Alex Guenette

Age: 28

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Season Age Series Starts Wins T5 T10 ASP AFP eARP ASP-FP eGR-LR PFAE Avg. PFAE Succ% Laps Led Laps Run %LL %LC
2013 16 Trucks, Pinty's 13 0 2 5 11.23 14.38 10.67 -3.15 -0.13 -34.99 -2.692 38.5 11 2127 0.52 92.80
2014 17 ARCA, Trucks, Pinty's 7 0 2 5 11.14 11.71 8.13 -0.57 0.12 8.29 1.185 71.4 15 938 1.60 80.58
2016 19 Xfinity, CARS Pro 5 0 0 0 28.80 26.20 24.77 2.60 0.05 1.75 0.349 60.0 0 490 0.00 81.40
2019 22 ACT, Pinty's 4 0 0 2 11.75 12.50 10.61 -0.75 0.00 -4.04 -1.010 75.0 0 408 0.00 81.60
2021 24 Pinty's 10 0 2 7 10.20 9.30 8.81 0.90 0.10 4.33 0.433 80.0 0 889 0.00 87.93
2022 25 Pinty's 6 2 3 5 10.67 7.17 7.50 3.50 0.41 15.39 2.565 83.3 12 278 4.32 87.15
2023 26 Xfinity, Pinty's 19 0 3 12 10.05 12.05 8.13 -2.00 -0.10 -16.37 -0.861 57.9 37 2382 1.55 92.00
2024 27 Pinty's 6 0 4 4 7.83 8.33 7.99 -0.50 0.18 1.46 0.244 66.7 0 888 0.00 91.26
Owner Car Season Series Starts Wins Average Start Average Finish Avg. PFAE
Mario Gosselin 39 2013 Trucks 1 0 14.00 25.00 -10.191
Dave Jacombs 39 2013 Pinty's 12 0 11.00 13.50 -2.067
Mario Gosselin 17 2014 ARCA 1 0 15.00 20.00 -4.165
Mario Gosselin 74 2014 Trucks 1 0 24.00 36.00 -13.516
Steve Turner 32 2014 Trucks 1 0 12.00 9.00 5.484
Jacques Guenette 39 2014 Pinty's 4 0 6.75 4.25 5.122
Mario Gosselin 90 2016 Xfinity 1 0 28.00 26.00 2.053
Victor Obaika 97 2016 Xfinity 3 0 34.00 29.67 0.465
David Gilliland 98 2016 CARS Pro 1 0 14.00 16.00 -1.700
None 48QC 2019 ACT 1 0 7.00 25.00 -15.310
Jacques Guenette 39 2019 Pinty's 1 0 21.00 11.00 5.800
Scott Steckly 18 2019 Pinty's 2 0 9.50 7.00 2.735
Rick Ware 52 2021 Pinty's 10 0 10.20 9.30 0.433
Dave Jacombs 39 2022 Pinty's 6 2 10.67 7.17 2.565
Emerling-Gase Motorsports 35 2023 Xfinity 1 0 37.00 33.00 -6.527
Mario Gosselin 36, 91 2023 Xfinity 2 0 24.50 26.50 -3.898
Ed Hakonson 3 2023 Pinty's 16 0 6.56 8.94 -0.128
None 39 2024 Pinty's 6 0 7.83 8.33 0.244

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.