There remains plenty to enjoy in the jaundiced pages of early 80s Shoot! magazines. Brian Clough launching whisky-tipped howitzers at anyone within a 250-mile radius of Nottingham. The startling sight of Martin Jol, rake-thin with locks swept back like Dirty Harry-era Clint Eastwood. Romeo Zondervan's Jheri curl smelling of Soul Glo even in photographs. And proper hard men, such as Graeme Souness and Brian Kilcline, with perms as tight as their shorts; an alluring mix of Elnett and testosterone. But while the hairdos were elaborate the numbers were elementary. Half-time score. Full-time score. Attendance. 1-11, 0-90. 4-4-2. That was pretty much it.

Nowadays almost everything in football is tracked and crunched. Prozone monitors players' movements every 10th of a second, sprints, rests and more. Opta has a model that quantifies the percentage chance a shot has of going in. And while some data is squirreled away by those whose livelihood depends on an edge – big clubs and professional gamblers – much of what remains would enhance our understanding of the game.

Which makes it puzzling that broadcasters continue to focus on crude possession and player distance stats, even when they are as illuminating as an energy-saving light bulb.

Last week, during the second-half of Milan's Champions League tie against Barcelona, a statbox showed the visitors had enjoyed 67% of the ball. It was as surprising as dawn breaking. In the 345 matches Barça have played since 2007-08, they have had over 50% possession in every game except Real Madrid on 7 May, 2008 and Getafe on 6 February, 2010. It is an obvious hallmark.

Therefore a little filtering was needed. How much of Barcelona's possession was in Milan's penalty area? How many touches did Lionel Messi take in the 18-yard box? (answer: one). How did that compare to previous away games in the knockout stages? Suddenly a broader picture would have emerged.

The distance-run stats did not particularly enlighten either. If you are facing Barcelona and your plan is to allow possession in some areas and press in others, you do not necessarily need your midfielders to do a passable imitation of Bryan Robson circa 1982. As Chris Galley, the head of analysis at Smartodds, which provides analytics and qualitative models for professional gamblers, puts it. "It's OK saying that a player runs 12km – but the key question is what has he done with the ball? How many high-intensity sprints has he made and where have these runs been made?"

So if Milan were counterattacking – why not show how many passes and seconds it took for them to get from their penalty box to the offensive third? Or how many times a midfielder sprinted to get involved with the attack? Again, you are using the same statistics but go deeper and richer.

When you look at the teams with the best possession stats in Europe this season – Barcelona 69.76%, Bayern Munich 63.91%, Manchester City 58.44%, Arsenal 58.24%, Juventus 58.23%, Liverpool 58.1%, Lille 58.01% – it is clear that it does not guarantee success (even Barcelona have lost 35 times since the start of the 2007-08 season).

Nor does it necessarily tell you which team are on top. Last season Swansea had lots of the ball but little in the attacking third. It is telling that Rob Mastrodomenico of Global Sports Statistics, which uses data and advanced models to help predict future matches, says: "From a purely modelling point of view we don't use possession. Shot-based stats are more relevant if you are looking for a team to score."

Opta's figures back that up. Of the 181 games won in the Premier League before last weekend, the team who had the most possession only won 103 – 57% in total. The team who had more shots on target than their opponents won 128 matches – 71% of the total.

You can plunge even deeper. Sam Green, an advanced data analyst at Opta, has used a database of thousands of matches to develop a model that quantifies the chance of a shot going in depending on its location.

When Newcastle lost 2-1 at home to Reading last month they had 56% possession and 16 shots to seven. But, as Green points out: "Reading created two excellent chances – Pavel Pogrebnyak's miss in the 27th minute (goal probability 49%) and Adam Le Fondre's opener (from point-blank range, 69%), as well as his second (17%) – while Newcastle only had one very good chance: Papiss Cissé's shot in the 30th minute (from just outside the six-yard box, 34%)."

Using his model, Newcastle had a goal expectancy of 1.4, with Reading slightly better at 1.6. The bald stats told one story, the more detailed analysis another.

So why don't broadcasters use data that clubs have long since dipped into? Blake Wooster from Prozone, which provides match data to Canal Plus and Al-Jazeera, believes is it about understanding audiences. "I sometimes make the distinction between what is interesting and what is important," he says. "Professional footballers and gamblers are interested in the key performance indicators that contribute to winning – viewers perhaps less so."

That process is surely changing, with Gary Neville's forensic pre-game dissections on Monday Night Football at the vanguard. Now we just need a similar mini-revolution during live matches.