icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2012-13 | — | MJHL | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2013-14 | — | MJHL | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2014-15 | — | MJHL | 57 | 3 | 7 | 10 | 0.175 | 0.0338 | 0.0358 | 0.1106 | 0.1171 |
| 2015-16 | — | MJHL | 59 | 6 | 34 | 40 | 0.678 | 0.1305 | 0.1313 | 0.4275 | 0.4301 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Bemidji State | D1 | WCHA | SO | 36 | 4 | 15 | 19 | 0.528 |
| 2016-17 | Bemidji State | D1 | WCHA | FR | 41 | 3 | 14 | 17 | 0.415 |
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.