World Cup 2026: Running-Distance Data Foreshadowed Germany's Group-Stage Exit

In the 90th+6th minute at Kazan Arena on June 27, 2026, Son Heung-min collected the ball near the halfway line, pushed it past goalkeeper Manuel Neuer, who had advanced to join the attack, and rolled it into the empty net. The score closed at 2-0 for South Korea. Germany, the reigning world champion, left the 2026 World Cup bottom of Group F with three points from three matches and a goal difference of -2.

Three weeks earlier, I published a self-computed data table with a conclusion many colleagues called reckless: Germany would not get out of the group. The table rested on four metric groups — average distance covered per match, expected-goals differential in the last three pre-tournament friendlies, the PPDA index, and squad age structure. The result in Kazan confirmed the table; how it was confirmed is the part worth discussing.

I read football through spreadsheets before I read it through my eyes. In 2026, at 34, I proposed covering the entire U20 World Cup in South Korea myself. U20 Venezuela's average PPDA was 7.9, the lowest in the tournament; PPDA measures how many passes an opponent is allowed before each defensive action, so a lower figure means more intense pressure. I predicted Venezuela would reach the final before the group stage began. They reached the final and lost only 0-1 to U20 England. From a youth tournament in South Korea, I read five years ahead of world football, and from then on every analysis I wrote began with a self-computed data table rather than with a team's reputation.

At the 2026 World Cup I kept the same method. Group F held Germany, Mexico, Sweden and South Korea. Germany arrived as reigning champion, with a squad built largely from the players who had won in 2026. Based on my experience tracking the pre-tournament friendlies, the four metrics lined up into a single picture, and that picture did not match the status of reigning champion.

The first metric was average distance covered per match. Across the three pre-tournament friendlies, Germany's figure was 4.3 kilometres per match below the average of the teams in their group. This is the most misread metric in football analysis, because distance covered measures only the volume of movement, not its value. A team can run little and still control a match; a team can run a great deal and produce only wasted sprints. The low distance here was a symptom, not a cause.

The second metric was the expected-goals differential. Across the last three friendlies, Germany's xG differential was negative, meaning the quality of the chances they created was lower than the quality of the chances they conceded. The third metric was a rising PPDA, reflecting declining high pressing. The fourth was age structure: the core players clustered in the post-peak years, after a congested club season.

The group stage unfolded in the sequence the data table suggested. On June 17, 2026, Germany lost 0-1 to Mexico after a counterattack finished by Hirving Lozano. On June 23, 2026, Germany beat Sweden 2-1 through a Toni Kroos free kick in the 90th+5th minute, an individual moment that papered over a systemic problem. On June 27, 2026, Germany lost 0-2 to South Korea; Kim Young-gwon scored in the 90th+3rd minute and Son Heung-min sealed it in the 90th+6th.

Data hides nothing; we simply have not arranged it in the right order. Yet the same data table also led me to predict Brazil as champion. On July 6, 2026, in Kazan, Brazil lost 1-2 to Belgium and stopped in the quarter-finals. One model caught Germany and missed Brazil. The limit of data analysis lies here: a model describes probability, it does not foretell the future.

The deeper blind spot lies in causation. The low distance did not make Germany lose; it travelled alongside the thing that made Germany lose, which was chance quality. Looking only at distance covered, I could have reached the right result for the wrong reason, and a conclusion that is right for the wrong reason collapses at the next tournament. For Vietnamese fans, January 2026 taught the opposite lesson: Vietnam's U23 team reached the AFC U23 Championship final on January 27, 2026, in Changzhou, losing 1-2 to Uzbekistan in extra time, in a match where snow and emotion blanketed every data table. Russia 2026 taught me that the greatest risk is failing to bet on the data. Changzhou taught me that data only means something when we know it does not tell the whole story.

The signal for the next cycle is not the trophy. It sits in Germany's age structure during Euro 2026 qualifying and in the minutes played by the group of players born after 2026. Football never obeys emotion, but it always obeys probability. For those who work with data, the question that remains is this: when a data table is right about the result but wrong about the cause, do we dare to rewrite the formula?