| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Thayer Academy | USHS-W | 24 | 22 | 5 | 27 | 1.125 | 0.3275 | 0.3474 | — | — |
| 2022-23 | Thayer Academy | USHS-W | 25 | 26 | 16 | 42 | 1.680 | 0.4890 | 0.4882 | — | — |
| 2023-24 | Thayer Academy | USHS-W | 24 | 29 | 13 | 42 | 1.750 | 0.5094 | 0.4778 | — | — |
| 2024-25 | Thayer Academy | USHS-W | 26 | 36 | 17 | 53 | 2.038 | 0.5934 | 0.5385 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2025-26 | Harvard | D1 | ECAC-W | — | 34 | 11 | 5 | 16 | 0.471 |
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.