It's a great piece of work from Constantinos and Liverpool's split personality when playing very well against title contenders and Everton compared to when they do less well against lower class teams has generated much speculation.
These have generally fallen into two mutually exclusive groups, either narrative based tactical flaws of Klopp and Liverpool or odds based simulations that attempt to explain away the split as mere randomness.
It is unlikely that either approach will wholly account for Liverpool's apparent failure to dispatch mid and lower table teams with the authority they appeared to preserve for the league's stronger sides.
Football is awash with randomness as well as tactical nuances, so it seems much more likely that a combination of factors will have contributed to the 2016/17 season.
It's a simple task to simulate multiple seasons, often using bookmaker's odds as a proxy for team strength to arrive at the chances that a side, not necessarily Liverpool might exhibit a split personality.
However, it's a stretch to then conclude that either chance was the overriding factor or it can be excluded as a cause merely because this likelihood falls above or below an arbitrary level of certainty.
There is so much data swirling around football at the moment, particularly ExpG, that it seems helpful to use these number to shed some light on Constantinos' intriguing observation.
Rather than a pregame bookmaker's estimate a a side's chance, we have access to ExpG figures for all of Liverpool's 2016/17 matches.
ExpG have arisen from the tactical and talent based interaction that took place on the field and spread over 90+ minutes of all 38 games they perhaps provide a larger sample of events with which to explain a series of game outcomes, rather than simply using 38 individual sets of match odds, however skillfully assembled.
One aspect of a low scoring sport, such as football, where ExpG struggles is how teams adopt different approaches to achieve the aim of winning the most available number of points.
A side may take a fairly comfortable lead early in a contest and then chose to commit more to defence against a weaker or numerically deficient opponent.
An extreme case was Burnley's win over Chelsea, where early actual goals allowed the visitors to concede large amounts of ExpG and just few enough actual ones to handsomely lose the ExpG contest, but win the match.
ExpG figures are inevitably tainted by actual real events, such as goals and red cards, but it is still at its most useful when used in conjunction with simulations to attempt to describe the range and likelihood of particular events occurring.
Scoring first (and 2nd and 3rd, along with Chelsea going down to 10 men) was a big assistance to Burnley and Andrew Beasley has written about the importance of the first goal here, for Pinnacle.
If we look at the size of the ExpG figures for all goal attempts in a game and the order in which they arrived, there may be enough data that is not distorted by actual events to estimate which side was most likely to open the scoring, allowing them then to be able to more readily dictate how the game evolves.
In games against the 13 lowest finishing teams, Liverpool took the initial lead 16 times, compared to a most likely figure of 15.
With the interaction of attempts allowed and taken, Liverpool ended up 1-0 to the good or bad or goalless throughout about as often as their process deserved.
They fared much better against the top teams.
In those 12 games Liverpool took the 1-0 lead nine times compared to a most likely expectation of just six based on the ExpG in their games.
It was around a 7% chance that an average team repeats this if Liverpool carve out and allow the chances for them.
It's understandable to look to the heights that may be achieved, rather than the lowly foothills left behind.
But based on Liverpool's 2016/17 process from an ExpG and first goal perspective, perhaps their relatively disappointing record against lower grade sides is not the outlier, but rather their exceptional top 6 results are.
Scoring fewer first goals than they actually did in these top of the table clashes would likely decrease their ppg in these games, while inevitably increasing those of their six challengers.
This would shift the top six group gradually to the right in the initial plot and Liverpool slightly more substantially to the left until they perhaps formed a more homogenous group with no outlier.
It's traditional to wind up with "nothing to see, randomness wins again", particularly when one set of data is taken from a small, extreme inducing sample of just 12 inter connected matches per team.
But we now have the data, a place to look and video to see if there is some on pitch, if possibly transient cause to the effect of Liverpool finding the net first in big games or if the usual suspect in Constantinos' mystery does indeed turn out to be the major guilty party.
All data from @InfoGolApp
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