| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | — | BCHL | 41 | 6 | 8 | 14 | 0.342 | 0.1316 | 0.1422 | 0.4970 | 0.5369 |
| 2012-13 | Victoria Grizzlies | BCHL | 52 | 17 | 18 | 35 | 0.673 | 0.2593 | 0.2678 | 0.9796 | 1.0118 |
| 2013-14 | Cowichan Valley Capitals | BCHL | 58 | 21 | 38 | 59 | 1.017 | 0.3919 | 0.3867 | 1.4803 | 1.4606 |
| 2021-22 | — | Allsvenskan | 40 | 17 | 27 | 44 | 1.100 | 2.7500 | 2.4788 | 10.3201 | 9.3023 |
| 2022-23 | IK Oskarshamn | SHL | 50 | 9 | 6 | 15 | 0.300 | 0.7500 | 0.7053 | 3.9146 | 3.6814 |
| 2023-24 | IF Björklöven | Allsvenskan | 41 | 20 | 23 | 43 | 1.049 | 2.6220 | 2.1454 | 9.8397 | 8.0512 |
| 2024-25 | ERC Ingolstadt | DEL | 52 | 14 | 32 | 46 | 0.885 | 2.2115 | 2.0285 | 7.4998 | 6.8792 |
| 2025-26 | ERC Ingolstadt | DEL | 42 | 17 | 21 | 38 | 0.905 | 2.2620 | 2.1807 | 7.6711 | 7.3954 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | RIT | D1 | AHA | SR | 37 | 13 | 26 | 39 | 1.054 |
| 2016-17 | RIT | D1 | AHA | JR | 37 | 13 | 11 | 24 | 0.649 |
| 2015-16 | RIT | D1 | AHA | SO | 39 | 15 | 17 | 32 | 0.821 |
| 2014-15 | RIT | D1 | AHA | FR | 36 | 4 | 6 | 10 | 0.278 |
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.