icepath.io · Hockey Analytics
icepath.io · Hockey Analytics
Florida Panthers
| Season | Team | League | GP | G | A | Pts | PPG | NCAAe-PPG | Age-Adj | D3e-PPG | Age-Adj |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2011-12 | Lincoln Stars | USHL | 1 | 0 | 0 | 0 | 0.000 | — | — | — | — |
| 2012-13 | U.S. National U17 Team | NTDP-U18 | 56 | 13 | 18 | 31 | 0.554 | 0.4115 | 0.4258 | 2.0759 | 2.1480 |
| 2013-14 | Tri-City Storm | USHL | 57 | 17 | 19 | 36 | 0.632 | 0.3726 | 0.3950 | 1.8952 | 2.0092 |
| 2014-15 | Tri-City Storm | USHL | 59 | 35 | 20 | 55 | 0.932 | 0.5499 | 0.5560 | 2.7973 | 2.8281 |
| 2022-23 | Bietigheim Steelers | DEL | 44 | 16 | 11 | 27 | 0.614 | 1.5340 | 1.7068 | 5.2011 | 5.7869 |
| 2023-24 | Grizzlys Wolfsburg | DEL | 50 | 21 | 12 | 33 | 0.660 | 1.6500 | 1.7512 | 5.5944 | 5.9376 |
| 2024-25 | Shanghai Dragons | KHL | 6 | 0 | 1 | 1 | 0.167 | 0.4167 | 0.3844 | 2.2965 | 2.1187 |
| Season | School | Div | Conference | Year | GP | G | A | Pts | PPG |
|---|---|---|---|---|---|---|---|---|---|
| 2019-20 | Colorado College | D1 | NCHC | — | 34 | 23 | 8 | 31 | 0.912 |
| 2018-19 | Colorado College | D1 | NCHC | — | 20 | 6 | 13 | 19 | 0.950 |
| 2016-17 | North Dakota | D1 | NCHC | SO | 30 | 1 | 9 | 10 | 0.333 |
| 2015-16 | North Dakota | D1 | NCHC | FR | 32 | 5 | 4 | 9 | 0.281 |
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.