Van Persie, has so far out performed the model by scoring slightly more goals than you would expect from an average player. However, such is the limited sample size for the Dutchman, it isn't possible to use data from the four matches he has played so far to demonstrate without doubt that he is an above average striker.
An inferior striker (if we assume from extensive evidence over the longer period of van Persie's career that he is indeed above average) could quite easily have scored the three goal total already achieved by van Persie in 2013/14. So in the absence of a larger cv, an elevated strike rate compared to a generic shooting model shouldn't be regarded as evidence of better than average talent. Data evaluations of playing talent will always come with levels of uncertainty, rather than cast-iron conclusions.
Shot data accumulates more rapidly for teams than for individual players and following Liverpool's 1-0 home defeat to Southampton, the Merseysiders had executed 63 attempts in scoring 5 times. The overall, model predicted, goal expectancy from all 63 shots is total just under five goals. Therefore, it is no surprise to see that the most likely individual goals tally recorded by an average side if they had been given those 63 opportunities is also five.
There is a 20% chance of an average team scoring five goals and a shade of odds on that a side would score at least five goals given Liverpool's opportunities. So we can tentatively say that over the first 63 chances created by Liverpool, there has been little surprise in their conversion rate. Everything that has happened once the chances presented themselves could reasonably have been duplicated by an averagely competent converting side.
Liverpool's shooting accuracy, however, is more extreme. The model predicts an average of just under 20 of the 63 goal attempts to have been on target and Liverpool so far have hit well in excess of that prediction with 27, making them the joint second most accurate shooting side in the EPL in 2013/14.
An over-performance of 40% in hitting the target 27 times compared to an expected 19.6 does appear outstanding and can easily give the impression that we are looking at a real and possibly sustainable effect. The temptation is to look to causes and explanations. But first we perhaps should see how unusual such a rate is for our baseline, average side to have achieved in 63 trials.
In simulations assuming an average level of all round competence, 27 shots are seen to hit the target around 1.5% of the time and at least 27 shots were recorded about 5% of the time. Certainly unusual, but not within the bounds that could be considered significant. On the evidence of 63 shots, Liverpool may be more accurate than an average side, but by quoting the 40% improvement over average, (especially if sample size is omitted), an inflated expectation of their true ability is almost certainly being created.
So, in statistical terms, there is a justifiable reason to suppose that, despite an impressive accuracy rate, Liverpool may be little better than average in reality.
Previous seasons and repetition of this inflated accuracy by broadly similar Liverpool teams of the recent past, is one route to adding weight to any opinion regarding Liverpool's shooting accuracy. But intimate knowledge of the shooting model that has been used is another. The model I've used includes many of the readily collectible variables, such as shot location, shot type, but it doesn't include such things as shot power, which are both subjective and virtually impossible to collect in any great numbers.
In the limited data I have, the power of the shot impacts negatively upon the accuracy, and yet increased power doesn't appear to statistically significantly improve conversion rate compared to normally struck efforts. (Placement is the obvious missing link). Therefore, (with the caveat that this is very limited data) you can construct a scenario, where reducing the power of a shot, doesn't reduce the conversion rate, but increases the accuracy and a shot extra saved is an extra possibility of a further shot attempted from an additional rebound. The exact profile seen at Liverpool this year.
Models can tell us much about how teams perform, as long as we aren't too dogmatic about conclusions. Ultimately, they just provide information on how likely it is that a real, data based assessment is going to coincide with an unobtainable, all encompassing knowledge of a side's true ability. Random variation can turn world beaters, short term, into average, run of the mill sides and vice versa. But equally (as in the proposed effect of shot strength), seemingly unusual results can be an early indication of a model depleted of minor, yet important variables.