Source: Wyscout.hudl.com / Manually tracked (for blocks preventing tangible danger)

Weight: 100%

What's handy is that Wyscout tracks all kinds of blocked shots. What isn't so handy is that there is a rich variety in how much actual danger those are preventing. Much like with shots, blocks are not created equal, hence I am applying a co-efficient to extra credit those who block shots that are clearly goalbound and from dangerous positions; ie. vastly different from hopeful long-range attempts headed for easy suffocation. For this bonus to be applied, the player also needs to actively move into a position to block such a dangerous shot. While Wyscout counts even passive blocks with the player basically just standing in the shot's way, sometimes even facing away from the shooter, the co-efficient disregards these instances. That's why there were only 3 players going into the double digits with these vital blocks in 25/26 (Prebsl, Halinský and Čihák). All of those mattered.

Source: Manually tracked

Weight: 100%

Instead of relying on Wyscout's clearances (sometimes bizarrely tagged deep into the attacking half) or vague "successful defensive actions", I rely on my own set of eyes and track truly vital defensive actions by myself. For this metric, I look at one's balance in game-reading (successful interceptions versus only partial interceptions, mistimed jumps or cases of miscommunication) and pure damage control (vital clearances or cases of backtracking versus those missed ones). Since it's all about the balance, the top of the leaderboard isn't flooded by bottom feeders with the most opportunities to sweep up (while pinned back). Even the likes of David Zima or Abdoulaye Sylla rank pretty high.

Source: Wyscout.hudl.com

Weight: 100%

After flirting with the centre back's contribution inside the opponent's box on top of the usual (success in his own penalty area), I am now back to only looking at the biggest areas of concern for a centre back in this space. Overall aerial efficiency (as an index) is considered separately.

Source: Wyscout.hudl.com

Weight: 100%

To filter out noise that doesn't matter, I'm concerned purely with ground duel success rate in here.

Source: Driblab

Weight: 75%

For years, I have stubbornly ignored Wyscout's "possession-adjusted tackles" metric since it only looked at one side of the coin. Enter Driblab, who bring us this metric, comparing the amount of tackles to the number of times the player was dribbled past (Virgil Van Dijk would never!).

Source: Driblab

Weight: 50%

Percentage of successful aerial duels together vs the volume of aerial duel wins. Anywhere. Simple.

Source: Wyscout.hudl.com

Weight: 100%

Pretty straightforward; with an added co-efficient applied to bring out penalty fouls.

Source: Wyscout.hudl.com

Weight: 100%

This is an interesting metric in that it accounts for both misplaced passes and lost aerial or ground duels (with the former weighed more heavily due to more control). The follow-up shot needs to occur inside the next 20 seconds per Wyscout rules, otherwise it’s rendered a “harmless” loss.

Source: Manually tracked

Weight: 100%

This is where I bash the player for any time he was caught sleeping; specifically whenever he caused a goal or a major chance via poor positioning, loose marking or lacking gap control (not applying pressure on a shooter/passer soon or urgently enough); a special co-efficient is applied on top of this to account for goal-causing errors. To be clear, I am no seasoned coach or even a tactics experts, so I might be off on a lot of these situation, but across the full season, I'd argue it evens out.

Source: Manually tracked

Weight: 100%

I have notes on all tangible danger occurring in each game, detailing culprits of all goals and chances allowed. For goals, these can be up to 4; for chances a maximum of 2. Similarly, any prevented threat gets assigned the "saviour". Once you put all starts together, how often does a centre back appear on the right side of the history? Given that there are more slots to go around for culprits rather than saviours, you might be surprised 29 of 67 regular CBs were at least break even. I normalize this per 90 mins, too, because being minus-2 on balance is not the same after 10 as it is after 30 games.

Source: Manually tracked

Weight: 100%

As previously noted, I assign up to 4 goal-allowing slots to any goal conceded across the season. There is one slot reserved for a grave fuck-up and three extra ones for more run-of-the-mill mistakes like losing a key aerial/ground duel, getting peeled off by a ball carrier, etc. This index then combines the percentage of goals the centre back "caused" — only accounting for goals against he is on the pitch for, to be fair — and the goals conceded per 90 mins rate with the CB around, as well.

Source: Driblab

Weight: 75%

Per Driblab's own glossary, this communicates the "sum of all bad actions committed (pass unsuccessful, take on unsuccessful, dispossessed, offside pass, ball touch unsuccessful) in own half".

Source: Driblab

Weight: 50%

You don't want your centre back to play it too safe, but you also don't want him to squander possession all too often. That's why this metric is here, but not valued all too high.

Source: Manually tracked

At extreme, I may note how often a centre back was implicated in a wasted chance or danger overall.

Source: Wyscout.hudl.com

Weight: 100%

As opposed to fullbacks, I am going with the success rate here to complement the aerial and ground duel success rates, to ultimately paint a rather full picture of one centre half's duel acumen.

Source: Wyscout.hudl.com

Weight: 100%

Interceptions alone don’t tell the full story — if your team dominates possession, you barely get the chance to make any. Wyscout fixes that by normalizing for context: they assume every team spends an equal 30 minutes per game out of possession (based on a 60-minute average of actual ball-in-play time). That way, players from possession-heavy teams aren’t punished for simply doing their job — which is how guys like Ševínský or Chaloupek still manage to land in the 80th+ percentile.

Source: Wyscout.hudl.com

Weight: 100%

This is one of my original innovations undergoing a bit of reconstruction in 2024, when I switched from the share-of-all approach to instead look simply at the number of controlled clearances normalized per 90 minutes. As a refresher: a clearance is considered “controlled” when it results in the team in question retaining the possession post-clearance. Sometimes you can also see it called a “targeted header”, but I don’t only consider aerial clearances, mind. I’ve dropped the percentage because a lot of clearances are done in crowded, high-pressure areas inside the penalty box, and those facing more daunting tasks like these are unfairly punished. Now I believe my model does at least marginally better in trying to tell us a (partial) story of one’s awareness/peripheral vision.

Source: Wyscout.hudl.com

Weight: 100%

This metric, normalized per 90 mins, measures how many meters a player advances the ball through successful carries, excluding passes. It calculates the difference in distance to the opponent's goal between the start and end point of a run or dribble, counting only forward movements.

Source: Driblab

Weight: 75%

Passing accuracy is an outlived concept, a largely irrelevant stat only data dinosaurs tend to refer to these days. But when you look at pass completion under strong pressure (ie. within 0-2 meters of the nearest opponent), it's a different discipline entirely — telling a story of one's awareness.

Source: Driblab

Weight: 50%

Recoveries 40+ meters from own goal made 8 seconds after losing the possession of the ball.

Source: Driblab

Weight: 25%

Number of successful efforts (possessions recovered) made by a player when pressing the opponent.

Source: Wyscout.hudl.com

Weight: 100%

Sorting through tags, I filter out accurate long passes that stretch play more or less diagonally, hitting the channels, and take away any out-of-the-bounds stretch passes from the total. This metric is also normalized per 90 mins since being plus-4 means something else across 10 and 30 starts.

Source: Wyscout.hudl.com / manually tracked (for danger created via touch/feel for the game)

Weight: 100%

The number of times, normalized per 90 mins, a player enters the opposition’s penalty area in open play — via a carry, a cross, or a pass. It discounts set pieces for fair comparison. In addition, a co-efficient benefitting prolific chance/goal creators via superior touch and feel for the game is applied.

Source: Driblab

Weight: 100%

Per Driblab's own glossary, "Expected Threat (xT) is a metric that measures the threat a player creates to the opponent by carrying or passing the ball to areas where the possession's probability of ending in a goal is higher". At the same time, Driblab also tracks how the player allows dangerous areas to be penetrated at the other end, which is exactly where the "net" aspect comes in play.

Source: Wyscout.hudl.com

Weight: 100%

I used to consider both expected goals and assists in this space, but then I realized in 2025 that for creative passing/crossing, there are enough other metrics, so here I focus purely on the threat posed in the capacity of a finisher. Normally, this stat boils down to "who's the biggest set piece alfa", though I additionally track the percentage of xG coming from open play as well as the amount of xG generated through head shots (normalized per 90 mins) via Driblab out of sheer curiosity.

Source: Manually tracked

Weight: 100%

My own alternative to Wyscout's flawed xG/A, where I don't care for unfinished business. As long as the player delivers the ball to a dangerous position, onto his teammate's feet, he gets credited regardless of the outcome. Sometimes, if the teammate doesn't time his slide properly or wildly miscontrols the ball, the "on his teammate's feet" caveat doesn't apply, either. And with the exception of goals, the player can also be credited for creating danger for himself. As opposed to xA, I also disregard set piece delivery to make sure the comparison is fair and indeed feasible.

Source: Driblab

Weight: 100%

Driblab is much more playful with xG than Wyscout. Here I am leveraging on their metric that takes into account the player's contribution in the build-up where both the shooter and the one who set him up are excluded. Unsurprisingly, centre backs of Slavia and Sparta rank the highest through the sheer amount of xG generated, but there are still intriguing appearances up and down the ladder.

Source: Wyscout.hudl.com

Weight: 100%

Oh yes, your hipster friend’s term — of course it pops up. You always find the half-space here, and exploiting it is a noted weapon, so hitting them regularly is welcome. Also normalized per 90 mins.

Source: Manually tracked

Weight: 50%

Via all goals and only meaningful assists (ie. not just balls handed over to the lucky/sharp shooter at the edge of the box). For 2025/26, I am also crediting any indirect goal contribution (at a lesser weight), while setting back the player for any goal-causing (grave) error which also carries its own value. Here's full explanation of the innovative model, initially introduced by the tremendous CSfotbal. And here's the final leaderboard for 2025/26 (featuring not too many centre backs, duh).

Source: Driblab

Weight: 75%

Switching from Wyscout to Driblab, I'm still interested in passes that penetrate the defensive line.

Source: Driblab

Weight: 50%

Here I compare two separate Driblab values: the traditional pass accuracy against the expected pass completion. You basically want to be anywhere above break even, which would suggest you are doing well with the passes you pick (18 of 67 CBs didn't manage that). Here's more on the logic.

Source: Driblab

Expressed as percentage of shots on target ending in a goal above average, this ready-made metric effectively measures how much value the player in question adds with the quality of his shots.