Complete Halftime Analysis

Most halftime shows include comments from former players and coaches about how teams must “pick up the intensity” or “step up” in the second half. In basketball games, analysts talk about strategies like “getting the ball inside” or “taking better care of the basketball.”

While such input from former players and coaches is valuable, it is far from complete analysis. You need to get into the numbers for that to happen. Sports analytics provides powerful insight and doesn’t need to involve anything complex. The concept of regression to the mean reveals far more about what to expect in the second half, and only requires comparing a few key stats.

Let’s say one team shoots 8-for-10 from three-point range to grab a 10-point lead while the other clanks 1-for-9. If both teams entered the contest shooting 40 percent on the season, it is almost certain that both teams regress to the mean – the 40 percent mark – in the second half. Defense impacts these stats, but randomness (or luck) is a huge factor in small samples. As more shots get taken, teams should move toward their season percentage and cause the score to tighten up.

Free throw percentages are another great stat to examine at halftime. Unlike three-pointers, they aren’t defended. So randomness plays an even greater role.

I believe broadcasts will soon have a statistical expert offering such insight – alongside coaches and/or former players – on halftime shows. But until that happens, we can all do it ourselves.

Sports Statistics as a Marketing Tool

Politicians discovered the power of numbers long ago. One might say “my administration created one million more jobs than any other in history.” Of course, it only takes a few minutes to pick that apart: How many jobs were lost? What was the net increase? What was the percentage increase? What was the average salary of these created jobs? But by the time his statement gets scrutinized, the politician moves on to the next talking point.

The same thing works in sports. In 2009, when Colt McCoy was a top Heisman Trophy candidate, the media repeated this statement over and over: “McCoy has won more games than any quarterback in college football history.” Wins are powerful, the true currency of sports. The stat spread everywhere and stuck in people’s minds, even though it was not a particular good statistic.

McCoy won more football games partly because he played in so many. Longer seasons and conference title games gave him more opportunity to record victories. Yes, he won the most games of any quarterback, but he was one of 22 starters. And many of those former teammates have joined him in the NFL.

Obviously it took a great quarterback to win that many football games. McCoy had to earn the starting job and keep it four years; no easy feat at a top program. He had a major role in 45 wins. Nonetheless, teams win games, not quarterbacks.

The McCoy stat still got extensive airtime on sports talk radio, highlight shows and game broadcasts. As with a smooth-talking politician, there was little opportunity in those settings to contradict it with objective evidence.

This demonstrates the power of numbers. Since few people effectively use sports statistics as a marketing tool, they present a blank canvas to work with. And the timing couldn’t be better with the rise of social media, when you may only get 140 characters to send a clear powerful message.

If even bad stats have value, can you imagine the impact from innovative statistical content? Finding this isn’t easy – as the best information lies beyond the core stats that dominate the mainstream sports media – but it is well worth the effort.