icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Kärpät U20 | SM-Liiga-Jr | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | Kärpät U20 | SM-Liiga-Jr | 39 | 6 | 13 | 19 | 0.487 | 0.2637 | 0.2850 | 0.7236 | 0.7821 |
| 2023-24 | Kärpät U20 | SM-Liiga-Jr | 46 | 22 | 35 | 57 | 1.239 | 0.6707 | 0.6891 | 1.8403 | 1.8908 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Michigan Tech | D1 | CCHA | SO | 37 | 8 | 14 | 22 | 0.595 |
| 2024-25 | Michigan Tech | D1 | CCHA | — | 36 | 12 | 11 | 23 | 0.639 |
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.