| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Chippewa Steel | NAHL | 59 | 16 | 18 | 34 | 0.576 | 0.2283 | 0.2295 | 0.6051 | 0.6084 |
| 2022-23 | Chippewa Steel | NAHL | 53 | 20 | 21 | 41 | 0.774 | 0.3065 | 0.2931 | 0.8122 | 0.7767 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Stonehill | D1 | AHA | — | 35 | 11 | 4 | 15 | 0.429 |
| 2024-25 | Stonehill | D1 | AHA | SR | 29 | 5 | 6 | 11 | 0.379 |
| 2023-24 | Stonehill | D1 | AHA | JR | 22 | 3 | 4 | 7 | 0.318 |
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.