Age: 35
| Season | Age | Series | Starts | Wins | ASP | AFP | eARP | ASP-FP | eGR-LR | PFAE | Avg. PFAE | Laps Led | Laps Run | %LL | %LC |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2015 | 26 | CARS Pro | 3 | 0 | 25.00 | 28.33 | 25.44 | -3.33 | -0.68 | -23.88 | -7.958 | 0 | 114 | 0.00 | 26.82 |
| 2017 | 28 | Trucks, CARS Pro | 3 | 0 | 24.00 | 18.00 | 20.53 | 6.00 | 0.23 | 8.36 | 2.786 | 0 | 366 | 0.00 | 95.31 |
| 2018 | 29 | Trucks | 9 | 0 | 24.11 | 21.33 | 23.02 | 2.78 | 0.08 | -1.36 | -0.151 | 0 | 1221 | 0.00 | 94.14 |
| 2019 | 30 | Xfinity, Trucks | 2 | 0 | 26.50 | 29.00 | 30.08 | -2.50 | -0.34 | -10.30 | -5.152 | 0 | 208 | 0.00 | 66.88 |
| 2020 | 31 | Xfinity, Trucks | 9 | 0 | 27.67 | 22.67 | 24.94 | 5.00 | 0.14 | 8.50 | 0.945 | 0 | 1145 | 0.00 | 98.62 |
| 2021 | 32 | Xfinity | 1 | 0 | 23.00 | 25.00 | 24.00 | -2.00 | -0.12 | -2.47 | -2.470 | 0 | 105 | 0.00 | 86.07 |
| 2023 | 34 | ARCA | 2 | 0 | 6.00 | 17.00 | 11.50 | -11.00 | -0.32 | -17.42 | -8.711 | 0 | 160 | 0.00 | 100.00 |
| Owner | Car | Season | Series | Starts | Wins | Average Start | Average Finish | Avg. PFAE |
| Chad Finley | 2L | 2015 | CARS Pro | 3 | 0 | 25.00 | 28.33 | -7.958 |
| Jay Robinson | 49 | 2017 | Trucks | 2 | 0 | 21.50 | 18.00 | 0.879 |
| None | 2L | 2017 | CARS Pro | 1 | 0 | 29.00 | 18.00 | 6.600 |
| Jay Robinson | 15 | 2018 | Trucks | 7 | 0 | 24.71 | 21.57 | 0.019 |
| Josh Reaume | 33 | 2018 | Trucks | 2 | 0 | 22.00 | 20.50 | -0.745 |
| Rick Ware | 17 | 2019 | Xfinity | 1 | 0 | 33.00 | 28.00 | 1.447 |
| Jeff Finley | 42 | 2019 | Trucks | 1 | 0 | 20.00 | 30.00 | -11.750 |
| Johnny Davis | 15 | 2020 | Xfinity | 4 | 0 | 21.50 | 20.50 | 0.172 |
| Logan Puckett | 97 | 2020 | Trucks | 5 | 0 | 32.60 | 24.40 | 1.563 |
| Shigeaki Hattori | 61 | 2021 | Xfinity | 1 | 0 | 23.00 | 25.00 | -2.470 |
| Bruce Cook | 42 | 2023 | ARCA | 2 | 0 | 6.00 | 17.00 | -8.711 |
If you see any numbers that are odd, they probably are, especially if it appears a series if missing a lot of laps led or a driver has the same start as they do finish (in aggregate). We have to do a bit of data cleanup to make things useful, and as a result some missing data is covered up with defaults that hopefully won't pervert the results too much.