icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2014-15 | Brooks Bandits | AJHL | 47 | 1 | 13 | 14 | 0.298 | 0.0999 | 0.1063 | 0.2757 | 0.2935 |
| 2015-16 | Dauphin Kings | MJHL | 42 | 5 | 8 | 13 | 0.309 | 0.0596 | 0.0611 | 0.1952 | 0.2000 |
| 2016-17 | Hawkesbury Hawks | CCHL | 41 | 5 | 9 | 14 | 0.342 | 0.0741 | 0.0715 | 0.2642 | 0.2550 |
| 2017-18 | — | BCHL | 12 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Cortland | D1 | — | SO | 25 | 0 | 2 | 2 | 0.080 |
| 2019-20 | SUNY Cortland | D3 | SUNYAC | SO | 25 | 0 | 2 | 2 | 0.080 |
| 2018-19 | Cortland | D1 | — | FR | 17 | 1 | 3 | 4 | 0.235 |
| 2018-19 | SUNY Cortland | D3 | SUNYAC | FR | 17 | 1 | 3 | 4 | 0.235 |
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.