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Marco

Marco is a rising force within Cargo Champs. In his rookie season, he's put himself on a powerhouse trajectory with top-tier throws. His work shows clear inflection points: faster MPP, higher BPM, and a speed bonus curve that signals extraordinary long-term potential.

Not yet a champion, Marco's throws push other top-contenders to new heights. He's a clear contender on the climb who uses raw strength, sharpened pace, and momentum to turn raw skill into legend.

Throwbriquet Seasons Active
El Mazo —
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
- -

154436

207715

17 166335

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.
ℹ️ Click to Learn More

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.

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