| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | St. Cloud Norsemen | NAHL | 48 | 16 | 30 | 46 | 0.958 | 0.3797 | 0.3921 | 1.0061 | 1.0391 |
| 2023-24 | Des Moines Buccaneers | USHL | 55 | 6 | 9 | 15 | 0.273 | 0.1676 | 0.1575 | 0.8034 | 0.7548 |
| 2024-25 | Des Moines Buccaneers | USHL | 60 | 20 | 25 | 45 | 0.750 | 0.4610 | 0.4096 | 2.2096 | 1.9632 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Dartmouth | D1 | ECAC | FR | 34 | 2 | 9 | 11 | 0.324 |
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.