That's a great demonstration on why you shouldn't rely too much on statistics.
Both the Force & the Reds are statistically better then the Tahs,yet they were both man shamed by the Tahs.
This has got to be a Michael Foley statistic.Someone scored a bonus point win against your doughnut,and you find a measure to demonstrate that you were superior to them.
How come despite the stats,both the Reds & For e are juicy odds this week,and the hapless Brumbies are favourites against the Unbeaten Tahs?
You're right ILTW. These stats particularly: they derive from a tiny number of games, some teams have played a third less games than others so far, and the large cluster of team results around the high eighties as a % outcome highlights no real performance differentiation that's meaningful at this juncture of the comp.
Moreover, there is a massive problem with the widespread use of 'individual event or attribute' based rugby stats. Namely, and USARugger rightly notes this above, they are event isolates and the degree to which they actually correlate (or not at all) with the real performance outcomes that matter - points scored (or not) via
a linked chain of performance events, potentially a very long chain - is totally unexamined and unrevealed by these types of isolated measures.
The only and right way to fix this would be invest in properly sophisticated rugby match databases, big deep-correlation-oriented stats models, and large computational resources of a type that could be used to reveal the far more powerful 'long chain correlations' whereby a huge range of team and player stats are combined over 80 mins or segments thereof in chain correlated form to yield what performance events
in dynamic combination created the most points, or end up conceding the most points. To my knowledge, this has never been done for rugby at any level - and indeed it'd be a big task to get the foundation of these types of analytics in place.
I am not saying that the isolated event stats we have are totally useless, they can highlight over a season some useful observations. But, other than superficially, they by no means reliably explain a team's total rugby performance or even why teams win certain matches and not others, or win more matches than opponents over time.