| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2005-06 | Calgary Royals | AJHL | 56 | 19 | 37 | 56 | 1.000 | 0.3354 | 0.3587 | 0.9254 | 0.9896 |
| 2007-08 | Calgary Hitmen | WHL | 72 | 18 | 52 | 70 | 0.972 | 0.4730 | 0.4472 | 2.3855 | 2.2556 |
| 2015-16 | Malmö Redhawks | SHL | 29 | 3 | 12 | 15 | 0.517 | 1.2930 | 1.1835 | 6.7487 | 6.1774 |
| 2016-17 | — | KHL | 16 | 4 | 3 | 7 | 0.438 | 1.0938 | 1.0158 | 6.0282 | 5.5984 |
| 2017-18 | Dinamo Riga | KHL | 11 | 0 | 6 | 6 | 0.545 | 1.3638 | 1.2083 | 7.5163 | 6.6591 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2006-07 | Dartmouth | D1 | ECAC | FR | 33 | 14 | 17 | 31 | 0.939 |
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.