1380 | 0.1549 |
| 2016-17 | Haliburton County Huskies | OJHL | 49 | 6 | 11 | 17 | 0.347 | 0.0969 | 0.1044 | 0.2394 | 0.2579 |
| 2017-18 | Haliburton County Huskies | OJHL | 54 | 20 | 21 | 41 | 0.759 | 0.2121 | 0.2183 | 0.5240 | 0.5393 |
| 2018-19 | Haliburton County Huskies | OJHL | 54 | 15 | 26 | 41 | 0.759 | 0.2121 | 0.2079 | 0.5240 | 0.5137 |
| 2019-20 | Corpus Christi IceRays | NAHL | 31 | 10 | 7 | 17 | 0.548 | 0.2036 | 0.2036 | 0.5806 | 0.5806 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2023-24 | SUNY Oswego | D3 | SUNYAC | JR | 26 | 22 | 20 | 42 | 1.615 |
| 2022-23 | SUNY Oswego | D3 | SUNYAC | SO | 27 | 9 | 18 | 27 | 1.000 |
| 2021-22 | SUNY Oswego | D3 | SUNYAC | FR | 19 | 2 | 11 | 13 | 0.684 |
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.