Despite all the preparation before the start of a soccer match, one small stroke of luck and a goal for either team can change everything in an instant. How teams react and how the game changes is crucial for live betting, but how do you measure the impact a goal has on how a team plays? Read on to find out.
It is no doubt vexing for Manchester United fans that their relative fall from the very top in the period immediately following Sir Alex Ferguson’s retirement has also coincided with Manchester City’s sustained rise in the European pecking order.
Mourinho has partly restored United’s status following finishes of 7th, 4th, 5th and 6th under a trio of managers, but still United’s current achievements suffer in comparison to the riches of trophies and entertaining style that was typical of the team under their former manager.
Why is it important to react after a goal?
No one has been able to match Alex Ferguson’s domestic record at Manchester United. One standout feature of his team was the ability to turn a losing position into points late in matches or get three points with a regular flurry of late goals when any other team would have ended up with a draw.
Anecdotally, it has been suggested that United’s knack of scoring important late goals may have originated on the training ground, where manufactured games were sometimes played with the players ignorant of the actual scoreline.
It certainly helped that United’s bench was among the strongest around, but the key success was the manner in which Ferguson managed the balance between the rewards of committing more resources to seeking an important goal against the risk of conceding at the other end of the field.
Understanding goal scoring patterns in soccer
The broad dynamics of a soccer match are well known. Single games or even entire seasons for some sides may deviate from the norm, but overall and in the long term many factors repeat. For detailed explanations on both short term and long terms factors you should consider as a bettor, read Pinnacle’s soccer betting advice articles.
It is important to note that the rate of goal scoring increases imperceptibly, but relentlessly as the game progresses in soccer - roughly 45% of goals are scored in the first half of a match and the remaining 55% in the second.
Over the long term you should expect a side’s chance creation and suppression to be at its most effective when that side is in a less favourable match position.
There is also a noticeable if small redistribution in the way in which future goals are shared between two teams compared to earlier in the game that is dependent upon the current scoreline.
Alex Ferguson may have been the master of the late comeback goal, but recent data will be more relevant to bettors analysing to what extent teams see a shift in the attacking balance of their matches when they are chasing the game or defending a precious lead.
The time remaining, the relative abilities of the teams and the current scoreline all contribute to how the remainder of a game might play out.
The large gulf in class between the current “big six” and the remaining 14 Premier League teams often causes problems when summarising season-long data.
A mid to lower table team trailing to one of the big six may want to be more risk taking to overturn a deficit, but often the opponent is simply too good and damage limitation, rather than actively seeking to get back in the match sometimes becomes the only realistic option.
Therefore, to see how Premier League teams react to different scorelines and in particular how they alter their strategy, examining the chance creation rates of non-top six teams when they faced other such sides will be most beneficial.
Goals are a relative luxury in soccer; the average Premier League match between mid-ranking teams rarely deviates much from an average of 2.5 per game - even over an entire season a side’s scoring and conceding record may not accurately reflect their core efforts.
Expected goals, which attempt to measure the chance quality that teams create and face has become an established alternative that draws on a larger sample size and better reflects a side’s process, rather than their often less repeatable actual goal output.
How to measure a team's change in performance
In 2016/17 Southampton finished the season in 8th spot with just 46 points, 23 adrift of Mourinho’s United in 7th spot - they headed a group of sides with 40 or more points that stretched down to Watford in 17th position.
The Saints spent around 57% of their matches tied level with their opponent against the non-top six teams, 27% of the time leading and 16% trailing.
In these 26 matches they averaged 1.8 expected goals per game and they conceded about 1.1 per game. This is consistent with Southampton’s 2016/17 team being very nearly the best of the rest in the Premier League.
To see if they deviated from these baseline figures by altering their risk/reward levels based on the demands of the current scoreline, we need to see if these expected goals rates (adjusted to a per 90-minute figure) alter with the current score differential.
Sir Alex Ferguson’s Manchester United team were at their most dangerous when they trailed in matches or were drawing games that they expected to take all three points from. The question is, can other teams also reproduce this, albeit to a lesser degree?
During the minutes Southampton were leading against non-elite rivals, they created chances that were equivalent to 1.7 expected goals over a full 90 minutes period.
When they trailed, they increased this rate to just under 2 expected goals per 90. So in keeping with many previous observations, trailing teams in general do “up their game”, in Southampton’s case in 2016/17 by around 17%.
A mid to lower table team trailing to one of the big six may want to be more risk taking to overturn a deficit, but damage limitation sometimes becomes the only realistic option.
Expected goals created is only one side of the competitive balance within a game. By committing players forward in search of a goal their opponents may choose (through risk aversion) or be forced into defending in larger numbers - this may in turn reduce their offensive creativity.
This appears to have been the case in Southampton’s games. They allowed the equivalent of 1.2 expected goals per 90 when leading, but when they actively took the attacking initiative when trailing their opponents were forced to (or chose to) play more conservatively and Southampton conceded just 0.9 expected goals per 90.
Southampton’s experience is broadly typical of most non-elite teams playing one another and can be neatly summed up by the expected goal difference per 90 of the Saints under different score lines.
When ahead in 2016/17, the Saints’ expected goal difference was 0.5 expected goals per 90, but when they trailed and the dynamics of the game required a response, they became much more dangerous, creating an expected goal differential of nearly 1.1 expected goals per 90.
Sir Alex’s Red Devils, it seems were hardly unique in their ability to play at another level when it was most needed, but they stood out because they were by far the most proficient at balancing risk and reward to achieve a favourable outcome.
And the lesson for bettors is, dependent upon the quality of opposition, over the long term you should expect a side’s chance creation and suppression to be at its most effective when that side is in a less favourable match position.