Cargo Champs uses a competitive framework to gamify freight management. Specifically, the app measures how well throwers and teams clear trailers by focusing on the number of minutes it takes to clear one trailer panel (minutes per panel, or "MPP”).

On average, trucks are only about 15-20% smaller or larger (+/- 100 cases) than one another. Teammate sizes and overall completion times only differ by 15-25%. The net effect of this is that, regardless of any other factor, most trucks are cleared within about 30 minutes of one another.

BPM ("boxes per minute") is a noisy, crude metric simply focused on raw throughput. That is, it tells us how many boxes exit the truck in a unit of time. It tells us very little about load conditions and thrower/team intensity, and because it's highly sensitive to load size, smaller trucks nearly always have higher BPMs.

MPP, on the other hand, is a more sensitive metric that helps measure a thrower's real progress through the truck, regardless of box sizes or load conditions. It tells us how effectively a thrower movs through space and indirectly accounts for clutter, messes, rhythm, flow, and spatial awareness. Focusing on it ensures our scoring system rewards throwers who clear trucks quickly, maintain strong speed throughout, and make steady, meaningful progress no matter what they encounter inside the trailer.

The impact of a thrower or throwing team is paramount. The thrower's efficiency and determination largely dictate how efficiently a team clears a truck. Since truck and team sizes don't have a significant impact on unload times, throwers drive superior results when they take ownership of the process and perform with focus, stamina, efficiency, and precision.

To improve your score, focus on four things:

Embrace challenges, own the truck, throw 100%, make every panel count, and do it all as often as possible. This approach will maximize your score and leaderboard rank and ensure that you stand out as a true Cargo Champ.

We classify truck weight classes based on min/max adjusted sizes (that is, truck size minus the area occupied by pallets).

We calculate thrower scores as follows:

((1/Minutes Per Panel) + ((Adjusted Truck Size/100)*% Thrown) + Teammate Adjustment - Claims Adjustment + Speed Bonus + Boxes Per Minute Adjustment)

This formula ensures that MPP remains the dominant metric, while adjustments for truck size, teammates, claims, relative unload speed, and BPM refine the score based on the difficulty and efficiency of the throw relative to other throws in the dataset.

Here's an example of this in action:

We have a 2,000-piece truck with five pallets. Each pallet occupies 48x40 inches of horizontal space in the 53' trailer (2.97%). Since palletized cargo is stacked vertically and often removed as a unit, we treat these sections as "out of bounds" and exclude them from thrower performance calculations. This ensures fair comparisons by focusing only on the loose boxes that must be thrown by hand.

Five pallets reduce the truck size by 14.85%, giving us an adjusted truck size of 1,703, which is slightly smaller than average (-0.02 vs. the mean). By downscaling the throwable area, we ensure thrower metrics like MPP and BPM reflect only the boxes a thrower actually moves.

Smaller teams can rate limit throwers. Since they increase total potential throughput, larger teams create a greater opportunity for engaged throwers to shine. Our model ensures that, when throwers use larger team sizes as an asset, they are rewarded accordingly. On this day, there were seven teammates working the line, which is slightly below the average team size (-0.05 vs. the mean).

The truck had three claims, which is slightly above average (+0.6 vs. the mean). The truck took one hour and 41 minutes to unload. For longer breaks, we stop the clock. But, if there is an interruption to the unloading process, we reduce unload time by five minutes to compensate for momentum loss. Today, we stopped once to clean up a mess so we decrease the thrower's time by five minutes. This gives us an adjusted completion time of 01:36, slightly faster than average for a truck of this size (+1.11 vs the mean). This figure (+1.11) becomes the truck's "speed bonus": a metric the attempts to standardize throw speed and performance across truck sizes (weight classes). If a thrower is faster than average, the speed bonus increases his or her score. If slower, the speed bonus decreases it.

This thrower threw 100% of the truck, sustained a BPM of 18 (+0.11 vs. the mean), and cleared a panel every 2.53 minutes (about 2% faster than average).

With the values we need, we can now give the thrower a score for this truck:

((1/2.53) + ((1703/100)*100%) + 1.88 - 0.06 + 1.11 + 0.11) = 20.47

We then average this thrower's scores from all the trucks s/he threw to determine his/her place on the leaderboard relative to all the other throwers and their average scores.

Finally, we add one point (or a fraction of a point) to thrower or throwing team's leaderboard score. This "throwing bonus" corresponds with the total percentage of trucks they've thrown during the current season. For example, we'd add two points to a thrower's leaderboard score if he threw 100% of two trucks that season. We'd add .5 points to another thrower's leaderboard score if she threw 50% of a truck that season.

This discourages score parking or leaderboard "camping." The #1 thrower(s) can't sit on past performances forever, and throwers can seize the top spot with one amazing throw. Throwing a truck is like a boxing match: we're focused on peak performance during a single performance. Like knocking out the reigning champ, throwers can win the Cargo Champs title with one dominant throwing experience.

When you enter the truck, it's your time to shine and prove you're the best. And consistent excellence across time will help you defend your title.

In this case, in the current season, the thrower has thrown 25% of one truck, 50% of another truck, and 100% of this truck so we calculate his leaderboard score as follows:

20.47 + (.25 + .5 + 1) = 22.22

This places him in fourth place behind a higher-scoring single truck thrower and two high-scoring, multi-truck throwers.

Opportunities to Throw
Historically, Cargo Champs had a "street ball" culture when it came to throwing opportunities. Worker-athletes asserted their desire to throw. If no one challenged, the thrower got the truck. We saw periodic "rock paper scissors" style negotiations when two throwers wanted the same truck. But, for the most part, thrower will and assertiveness ruled.

This approach has its benefits, but it also exploits an opportunity bias in the Cargo Champs scoring model. The most assertive throwers throw more trucks, and this inevitably lifts their scores. Throwers with high scores might also avoid smaller trucks to protect their scores. This state of affairs creates a reality in which the most assertive throwers throw more, de risk their scores, and competition ultimately suffers.

As a fix, in the middle of the fourth season (Q3 2025), we began using our task randomizer to assign throwers to trucks. This neutralizes the opportunity imbalance of the street ball regime. Throwers get equal access to trucks, and we're able to amplify the performance -- vs. opportunistic -- strengths of Cargo Champs' scoring system.

Tactically, here's how this works: Before throwing begins, load the task randomizer. If the thrower that appears isn't working that day or declines the throw, reload the page or click "Regenerate." Continue this process until a thrower accepts the throw.

Data Fidelity
Data occasionally goes missing due to human or technical reasons. Someone might forget to make a note, for example, or a certain datapoint for a certain truck may not be available in an API or database. Pallet count, teammate presence, claims, and breaks/interruptions are especially prone to this. When one or more of these values are unavailable for a given throw, we simply fill the gap using historical averages.

We nearly always have unload time, but in the rare cases when it's missing, we use the current average unload time for that truck's weight class (eg., 01:11 for a flyweight truck). Truck size, thrower(s), and percent thrown are required values. If this data is unavailable, thrower(s) forfeit the throw, and we will not add it to the database.

This approach gives Cargo Champs enormous scoring flexibility. And it allows us to capitalize on high-quality aggregate data and make scorekeeping simple for worker-athletes. It also echoes other dynamic ranking frameworks such as those used by boxing and MMA and Formula 1. Unlike brittle, stats-heavy baseball, which depends on exact data and precise metrics to rank players and teams, these models don't need perfect fidelity to operate effectively. In fact, they thrive in the presence of a certain amount of subjectivity and entropy.

Like boxing, MMA, and F1, the Cargo Champs scoring system is nimble in the face of incomplete data and inevitable externalities. And it rewards trends and performance across time while making room for subjective value judgements about thrower and team quality. Our goal is to encourage ongoing performance, make room for subjective judgement, and, above all, ensure high-quality narrative momentum.

Records and Legendary Throws
In some cases, a throw that uses average, historical data may set a record or appear to be legendary. When this happens, we asterisk the throw. These throws warrant recognition and attention, but they do not qualify as official legendary throws or set official records because of incomplete data fidelity.

However, asterisked throws serve a vital function. They act as signal flares that suggest associated throwers/teams warrant special attention. When throwers and throwing teams consistently produce asterisked performances, we flag them for official observation and follow-up.

The Cargo Champs scoring model is not only designed to reward verified excellence. It also detects trends, surfaces outliers, and guides the attention of officials toward standout performers. In short, the system doesn't just record, reward, or respond to verified excellence. It actively hunts for it.

Official and Non-Official Throws
When throwers self-report data, we label that throw "NOF" (Non-Official).

NOF throws are valid and valuable, and they still contribute to thrower points, standings, and even unofficial records and benchmarks. NOF throws help us track trends, recognize effort, and surface rising talent. Consistent performance across NOF throws, in fact, is often the first signal that a thrower or team warrants official observation.

However, because they aren't logged or witnessed by a Cargo Champs official, we distinguish them from official throws whose core data points (start/end time, percent thrown, pallet count, &c.) are recorded by one or more Cargo Champs officials.

This approach supports the scalability of the Cargo Champs ecosystem. On a long enough timeline, every backroom, warehouse floor, and distribution center becomes a kind of farm league. And our master dataset becomes a dynamic blend of day-to-day NOF throws and official throws witnessed by trained Cargo Champs monitors. This creates an autonomous, nationwide talent pipeline that encourages mass participation and allows us to identify, witness, and encourage talented outliers.