Investigators are often faced with an overwhelming amount of data. In these situations finding an exact person, time, or place among all the noise can be very difficult. This problem is not limited to geo- or chronolocation challenges like those published by Quiztime either.
Fortunately this is not a new problem and there are tried and tested techniques for sifting useful information from all the noise. By applying filters that include what we know to be true and that exclude what we know to be false it is possible to eliminate incorrect answers until only correct ones remain. If this sounds like too much hard work just to solve a Quiztime puzzle, consider how often we do this every day without even consciously thinking about it.
Adding Filters
Let’s say that I want to buy a used car. There are about 430,000 used cars for sale in the UK currently – so how do I find one that I want and get rid of those that I’m not interested in? I just apply filters that include the features I want and exclude those that I don’t want: include hybrids, exclude diesels, exclude cars more than five years old, exclude SUVs and saloons, include estates and hatchbacks, exclude high mileage vehicles, include cars within my budget and within 50 miles of my house, and so on, and so on. Eventually the 430,000 cars is reduced to just a handful of possible purchases by carefully applying my chosen filters to eliminate the cars I am not interested in.
The popular children’s game Guess Who? works on the same principle. You have to guess the right person, but there are 24 possibilities. Only one is correct and 23 are wrong. Just as with the car adverts, finding the correct one is done by applying filters until the process of elimination is complete. Is the person male or female? Does he have black hair? Does he have a beard? Does he wear glasses? Is he bald? And so on. If your powers of elimination are good, you’ll ask better filtering questions than your opponent and guess the correct person first.
The exact same process of elimination can be used to filter out incorrect or useless data in an investigation. Perhaps you can’t quite pin down a location during a geolocation challenge? Try applying some filters based on what you know to be true or false and reduce the range of possible locations further and further. I’ve written about this type of approach before here and here.
So where could be better to practise this technique than with another Quiztime puzzle? Let’s have a look at Phillip Dudek’s latest question:
This is not primarily a geolocation question. It’s a chronolocation question – we need to know when the video was taken. Although we still need to know where it was, the hard part will be finding exactly when. Why is this hard? Because there are dozens or perhaps hundreds of different matches that this could be, and checking out hundreds of them would be time consuming and tedious. Instead we will be able to solve this by identifying features in the video and turning them into filters that we can apply to eliminate all the incorrect dates until we are left with only the correct answer.
Finding The Location
It isn’t too tricky to find out which stadium this footage was taken in. There are a lot of adverts for “Werderstrom“. A quick Google tells you that this relates to the supporters of Bundesliga club Werder Bremen. They play their home matches at the Weserstadion, and a quick 360 degree panorama check of the inside of the stadium shows the same layout, floodlights, and scoreboard position as in Philipp’s video.
Identifying where is quite straightforward – but finding out when is much more difficult. The green kit of one of the teams tells us that Philipp was watching a Werder Bremen home game, but we need to apply a lot of time-related filters to find the correct one.
Applying Filters
The first filter is very broad, but it is always better to work from big to small when narrowing things down. We can see a spectator filming the match on his smartphone (as presumably Philipp was too) so that means that the video cannot be any earlier than 2007 (when the first iPhone came out) and by definition no later than January 2022 when this video was posted. These time parameters are probably a little too generous, but better to start too wide than too narrow. Fifteen years is a little too broad to start researching specific matches however, so we will need to apply some more precise filters.
Right at the end of the clip we can see that the score was 2-2. We can’t see exactly who Werder Bremen were playing (which would have made this easier) but we do know that at some point in the match both teams had two goals each. It doesn’t mean that this was the final result, but it means all matches where this was never the case can be eliminated.
At this point it is tempting to research all of Werder Bremen’s historical fixtures and pick out matches that might be the correct one but this still leaves too many possibilities to check individually. In the Bundesliga each team plays approximately 40 matches per season. Even if only half of those are at home, that’s still 300 matches over a fifteen year period. Picking out possible results would take too long and would also be too tedious.
Time to find another filter. We can’t quite make out player names on the back of the shirts, but if we can correctly identify the Werder Bremen no. 5, we can tie him to a specific period when he played for the club and so be more certain about when this match took place. Football stats site Transfermarkt contains all kinds of useful data about player and club histories. We can even see the name of every player who has worn the number 5 shirt for Werder Bremen as far back as 1982.
We don’t need to go quite that far back, but Transfermarkt leads to another useful filter that can help to narrow down the time considerably. The player in the image above is white, but almost every player who has worn the No. 5 shirt for Werder Bremen in the past fifteen years is not:
Sambou Yatabaré, Assani Lukimya, Wesley and Pierre Womé are not white, and so cannot be the player in the photo above. The only two white players who wore the No. 5 shirt in this time period were Dusko Tosic (2008-2009) and Ludwig Augustinsson (2017-2021). We can’t quite make out the name on the back of the shirt, but it seems more likely that it says “Augustinsson” and not “Tosic” based on the name length. This means the video must have been made during Ludwig Augustinsson’s time at the club between 2017 and when he left for Seville in 2021.
It might be tempting to start researching the results for the period 2017-2021 to find the right game but there are still many more games that can be easily eliminated with more filters.
The next filter is the shirt worn by the Werder Bremen players. Although their home kit is always green, there is a slight variation every season. When Philipp was there, the green kit had white flashes on the shoulders – could this be distinctive enough to identify one particular season?
Yes it can. Football Kit Archive has images of every team’s kits going back many years, including those worn by Werder Bremen. During Ludwig Augustinsson’s spell at the club (2017-21) the club only wore green kit with white shoulders once, during the 2018-19 season. The shirt looked like this:
This means the video must have been filmed during this season (it also confirms that Dusko Tadic is not the number 5 in the video, since the kit did not look like this in the 2008-09 season either.)
You might be tempted to start checking the results at this point, but there’s still one more filter to apply. What else can we see in the picture that indicates the time? The clothing of the fans tells us that it is very cold. This is clearly not spring or summer, so we can assume that this match took place roughly between November 2018 and March 2019, when the weather was coldest.
Now we can check the fixtures! Werder Bremen played only 9 games at the Weser Stadion during this time period. Now you can see the benefit of working using carefully chosen filters to go through the process of elimination. Instead of checking through hundreds of matches we have eliminated all but nine, and of these nine only two meet the criteria for a possible 2-2 scoreline. These are the matches involving Eintracht Frankfurt and Schalke 04.
High levels of media coverage in football means it isn’t too tricky to find video footage of most professional matches. YouTube proved to be helpful for checking and verifying the right match.
This video is from the match between Werder Bremen and Eintracht Frankfurt. The kit colours are correct for both sides, including the purple kit for the Eintracht Frankfurt goalkeeper and the light blue shirts for the match officials.
You can even see our hero in the No. 5 shirt Ludwig Augustinsson conceding a terrible penalty at 3:29. Since Schalke play in blue and not red, we can also definitely rule out the only other possible match with this final filter. By process of elimination we can be sure that the video was taken on 26th January 2019.
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