| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Medicine Hat Tigers | WHL | 16 | 4 | 14 | 18 | 1.125 | 0.5473 | 0.6454 | 2.7566 | 3.2509 |
| 2023-24 | Medicine Hat Tigers | WHL | 61 | 34 | 63 | 97 | 1.590 | 0.7736 | 0.8742 | 3.8965 | 4.4033 |
| 2024-25 | Medicine Hat Tigers | WHL | 56 | 41 | 88 | 129 | 2.304 | 1.1207 | 1.2066 | 5.6445 | 6.0771 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Penn State | D1 | BigTen | FR | 35 | 15 | 36 | 51 | 1.457 |
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.