2009 Lexus IS F vs 2024 Ford F-150 Raptor R
AI Telemetry Verdict:In this head-to-head, the 2024 Ford F-150 Raptor Rholds the statistical edge in Performance Index (712). For the technical touge passes of Mount Fuji, the 2009 Lexus IS Fis the superior technical chassis due to its refined lateral G-force profile.
2009 Lexus IS F
Lexus
2024 Ford F-150 Raptor R
Ford"The 2024 Ford F-150 Raptor R dominates the competition with superior Performance Index, making it the clear choice for all-around festival racing."
| 2009 Lexus IS F | Metric | 2024 Ford F-150 Raptor R |
|---|---|---|
| 685 | Performance Index | 712 |
| 6.8 | Speed | 5.8 |
| 6.1 | Handling | 4.8 |
| 6 | Acceleration | 6.4 |
| 5.8 | Launch | 6.8 |
| 6.2 | Braking | 5.2 |
| 3.8 | Offroad | 8.8 |
| 170 | Top Speed (MPH) | 120 |
| 3780 | Weight (lbs) | 6000 |
| RWD | Drivetrain | AWD |
| 45,000 | Price (CR) | 110,000 |
📈 Technical Data Analysis:
Speed & Acceleration Analysis
When it comes to straight-line performance, the 2009 Lexus IS F boasts a speed rating of 6.8, while the 2024 Ford F-150 Raptor R hits 5.8.
The 2009 Lexus IS F has the edge in top-end velocity, reaching 170 MPH compared to the 2024 Ford F-150 Raptor R's 120 MPH.
Handling & Cornering Dynamics
In the tight technical sections of the Mount Fuji passes, handling is everything. The 2009 Lexus IS F features a handling score of 6.1, whereas the 2024 Ford F-150 Raptor R manages 4.8.
The 2009 Lexus IS F offers surgical precision in corners, allowing for later braking and earlier power application.
Launch & Braking Efficiency
Off the line, the 2009 Lexus IS F uses its 5.8 launch rating to grip and go, while the 2024 Ford F-150 Raptor R relies on its 6.8 rating.
Braking from high speeds is equally critical; the 2009 Lexus IS F stops with a score of 6.2, while the 2024 Ford F-150 Raptor R records 5.2.
🏁 Race Scenario Breakdown
Higher top speed rating allows for sustained high-velocity overtaking.
Superior braking and handling allow for more aggressive entry and exit speeds.
Suspension travel and tire compound optimization for loose surfaces.