| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Pickering Panthers | OJHL | 3 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2015-16 | Carleton Place Canadians | CCHL | 57 | 6 | 10 | 16 | 0.281 | 0.0609 | 0.0656 | 0.2172 | 0.2341 |
| 2016-17 | Carleton Place Canadians | CCHL | 57 | 7 | 22 | 29 | 0.509 | 0.1104 | 0.1132 | 0.3937 | 0.4037 |
| 2017-18 | Carleton Place Canadians | CCHL | 57 | 17 | 41 | 58 | 1.018 | 0.2207 | 0.2149 | 0.7872 | 0.7666 |
| 2023-24 | Kalmar HC | Allsvenskan | 51 | 14 | 29 | 43 | 0.843 | 2.1077 | 2.1387 | 7.9099 | 8.0261 |
| 2024-25 | IF Björklöven | Allsvenskan | 49 | 12 | 16 | 28 | 0.571 | 1.4285 | 1.3622 | 5.3608 | 5.1119 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Arizona State | D1 | NCHC | — | 35 | 4 | 11 | 15 | 0.429 |
| 2020-21 | Bowling Green | D1 | WCHA | JR | 31 | 5 | 10 | 15 | 0.484 |
| 2019-20 | Bowling Green | D1 | WCHA | SO | 38 | 3 | 10 | 13 | 0.342 |
| 2018-19 | Bowling Green | D1 | WCHA | FR | 34 | 4 | 7 | 11 | 0.324 |
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.