The Most Valuable Ball Progressers in the PSL
Exploring Expected Threat (xT)...
By now, most fans are familiar with Expected Goals (xG), the statistic that measures the quality of a team's chances by estimating the likelihood of a shot resulting in a goal. The metric itself has become a vital tool in understanding and evaluating performance, and has even begun to shape scouting and recruitment discourse and strategies. However, while xG remains the focal point in chance creation analysis, it is still limited in that a PSL game has only about 20 shots on average, from a pool of 2500 events on average. It means there is a lot of football not being measured, and this gap has led to the emergence of possession value models, like Expected Threat.
The Concept of Expected Threat (xT)
Think of it like this: when you're in a pub on a Saturday night, deciding which side of the bar to go to for quicker service, you make an intuitive calculation to choose the faster option. While you’re not performing a literal calculation, your decision is based on the recognition that one side offers greater value in terms of time efficiency. In football, the idea is similar — certain areas on the pitch are inherently more valuable in terms of scoring opportunities than others. Cheers!! 🍻🍻🍻
“Expected Threat (xT) is calculated by laying a 'value surface' over a football pitch to divide it into zones, where each zone has a value assigned to it based on how likely a goal is to be scored from that zone. Players can then be credited for moving the ball from zone to zone. It was first introduced by Karun Singh in 2018, and is arguably the most known possession value model in the industry.” (Statsbomb blog definition)
In simple terms, Expected Threat (xT) measures how dangerous a given pitch area is, based on the likelihood of scoring from a particular zone. We intuitively understand that two players (one in his own box and the other in the opposition box) are in zones of different danger - but how can we quantify that difference?
The Benefits of xT
While xG is useful for measuring shot quality and a team’s final ball “dangerosity”, it can’t assess the potential of a player or team’s overall attacking actions that don’t directly lead to shots. xT, however, zooms out to account for the entire attacking process — from carrying the ball upfield to making key passes that open up new avenues for scoring. For example, a shot from outside the box might have a low xG (and low Expected Assist value), but the pass or carry that set up that shot could have significantly increased the likelihood of a goal. By focusing on how the ball got to where it is on the pitch, xT fills the gap that xG and xA doesn’t.
The core value of xT lies in its ability to assess the probability of scoring from each possession, depending on the ball's position. This model doesn’t just look at shots or assists; it highlights how players advance the ball through the pitch, which is often the crucial first step in creating a dangerous chance. xT is’t perfect (for example - it uses only event data like passes and carries - there are other ways of adding value to a team’s attack (like defensive actions)). But it certainly adds much more value for Player evaluation, tactical analysis and even scouting than our fave goal involvements.
How xT Works in Practice
To make this tangible, let’s imagine a player passing the ball into a dangerous area of the pitch. Using data over the past seasons, each zone on the pitch is assigned an xT value, representing the chance of scoring based on the ball’s position. The closer to the opponent's goal, the higher the xT. Players who regularly progress the ball into these higher-value zones increase their team's chance of scoring — even if they don’t directly end in a shot. The original Karun Singh model looked something like this:
For example, a pass made by Teboho Mokoena to Peter Shalulile in the final third may seem like a small action, but in terms of expected threat, it significantly increases the chances of scoring. Similarly, a brilliant run by Pirates’ Patrick Maswanganyi, who collects a pass and surges through the midfield before laying off a key pass to Evidence Makgopa, boosts his team’s xT by moving the ball closer to dangerous zone.
By analysing how players contribute to progressing the ball through different zones, we can identify the top ball progressors in the league (not just by volume but by value). Often, these players may not always get the credit they deserve for opening up opportunities but their actions are crucial to their team’s attack.
Expected Threat in the 2024/25 PSL
By looking at the xT of a player’s completed passes, we can illustrate the most valuable ball progressors in the league. Some are predictable - they easily pass the eye test, but others perhaps a little underrated. The chart below shows the xT per game that a player has added from their passes.
Keletso Makgalwa is by some distance, the most threatening ball progressor in the league this season (by this measure). The midfielder's incisive passing into the final third and penalty area sees him clock up plenty of threat for saw him clock up plenty of threat for Sekhukhune United, which certainly passes the eye test. No wonder, he is also up there on the chances created metric (2nd overall).
Elsewhere, Gaston Sirino is still showing his ability to play clever passes in the midfield for Kaizer Chiefs. A very sought-after characteristic that brought him to Sundowns all those years ago. AmaZulu’s Riaan Hanamub has always shown himself to be a very attack-minded full-back and also ranked high in our xT model last season.
Lwandile Mabuya, Darwin Gonzalez (most big chances created last season), Puso Dithejane and Fawaaz Basadien are also showing their quality going forward. Gadinkame Modise, Azola Ntsabo and Deolin Mekoa make up the Top 10.
The Road Ahead for Expected Threat
As xT continues to develop, its application is broadening. Teams and analysts can use it to measure how players and teams are progressing the ball, identify key contributors to attack, and even evaluate the efficiency of a team’s overall strategy.
xT can be used to:
evaluate players' performances by analysing their contributions to the team
identify opposition trends in ball progression
scout players that contribute positively to a team
While xG remains a powerful tool for analysing shooting quality, xT brings a more holistic view of the attacking process, giving us deeper insight into how and why certain moments on the pitch are more valuable than others. Future work will break down xT for carries (so we see the most valuable ball carriers) and for passes (so we identified the most valuable passers).