When it comes to sports, is it really all about passion?

The final score tells us whether a team won. But by the time it appears, it is already too late to influence the game.

That makes winning a classic lagging indicator. Until the final whistle, anything can happen. The useful question is not simply, “Did we win?” It is, “Which actions during the game increased our probability of winning?”

From passion to performance data

To win, a team must create offensive pressure, resist the opponent's pressure, and convert opportunities into goals. I grouped match data into three broad dimensions:

When the Balance Indicator was compared with the results, the winning teams had a value roughly ten times higher than the losing teams. That does not make the model perfect. It does show that the final result leaves a trail of observable behaviors.

The variable the model could not capture

France and Argentina made the limitation obvious in the final. The match remained tied through regulation and extra time even though the aggregate model favored Argentina.

There is something subjective and difficult to gauge: grit—the extra strength a team finds when everything starts going south.

Both finalists showed enormous grit. Sports will always contain elements that are not fully predictable. The model does not eliminate passion; it helps translate repeatable behavior into actions a team can influence before the game is over.

Performance influencers

At the 2019 SMRP conference, William Leahy, CMRP, presented the idea of the KPI as a Key Performance Influencer: an action or measure that can influence a future result. His work with the USCGA Bears hockey team helped move the record from 5 wins and 13 losses to 16 wins and 1 loss with the same team and a different operating method.

Using the same principle, ten World Cup match behaviors emerged as meaningful influencers. The percentages below reflect the observed advantage of winning over losing when the condition was met in the dataset:

In the 64-match dataset, every team meeting eight or more of the influencers won. Every team meeting fewer than two lost. The sample is not a universal law, but the pattern illustrates how a final outcome can be broken into smaller controllable wins.

The asset-management parallel

Industrial organizations also need to translate distant goals into actions that can be completed today. Reliability, cost, risk, and production outcomes are lagging results. The daily work that influences them is often much smaller:

• Complete the work order with enough detail for the next person to learn from it.
• Report the actual failure mode rather than choosing the fastest available code.
• Perform inspections with attention instead of pencil-whipping the checklist.
• Protect schedule compliance and close the loop on defects.
• Recognize the early signals that move risk before a breakdown occurs.