| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2016-17 | Texas Jr. Brahmas | NA3HL | 47 | 5 | 5 | 10 | 0.213 | 0.0267 | 0.0282 | 0.0672 | 0.0710 |
| 2017-18 | Rochester Monarchs | USPHL-Premier | 29 | 5 | 12 | 17 | 0.586 | 0.0767 | 0.0776 | 0.1990 | 0.2014 |
| 2018-19 | Vermont Lumberjacks | EHL | 39 | 5 | 12 | 17 | 0.436 | 0.1007 | 0.0986 | 0.2133 | 0.2089 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2022-23 | SUNY Morrisville | D3 | SUNYAC | — | 24 | 1 | 8 | 9 | 0.375 |
| 2021-22 | SUNY Morrisville | D3 | SUNYAC | — | 25 | 2 | 9 | 11 | 0.440 |
| 2019-20 | SUNY Morrisville | D1 | SUNYAC | FR | 25 | 4 | 9 | 13 | 0.520 |
| 2019-20 | SUNY Morrisville | D3 | SUNYAC | — | 25 | 4 | 9 | 13 | 0.520 |
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.