| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2013-14 | Calgary Mustangs | AJHL | 4 | 1 | 0 | 1 | 0.250 | 0.0838 | 0.0912 | 0.2314 | 0.2520 |
| 2014-15 | — | AJHL | 32 | 11 | 8 | 19 | 0.594 | 0.1992 | 0.2063 | 0.5495 | 0.5692 |
| 2015-16 | — | AJHL | 56 | 27 | 15 | 42 | 0.750 | 0.2515 | 0.2488 | 0.6941 | 0.6866 |
| 2016-17 | Flin Flon Bombers | SJHL | 36 | 17 | 9 | 26 | 0.722 | 0.1850 | 0.1763 | 0.5444 | 0.5189 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Marian | D3 | NCHA | — | 5 | 0 | 3 | 3 | 0.600 |
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.