| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | Northwood School | JWHL-U19 | 20 | 14 | 7 | 21 | 1.050 | 0.3492 | 0.3492 | — | — |
| 2023-24 | Northwood School | 19U-AAA-W | 63 | 28 | 28 | 56 | 0.889 | 0.3071 | 0.3071 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | RIT | D1 | CHA-W | SO | 32 | 11 | 10 | 21 | 0.656 |
| 2024-25 | RIT | D1 | CHA-W | FR | 37 | 9 | 17 | 26 | 0.703 |
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.