Josue
Josue’s career may have been brief, but it was one of the most efficient runs in Cargo Champs history. Over the course of a single season, he threw just twenty trucks. But his precision, consistency, and flawless mechanics propelled him all the way to a world championship. Few throwers have ever done so much with so little volume.
Josue didn’t rely on high peaks or volatility. Instead, he delivered the same clean, controlled performance every time he stepped into a trailer. In a sport where most champions build their legacies over dozens of trucks and multiple seasons, Josue did it with surgical efficiency. His BPM curve was steady, his MPP stable, and his throws remarkably disciplined.
Even after his retirement, Josue’s record remains a testament to what can happen when skill, focus, and consistency align perfectly over a compressed timeline. Josue stands as the rare thrower whose legacy is defined not by quantity, but by the unmistakable quality of every single throw.
| Throwbriquet | Seasons Active |
|---|---|
| — | — |
| First Truck | Last Truck |
|---|---|
| — | — |
| Nationality | Home Store |
|---|---|
| 🇺🇸 | Walmart #2031 (Union City, CA, USA) |
| Trucks Thrown | Championships | Podiums | Career Points |
|---|---|---|---|
| — | — | — | — |
| Sub-Hour Throws | Two-Truck Days | Legendary Throws |
|---|---|---|
| - | - | — |
| Record | Metric | Held |
|---|
⭐ + bold dates/seasons indicate a currently-held record.
The following charts track three key performance metrics that measure a thrower's effort, pace, and competitive edge.
Together, these metrics strip away noise like truck size or teammate mix. They measure what’s truly in the thrower’s control.
⭐ indicates a thrower's personal best MPP, BPM, and Speed Bonus.
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The graphs represent the running cumulative average of a thrower's metrics across time and include only trucks where the thrower or throwing team threw 90%+ of the truck.
Trendlines attempt to reflect the behavior of a particular performance metric.
Minutes Per Panel (MPP) uses a LOESS trendline, a locally weighted regression that smooths short-term fluctuations while preserving the natural, nonlinear “learning-curve” shape of skill improvement over time.
Boxes Per Minute (BPM) uses a moving-average trendline, which filters random noise from day-to-day variation and highlights changes in throughput consistency and stamina.
Speed Bonus uses a linear-regression trendline, showing the athlete’s overall direction of improvement relative to normalized truck size and peer averages.
Together these trendlines attempt to balance clarity and realism, revealing long-term progress without distorting the underlying data.