The "xPI" formula is really just an extension of the power ratings we use to determine the strength of teams competing in today's NFL. Revising some of the calculus as it relates to seasonal average, and accounting for the variance in height and more significantly, weight, between teams that competed in seasons from the early 1980s to the presnt day, we believe we've developed a metric that gives a solid
Underwriting everything we're trying to do is getting an absolute global atemporal valuation of every pro football team to have competed in the NFL for the last 25-30 years, when there wasn't such a discrepancy in the size of players playing the game. And yet a valuation that possesses the kind of scope, incorporates a near-inexhaustible number of factors, and ultimately possesses the kind of broadness that supports the realistic comparison of a team from the 1970s with the 2018 Kansas City Chiefs. For example.
And so we devised the +xPI. The “x” signifies cross by the way, meaning a valuation that works and operates successfully across multiple years and decades; whilst the “PI” represents Power Index.
The main challenges with an endeavour like this was identifying the means by which to grade what a team was doing – and doing successfully, in 1982, with that same thing a team was doing in 2016. Then there was the disparity in weight and size, something else that had to be satisfactorily solved.
Work in the SEASONAL-AVERAGE at scoring, or pass yards, as the basis to determine how better a team's performance is, as opposed to pure comparison between Team A from 1981 and team B from 2016.
Underwriting everything we're trying to do is getting an absolute global atemporal valuation of every pro football team to have competed in the NFL for the last 25-30 years, when there wasn't such a discrepancy in the size of players playing the game. And yet a valuation that possesses the kind of scope, incorporates a near-inexhaustible number of factors, and ultimately possesses the kind of broadness that supports the realistic comparison of a team from the 1970s with the 2018 Kansas City Chiefs. For example.
And so we devised the +xPI. The “x” signifies cross by the way, meaning a valuation that works and operates successfully across multiple years and decades; whilst the “PI” represents Power Index.
The main challenges with an endeavour like this was identifying the means by which to grade what a team was doing – and doing successfully, in 1982, with that same thing a team was doing in 2016. Then there was the disparity in weight and size, something else that had to be satisfactorily solved.
Work in the SEASONAL-AVERAGE at scoring, or pass yards, as the basis to determine how better a team's performance is, as opposed to pure comparison between Team A from 1981 and team B from 2016.
In 1748, when defining causation, David Hume referred to a counterfactual case:
"… we may define a cause to be an object, followed by another, and where all objects, similar to the first, are followed by objects similar to the second. Or in other words, where, if the first object had not been, the second never had existed …" — David Hume, An Enquiry Concerning Human Understanding.
Counterfactualism is the view that dispositions are a type of counterfactual property.
Reasoning
Experiments have compared the inferences people make from counterfactual conditionals and indicative conditionals. Given a counterfactual conditional, e.g., 'If there had been a circle on the blackboard then there would have been a triangle', and the subsequent information 'in fact there was no triangle', participants make the modus tollens inference 'there was no circle' more often than they do from an indicative conditional (Byrne and Tasso, 1999). Given the counterfactual conditional and the subsequent information 'in fact there was a circle', participants make the modus ponens inference as often as they do from an indicative conditional. See counterfactual thinking.
Experiments have compared the inferences people make from counterfactual conditionals and indicative conditionals. Given a counterfactual conditional, e.g., 'If there had been a circle on the blackboard then there would have been a triangle', and the subsequent information 'in fact there was no triangle', participants make the modus tollens inference 'there was no circle' more often than they do from an indicative conditional (Byrne and Tasso, 1999). Given the counterfactual conditional and the subsequent information 'in fact there was a circle', participants make the modus ponens inference as often as they do from an indicative conditional. See counterfactual thinking.