icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
Minnesota Wild
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2018-19 | — | NCDC | 3 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2020-21 | — | USHL | 3 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2021-22 | — | USHL | 59 | 1 | 8 | 9 | 0.152 | 0.0937 | 0.0919 | 0.4493 | 0.4406 |
| 2022-23 | — | USHL | 58 | 6 | 19 | 25 | 0.431 | 0.2649 | 0.2460 | 1.2698 | 1.1792 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Long Island Univ. | D1 | AHA | JR | 31 | 4 | 9 | 13 | 0.419 |
| 2024-25 | Quinnipiac | D1 | ECAC | — | 24 | 0 | 2 | 2 | 0.083 |
| 2023-24 | North Dakota | D1 | NCHC | — | 19 | 0 | 1 | 1 | 0.053 |
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.