Alle Tore aus den 101 abgeschlossenen Spielen (einschließlich des heutigen Halbfinales) dieser Weltmeisterschaft wurden ausgewählt und nach dem 15-Minuten-Block gruppiert, in dem sie erzielt wurden.
In den letzten 15 Minuten der regulären Spielzeit (76–90, einschließlich Nachspielzeit) fielen 77 Tore – mehr als ein Viertel aller 296 und fast doppelt so viel wie jeder andere Block in der Tabelle. Insgesamt fielen in der zweiten Halbzeit 35 % mehr Tore als in der ersten.
Ich habe die Verlängerungstore aus den K.-o.-AET-Spielen als separate Leiste beibehalten, da sie aus einer viel kleineren Anzahl von Spielen stammen und es irreführend wäre, sie in den 76–90-Block einzuordnen.
Ziemlich cool, das richtig visualisiert zu sehen!
Habe das aufgebaut Das Prismaeine KI-Fußballanalyse-App, die ich entwickelt habe, um uns die Visualisierung solcher und weiterer Dinge zu ermöglichen. Daten + Methode in den Kommentaren.
Von moabusin
9 Kommentare
Data: ESPN’s public World Cup 2026 feeds – every goal from all 101 completed matches, bucketed by the minute it was scored. Regulation stoppage folds into its half (a „90+3′“ goal counts as 76–90); the 7 extra-time goals from AET knockouts are the separate „91–120“ bar since they come from far fewer matches.
Tool: [The Prism](http://theprismai.com) – an AI football analytics app I’m building; this is pulled straight from its World Cup data layer. Chart: Python/matplotlib.
Interesting! Also cool that the second-highest line is that time before the end of the first half.
Makes sense when you consider that added time is built into that section. The other section with added time is 31-45 which has the second most goals. I imagine the difference is from teams pushing to tie either doing so or surrendering an additional goal trying.
This doesn’t work as well this World Cup. Hydration breaks mean no goals will be scored between 23-26 mins, and those will be added to 45+. Likewise with 67-70 mins hydration break, added to 90+ goals.
I feel like if you add „added-on time“ to the 76-90 bracket, showing this as goals/minute would have made more sense.
Cause without correcting for the addon time, this seems kinda misrepresentative. I’m guessing that the average addon time isn’t enough on its own to offset the statistic like this, but I do no know that.
(same thing also goes for the first half and to an extent the ad breaks in the middle of the halfs. goals/m would also make the overtime stat at the end more interesting)
That said, this at least shows a clear trend towards goals in the second half of the match.
That’s when the subs are in
The last 15 minutes of a game is often „desperation time.“ That creates a lot of opportunities in both ends.
When they stop for an ad break theure less likely to score? Shocker
There’s 98 mins of game time at these games. 104 total minus 6 mins of hydration breaks
If you wanted to split it up into 6 equal groups it would be the following.
0 – 16
16 – 35
35 – 45+
45 – 61
61 – 80
80 – 90+
All roufhly 16 mins of game time.