| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Newmarket Hurricanes | OJHL | 2 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2022-23 | Newmarket Hurricanes | OJHL | 52 | 12 | 23 | 35 | 0.673 | 0.1650 | 0.1763 | 0.4607 | 0.4923 |
| 2023-24 | Newmarket Hurricanes | OJHL | 54 | 23 | 37 | 60 | 1.111 | 0.2723 | 0.2769 | 0.7605 | 0.7732 |
| 2024-25 | Austin Bruins | NAHL | 59 | 27 | 51 | 78 | 1.322 | 0.4696 | 0.4676 | 1.3880 | 1.3821 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Middlebury | D3 | NESCAC | — | 27 | 6 | 12 | 18 | 0.667 |
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.