icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2002-03 | Navan Grads | CCHL | 8 | 2 | 3 | 5 | 0.625 | 0.1996 | 0.2239 | 0.4838 | 0.5428 |
| 2003-04 | Navan Grads | CCHL | 51 | 31 | 32 | 63 | 1.235 | 0.3944 | 0.4228 | 0.9562 | 1.0250 |
| 2005-06 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2095 | — | — |
| 2006-07 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2095 | — | — |
| 2007-08 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2095 | — | — |
| 2008-09 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2094 | — | — |
| 2009-10 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2095 | — | — |
| 2010-11 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2095 | — | — |
| 2011-12 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2095 | — | — |
| 2012-13 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2094 | — | — |
| 2015-16 | Augsburger Panther | DEL | 52 | 20 | 29 | 49 | 0.942 | 1.0305 | 0.9913 | — | — |
| 2016-17 | EHC München | DEL | 51 | 11 | 25 | 36 | 0.706 | 0.7720 | 0.7278 | — | — |
| 2017-18 | EHC München | DEL | 46 | 11 | 12 | 23 | 0.500 | 0.5468 | 0.5059 | — | — |
| 2018-19 | Iserlohn Roosters | DEL | 52 | 22 | 34 | 56 | 1.077 | 1.1777 | 0.9827 | — | — |
| 2019-20 | Kölner Haie | DEL | 52 | 13 | 16 | 29 | 0.558 | 0.6099 | 0.6099 | — | — |
| 2020-21 | Kölner Haie | DEL | 37 | 16 | 22 | 38 | 1.027 | 1.1231 | 1.1231 | — | — |
| 2021-22 | Kölner Haie | DEL | 53 | 15 | 27 | 42 | 0.792 | 0.8667 | 0.5677 | — | — |
| 2022-23 | Kölner Haie | DEL | 54 | 11 | 27 | 38 | 0.704 | 0.7696 | 0.4815 | — | — |
| 2023-24 | Krefeld Pinguine | DEL2 | 30 | 10 | 13 | 23 | 0.767 | 0.3308 | 0.1654 | — | — |
| 2024-25 | Krefeld Pinguine | DEL2 | 50 | 20 | 30 | 50 | 1.000 | 0.4314 | 0.2157 | — | — |
| 2025-26 | Krefeld Pinguine | DEL2 | 44 | 15 | 21 | 36 | 0.818 | 0.3530 | 0.2095 | — | — |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2006-07 | Bowling Green | D1 | — | JR | 38 | 11 | 22 | 33 | 0.868 |
| 2005-06 | Bowling Green | D1 | — | SO | 36 | 20 | 28 | 48 | 1.333 |
| 2004-05 | Bowling Green | D1 | — | FR | 36 | 18 | 14 | 32 | 0.889 |
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.