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 | Amarillo Bulls | NAHL | 10 | 1 | 0 | 1 | 0.100 | 0.0371 | 0.0365 | 0.1059 | 0.1042 |
| 2013-14 | Mason City Toros | NA3HL | 44 | 55 | 58 | 113 | 2.568 | 0.3095 | 0.2856 | 0.8113 | 0.7487 |
| 2018-19 | Dinamo Riga | KHL | 33 | 4 | 1 | 5 | 0.151 | — | — | — | — |
| 2019-20 | Dinamo Riga | KHL | 36 | 1 | 3 | 4 | 0.111 | — | — | — | — |
| 2021-22 | HC Vita Hästen | Allsvenskan | 33 | 21 | 15 | 36 | 1.091 | — | — | — | — |
| 2022-23 | Örebro HK | SHL | 19 | 1 | 0 | 1 | 0.053 | — | — | — | — |
| 2023-24 | Nybro Vikings IF | Allsvenskan | 45 | 13 | 20 | 33 | 0.733 | — | — | — | — |
| 2024-25 | Eispiraten Crimmitschau | DEL2 | 21 | 9 | 8 | 17 | 0.809 | — | — | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2017-18 | Aurora | D3 | NCHA | SR | 18 | 5 | 12 | 17 | 0.944 |
| 2016-17 | Aurora | D3 | NCHA | JR | 17 | 8 | 4 | 12 | 0.706 |
| 2015-16 | Aurora | D3 | NCHA | SO | 21 | 4 | 10 | 14 | 0.667 |
| 2014-15 | Aurora | D3 | NCHA | FR | 17 | 7 | 10 | 17 | 1.000 |
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.