A decade ago, stats were used as complementary sides in football discourse. Nothing more than shots on target and possession were discussed when going over the events of the game.
Statistics were like the cranberry sauce placed on the edge of the plate during your Christmas feast – tasty, but not necessary for the meal to taste good.
Stats were largely just mini-context providers slapped onto your television screen during a match to offer a little data insight about which way the game swayed.
However, these metrics were often shallow and meaningless. Having 30 shots on goal means nothing if they were all from range and none hit the target.
Around the same time, Opta analyst Sam Green brought forward a new metric that would revolutionise football while creating a division between the more analytical thinkers and the game’s purists: expected goals.
Fast forward to 2022 and the world’s leading football broadcasters such as Sky Sports now use xG while the FIFA World Cup introduced stats such as ‘forced turnovers’ and ‘final third receptions’ during games.
Stats are no longer a complement to the eye test. While the latter is arguably still the most important, data can provide us with a whole picture of how a match unfolded without even setting our eyes on the game itself.
Data is now a way to confirm what you’ve seen, a method to check your biases and is only becoming more and more important in the sport to the point where top clubs have their own data departments, including many data analysts providing feedback to the coaching staff.
At Total Football Analysis, we’ve been doing our own bit to bring our readers daily stats packs of games from all corners of the globe, whether it be from the Premier League, the A-League, the Copa Libertadores or even the MLS. We’ve got you covered.
In this data analysis piece, we’ll be talking you through how to read our stats packs to get the most out of your viewing experience. This article will offer insight and analysis into how to understand our data visualisations better in order to leave with a grasp of how the games unfolded, without even needing to have laid eyes on the match.
To do so, the example we will use is the Premier League’s opening fixture on Boxing Day between Brentford and Tottenham Hotspur. Let’s get into it.
Lineups, average positions, heatmaps and touch maps
In the stats packs, the data is provided by Wyscout and Analytics FC and while they may not have as many in-depth metrics as FIFA were using during the Qatar World Cup, it does mean that TFA can cover quite a lot of bases, including average positions, xG, shots assists, high regains, chance creation, ball progression and much more.
First and foremost are the lineups from the two teams. This image sets out the starting eleven across both sides as well as the formations that each manager has chosen to use from the get-go.
As we can see, Thomas Frank deployed a 3-5-2 compared to the visitors’ 3-4-3. This is basic information and there’s not much to explain here. The starting elevens just provides the reader with a clear understanding of which player played in each position within the coach’s structure, so you have a clearer understanding of what’s to come.
What is more interesting is the average position map. Ultimately, formations mean very little. Manchester City and Liverpool set out in a base 4-3-3 formation, but the shape rarely resembles this quantified order.
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