| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015-16 | Chicago Steel | USHL | 44 | 4 | 11 | 15 | 0.341 | 0.2011 | 0.2034 | 1.0239 | 1.0355 |
| 2021-22 | Dinamo Riga | KHL | 34 | 0 | 2 | 2 | 0.059 | 0.1470 | 0.1669 | 0.8102 | 0.9197 |
| 2023-24 | Brynäs IF | Allsvenskan | 49 | 0 | 13 | 13 | 0.265 | 0.6632 | 0.6388 | 2.4890 | 2.3974 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Quinnipiac | D1 | ECAC | — | 34 | 4 | 14 | 18 | 0.529 |
| 2018-19 | Quinnipiac | D1 | ECAC | — | 38 | 2 | 18 | 20 | 0.526 |
| 2017-18 | Quinnipiac | D1 | ECAC | — | 38 | 3 | 10 | 13 | 0.342 |
| 2016-17 | Quinnipiac | D1 | ECAC | — | 38 | 5 | 10 | 15 | 0.395 |
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.