The hope or dread that a game changing goal is about to materialize often creates the tension that is so well known to football supporters, but the rarity of the event makes any predictions we make about the game prone to the random variation that is always present in small sample sizes.
The vagaries of random variation impact on the fortunes of football teams through a variety of ways. Firstly, by factors such as shot conversion rates refusing to co-operate in the short term by exhibiting unsustainably high returns or unrepresentatively below par rewards. Even when samples run to larger sizes and goals scored reflect a side's genuine abilities, they may not be distributed within the individual games to reap the maximum returns for the scorers.
However, even before we begin to wrestle with these questions, we need answer an even more fundamental question of how many goals is a side likely to score. August is the month for prediction and notwithstanding the churning of squads during the transfer window, evaluating future team performance in terms of the number of goals they can expect to score (and concede) merely from past performance is still a worthwhile pursuit.
What is likely to occur in the future often relates to what has happened in the past and goals are no different. However, we are partly hamstrung by their relatively infrequent nature. Goals are the most important match day event, but we really could do with many more examples to occur before we can begin to see repeatable skill overcoming unrepeatable, random noise.
In previous, recent posts I've looked at how to try to use more frequently occurring events, where skill is more prevalent than noise, that are reasonably strongly correlated to the less frequent event we are attempting to project for future games.
Goal scoring is inevitably associated with the final act of putting the ball past the keeper, but much takes place prior to the score. Passing build up, along with off the ball running to free a colleague into space, to name but two. At the risk of appearing simplistic, to score in football, you have to be good at playing football.
Passes are the building blocks of the game, but at an even more basic level, the most visible act of playing football involves a player simply touching the ball. Being in possession or close enough to the ball to get a touch immediately makes the player the focus of attention for his team mates, opponents and the crowd, even though much running off the ball is taking place.
If goals are the least common normal football action, merely touching the ball is by far the most common one.
Although it is an artificially designated area, most of the attacking and goal scoring action is played out in the final third. A team is already in the part of the pitch where most goals are struck from and where the majority of the assists or key passes originate. Therefore, it is an area where possession is more keenly fought for and a side which can accumulate lots of touches in this area is likely to be demonstrating that it can "play football".
Above I've plotted the correlation between total touches made by each side in the final 3rd during the 2011-12 season and the total number of goals they scored, with gifted opponent own goals removed. The relationship is reasonably strong and the direction and causative nature would appear to be sensible. More touches in the final third, which of course includes the opponents penalty area and six yard box is related to enhanced scoring.
Not Quite Building To A Goal, Genoa rack up the Final 3rd Touches against Stoke. |
How Good Are Final 3rd Touches At Predicting Future Goal Scoring Totals.
Team. | Final 3rd Touches 2011/12. | Goals Scored in 2011/12. | Predicted Goals from Final 3rd Touches. | Goals Scored in 2012/13. |
Arsenal. | 6740 | 73 | 68 | 69 |
Aston Villa. | 4689 | 37 | 43 | 47 |
Chelsea. | 6048 | 63 | 60 | 71 |
Everton. | 5614 | 47 | 54 | 53 |
Fulham. | 4988 | 43 | 47 | 45 |
Liverpool. | 6949 | 42 | 70 | 68 |
Manchester City. | 7428 | 91 | 77 | 64 |
Manchester United. | 7062 | 87 | 72 | 80 |
Newcastle. | 4225 | 51 | 38 | 43 |
Norwich. | 4947 | 52 | 46 | 40 |
QPR. | 4830 | 41 | 45 | 30 |
Stoke City. | 3942 | 35 | 34 | 33 |
Sunderland. | 4538 | 43 | 41 | 39 |
Swansea. | 4709 | 43 | 44 | 47 |
Tottenham. | 6298 | 65 | 63 | 63 |
WBA. | 5356 | 44 | 51 | 50 |
Wigan. | 4713 | 41 | 44 | 45 |
(Blue figures indicate the prediction generated from final 3rd touches was closer to next year's actual performance).
As ever, I've used the number of goals a team would have expected to score given the relationship between the secondary indicator (in this case touches in the final third) and goals and the actual number of goals scored. I've then compared the actual number of goals scored during the subsequent season to see if goals scored the previous year or expected goals derived from a much more frequently occurring, strongly correlated minor statistic is the better indicator of future performance. In short does the frequent, hopefully skill dominated secondary stat beat a more noisy, but direct comparison.
In 2011-12 and subsequently in 2012-13, touches overwhelmingly predict future goals scored over a season with less error. In 14 of the 17 surviving sides, touches gave a closer estimate of goals scored in year N+1. On average, touch generated predictions were out by 4.5 goals over the season compared to 8.5 when using actual goal totals.
Liverpool's 7,000 final 3rd passes merited 70 goals in 2011-12, but they managed a well adrift 42 scores from their own efforts, but bounced back with 68 a season later. Both over performing Manchester clubs and Newcastle each fell back to earth in 2012-13, producing seasonal goal totals that tumbled back towards the levels expected from the number of final 3rd touches they recorded during the previous year. Although United still managed to stay ahead of the expected curve. Manchester City, however, really did turn out to be noisy neighbours.
If the experience of 2011-12 and 2012-13 persists and we can better predict how many goals a side will score (and concede by a similar process) and by extension, a side's expected goal difference and ultimately finishing position in future seasons, a player merely touching the ball deep in opposition territory may become (almost) as exciting as a real live goal.
In 2011-12 and subsequently in 2012-13, touches overwhelmingly predict future goals scored over a season with less error. In 14 of the 17 surviving sides, touches gave a closer estimate of goals scored in year N+1. On average, touch generated predictions were out by 4.5 goals over the season compared to 8.5 when using actual goal totals.
Liverpool's 7,000 final 3rd passes merited 70 goals in 2011-12, but they managed a well adrift 42 scores from their own efforts, but bounced back with 68 a season later. Both over performing Manchester clubs and Newcastle each fell back to earth in 2012-13, producing seasonal goal totals that tumbled back towards the levels expected from the number of final 3rd touches they recorded during the previous year. Although United still managed to stay ahead of the expected curve. Manchester City, however, really did turn out to be noisy neighbours.
If the experience of 2011-12 and 2012-13 persists and we can better predict how many goals a side will score (and concede by a similar process) and by extension, a side's expected goal difference and ultimately finishing position in future seasons, a player merely touching the ball deep in opposition territory may become (almost) as exciting as a real live goal.
Where can final third touches data be found?
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