| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | KalPa U20 | SM-Liiga-Jr | 0 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2021-22 | KalPa U20 | SM-Liiga-Jr | 36 | 3 | 3 | 6 | 0.167 | 0.0902 | 0.0962 | 0.2476 | 0.2642 |
| 2022-23 | KalPa U20 | SM-Liiga-Jr | 45 | 5 | 14 | 19 | 0.422 | 0.2285 | 0.2339 | 0.6271 | 0.6419 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Yale | D1 | ECAC | JR | 28 | 6 | 7 | 13 | 0.464 |
| 2024-25 | Yale | D1 | ECAC | SO | 25 | 1 | 2 | 3 | 0.120 |
| 2023-24 | Yale | D1 | ECAC | FR | 30 | 5 | 1 | 6 | 0.200 |
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.