College luck

[upperdeck]

Bill Connelly had a story today on college luck last year. In it he talks about Turnovers/Injuries/Expected win %/wins in 1 score games

I scroll thru his numbers for SU. Some games make sense like Pitt. But he has us at 50% chance to win the Cal game.

Looking back we outgained them by 100 yds. We led by 2 scores almost all game. Really 1 long run from Cal away from being up almost 30pts.

We had the ball almost 20 more min. led in every stat.

It also falls into his 1 score game luck because Cal scored with 1 Min to go.

Much the same as the UNLV game. Out gained them by 150 yds, FDs by 15 yet only 40% chance to win. UNLV got multiple kicking game things to even stay in the game.
Sure we came back late, but UNLV got a ton of fluky plays.

 

[LeMoyneCuse]

That's the value of a guy like Bill C. Trying to quantitatively capture the flow of the game beyond the box score.

 

[upperdeck]

I get that. but at what point in the cal game would people be thinking su was lucky to be ahead by 2 scores . that's what his metrics are saying.

 

[CbusCuse]

To me It sounds like his win% etc. are based on what the metrics for both teams were at that point or maybe even end of the year metrics and not what actually happened in that specific game.

 

[richmondcuse03]

I get that. but at what point in the cal game would people be thinking su was lucky to be ahead by 2 scores . that's what his metrics are saying.

It's not perfect and can be skewed by games like that. It's an imperfect metric.

 

[LeMoyneCuse]

I get that. but at what point in the cal game would people be thinking su was lucky to be ahead by 2 scores . that's what his metrics are saying.

That's not what the metrics are saying. The metrics are saying that given the way the game was played, if it was played a thousand times, you'd expect Cal to win 50% of the time.

From a 2017 write up about his metrics: In its current state, S&P+ is based around the core concepts of the Five Factors of winning football: efficiency, explosiveness, field position, finishing drives, and turnovers.

Cal was more explosive (two 50+ yard touchdown runs), finished drives better (Cuse had 4 field goals and 2 punts, while Cal attempted 2 field goals and had 2 punts), and was slightly more efficient (based on total yards vs. time of possession). Turnover margin went in favor of Cuse, while field position was likely even.

Connelly works out of the macro, so his data points suggest that this game had several factors that could have swung it the other way.