| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2020-21 | HIFK | Liiga | 30 | 11 | 10 | 21 | 0.700 | 1.7500 | 1.7500 | — | — |
| 2023-24 | HV71 | SHL | 50 | 16 | 18 | 34 | 0.680 | 1.7000 | 1.7471 | — | — |
| 2024-25 | HV71 | SHL | 49 | 19 | 26 | 45 | 0.918 | 2.2960 | 2.2252 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Denver | D1 | NCHC | SO | 40 | 23 | 29 | 52 | 1.300 |
| 2016-17 | Denver | D1 | NCHC | FR | 37 | 22 | 21 | 43 | 1.162 |
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.