By: Edward Egros

cowboys

A New Explanation of Cowboys Graphics

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For the second-straight year, after every Dallas Cowboys game, I will post a recap of the game with an analytic visualization. Once again, these metrics sum up all of the important factors that determine the outcome of a football game. Some of the metrics are the same, while others are more refined and better reflect certain concepts.

Going from the top and working down, once again I will chart turnovers, one of the more impactful statistics in the game. The numbers reflect the turnover margin and the bars reflect how many turnovers were committed.

The next box will look at how the quarterbacks performed, often looking at
net yards per pass attempt. This metric is highly predictive; and while others may be more predictive, it is also far easier to calculate.

Perhaps the biggest change comes where it is labeled "Time of Possession/Rushing Yards". This metric was designed to determine who "controlled" the game. It has since been updated to look at how many rushing yards a team had per quarter.
As noted in a previous blog post, the more rushing yards a team scores later in the game, the likelier they are to win. The larger the number, the better that team "controlled" the game.

Overachiever/Underachiever refers to what the Cowboys' record should be, relative to their point differential for the whole season. In baseball, this idea is referred to as the
Pythagorean Expectation. In football, there is debate as to how to calculate such a record, but here, the exponent is 2.37: ((Points for^2.37) / (Points for^2.37 + Points Against^2.37)) * 16.

Finally, scoring efficiency has been tweaked. The idea here is to see how many points teams scored, relative to the number of yards they needed. The larger the bar and the bigger the number, the more efficient the team was. Simply put, it's points divided by yards, then multiplied by 15.457886 so that average is approximately 1. Using data from 2009-2016, we can also see if a team was overall good, average or bad in its efficiency. If the result is less than .949394, the team was inefficient. If the result is between .949395 and 1.057116, the team was average and gets a blue bar. If the result is greater than the aforementioned range, they were efficient and get a green bar.

Again, these metrics are meant to capture nearly everything that happened in a game that pertained to the result. Some of these metrics can also be used to forecast future games, but the intent is solely inference.

A Unique Cowboys Perspective

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The Dallas Cowboys are constantly watching film and studying the playbook for that added edge. Their fans also want to know anything that can help explain why their favorite team won or lost, and if there is a way to forecast how they will do and where they need to improve. Our newest data visualizations hope to do all of the above.

Before and during every Cowboys game, I will post on my various social media accounts some analytics that explain what is going on and predict what will happen. After the game, I will have one summary detailing what happened, using explanatory variables that are the best indicators for the outcome of any football game. Here is some extra information for each highlighted variable:

  • Turnovers are perhaps self-explanatory and the team with the better turnover ratio has a significant advantage.
  • Scoring efficiency goes beyond just the scoreboard. It's a ratio of (offensive yards/points). A team may have moved the ball but failed to score many points when near the end zone, so they were inefficient. Not only can each team's efficiency be compared, but each bar has a color: red for bad, blue for average and green for good. Respectively, these quality ranges are: 0-12, 12.01-18.5, 18.51-. These ranges came from the last ten years of NFL data, provided by Pro Football Reference.
  • The ratio (time of possession/rushing yards) looks at who was controlling the game effectively. Time of possession is not an effective indicator for success, but how well a team controls the ball while on offense is. The team with the better ratio earns the checkmark.
  • Overachiever/underachiever is a way to look at how well a team is doing for the season, relative to its point differential. In other words, if a team is has a strong record but all of their wins are close, they are overachieving. If they suffered a number of losses but they have been close, they are underachieving. This idea is calculated using a Pythagorean Expectation formula, something more commonly used in football: ((Points for^2.37)/(Points for^2.37 + Points against^2.37)). This winning percentage can then be multiplied by the number of games played to show where a team "should" be with its record.

Periodically there will be additional metrics to explain why the Cowboys won or lost, such as net passing yards/attempt, which takes into account sacks and incompletions as well as how many passing yards each quarterback is able to accrue. As more metrics become readily available, this summary will include them. To see these visualizations in real time, follow me:


Special thanks to
Fuzzy Red Panda for putting together these beautiful images and programs that advance sports analytics in such creative ways.

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