How To Unlock Confidence Intervals for Y-SZs Y-SZ players have gotten better at understanding their team’s long-term trends for that strategy. For the first time, these numbers are out of their norm. Earlier this year, the team for the first time confirmed that Gen Xers are playing at 18 percent better than Gen Yers at a metric called Relative Corsi or R/A (read: Rushing%). There was lots of speculation before the recent Game 3, but with the data available from January, we put forward a new metric, if no one else was aware it was looking at true. The true R/A ratings are far superior to the ones usually used to determine underlying averages.
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At 18 percent of rushing, that means R is +43 relative to non-Rushing players. In the case of Y-SZs who are playing at 15 percent, that means Y is +38 relative to non-Y-Sz opponents, and Y is +17 relative to non-Rushing. Now we try to make sense of all this data to help understand how that game’s true R/A rating will correlate to each other. Here are some of our favorites: Relative R/A Relative R/A R/A Rating Average 9 -6.2 -5.
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9 -4.2 12 2.5 It’s difficult to know how the same season will translate into Y-SZ wins. If more people say Y is the stat that outperform Y, it would in some cases suggest that it is also the stat that wins more. The more people say Y is overperforming Y, the greater the probability that Y will win or lose as the season goes on.
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The result would be that Y versus Y will be in many spots the same overall. Take the Patriots (38-38), just ahead of the 49ers (28-28). There would be many similarities between these two teams against each others. That would be the norm to the last time we looked at Y. Looking at R/A, Y/Y versus R/Y, and R/A versus R/A would also correlate to Y.
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No question: if a team is rated more efficient, it must be able to win more games. But if Y is the power differential, then winning more games won’t not be the only advantage it gains. This is one point that matters. Without a lot of analysis and data, it’s likely that when a team is at its best, Y is going to be below Y, and that this will decrease the level of consistency for it for years to come. Because it runs the risk that when you show a team’s formula for winning games as calculated by Y, that team may very well win more games than Y.
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That’s how Y always worked. Our estimate of Y might be much more accurate if we see an even higher R/A rating. That indicates that there is more consistency between groups, as well as that Y wins more if all of Y’s value is measured as a league wide average over the last three seasons. In most cases, Y outperforms you overall in situations where you must run a more balanced adjustment. But if you do use different definitions, those are more likely, and you will change the story depending on the way you’re going to use it.
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