| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | Notre Dame Hounds | SJHL | 8 | 0 | 1 | 1 | 0.125 | 0.0381 | 0.0430 | 0.9820 | 1.0728 |
| 2014-15 | Lincoln Stars | USHL | 30 | 2 | 1 | 3 | 0.100 | 0.0615 | 0.0642 | 0.2946 | 0.3074 |
| 2015-16 | Camrose Kodiaks | AJHL | 59 | 15 | 22 | 37 | 0.627 | 0.2081 | 0.2107 | 0.5812 | 0.5884 |
| 2016-17 | — | AJHL | 53 | 15 | 26 | 41 | 0.774 | 0.2567 | 0.2474 | 0.7170 | 0.6910 |
| 2017-18 | Corpus Christi IceRays | NAHL | 58 | 7 | 16 | 23 | 0.397 | 0.1571 | 0.1457 | 0.4164 | 0.3861 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2021-22 | Tufts | D3 | NESCAC | SR | 22 | 8 | 9 | 17 | 0.773 |
| 2020-21 | Tufts | D3 | NESCAC | JR | 0 | 0 | 0 | 0 | 0.000 |
| 2019-20 | Tufts | D1 | — | SO | 24 | 3 | 7 | 10 | 0.417 |
| 2019-20 | Tufts | D3 | NESCAC | SO | 24 | 3 | 7 | 10 | 0.417 |
| 2018-19 | Tufts | D1 | — | FR | 20 | 2 | 5 | 7 | 0.350 |
| 2018-19 | Tufts | D3 | NESCAC | FR | 20 | 2 | 5 | 7 | 0.350 |
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.