United States Men’s World Cup Qualifiers: Statistics Defining the Way to Qatar
Of course, this happened in the most discouraging way possible: a 2-0 defeat in Costa Rica in which Los Ticos fans shouted “¡Olé!” That was saying. Their defenders passed the ball to each other. But the United States men’s national team did what they couldn’t do in eight years, and the only thing they won’t have to worry about again: qualifying for the World Cup!
The USMNT automatically qualified for the 2026 World Cup as a joint host with Canada and Mexico, and the next time the tournament expanded to 48 teams, it was the last really awful, geometrically organized qualifying campaign for the American people. So, let’s look at the eight prime numbers in the first and only octagon. Here’s how USMNT got back to the biggest stage of soccer:
1.8
On the surface, it doesn’t look great at all – third place, the match between Canada, which has not been to the World Cup since the invention of the DVD, and Mexico, which has been on the brink of crisis every half time. Here’s how they compare to each qualifying campaign since the 1994 World Cup:
-1998: 1.7 points per game, second place
-2002: 1.7 PPG, 3rd
-2006: 2.2 ppg, 1st
2010: 2.0 ppg, 1st
-2014: 2.2 ppg, 1st
-2018: 1.2 PPG, 5th
In six qualifying tournaments before Greg Berhalter took over as manager, the USMNT averaged 1.8 points per game. In a qualifying contest after Berhalter took office … USMNT averaged 1.8 points per game. This is by far the smartest US team and two extra teams in the qualifying pool had to water down the competition, just reaching the average can be a bit disappointing. But there is little connection between qualifying and World Cup success; USMNT’s run to the semifinals came in 2002, after a poor CONCACAF run that produced just 1.7 points per game and came down to the final day. On top of all this, there is a lot to suggest that Barhalter’s team was better than the results suggested.
Many strange things can happen in 14 games. Choose any pattern of 14-game in the Premier League season and you can convince yourself that Liverpool is losing and Wolverhampton Wanderers are winning. In a low-scoring game like soccer, it takes a lot of games to match the results to the level of team performance.
To begin with, just look at the goals: goals scored, agreed and then subtracted from each other. Going back to ’98:
-1998: -0.8 goal difference per game, 2nd
-2002: more -0.3 GD, 3rd
-2006: more -1.0 GD, 2nd
-2010: more -0.6 GD, T-1st
-2014: Plus -0.7 GD, 1st
-2018: plus -0.4 GD, 3rd
This time around, USMNT scored 21 goals (second only to Canada) and 10 (fourth after Canada, Mexico and Costa Rica). 0.8. Only Canada (plus-16, plus -1.1 per game) produced good points in the octagon, and only one of the last six American teams outscored their rivals in a high-clipping side by Berhalter.
0.96
Statistical performance not only provides the expected target data for CONCACAF qualifying back in 2014, but it is still worth looking at as it is the best qualifying run of USMNT in terms of 2014 scores. Dig a little deeper, and there were already some warning signs for the rest of Jurgen Klinsmann’s career.
In the 2014 qualifiers, the team’s per-game xG difference was only a plus-0.26. In fact, in 2018 (plus -0.4) it was good, you know, crows and that’s all. This cycle, the number leaps to -0.96, which, for some reason, you can expect from one of the elite club teams in Europe. The competition is not comparable, but in terms of creating opportunities and blocking opportunities, the US dominated CONCACAF in the same way that Paris Saint-Germain could in League 1.
Overall, both USMNTs produced the highest xG in the octagon (23.3) and accepted the lowest (9.8). Remove the penalty, which may be a little unexpected, and that’s true:
Courtesy of TruMedia / Stats Perform
Despite the best underlying numbers in the competition, they finished third. What does it offer? xG is more a true representation of the quality of the team than their overall score; The USMNT did something repeatable – creating and suppressing opportunities – better than everyone else, but volatile – seizing opportunities – doesn’t always go their way. But there is another explanation.
