Current estimates are that nearly 100 million viewers tuned in to watch Seattle’s 43-8 win against Denver last night. Of course, there’ll be many reports that dissect the ways we watched the game, but for us, one particular area of interest is the prevalence of multi-device viewing. The concept of the “second screen”—people consuming media on multiple devices simultaneously—gets a lot of discussion these days, and sports sites are perhaps the best study in second screens. Sports fans still consume the vast majority of games on TVs but, while watching, they might also scan stats, highlights, and commentary on their phones, tablets, and computers.

That’s why I found myself flipping back and forth last night between a livestream of the game, my Chartbeat Publishing Dashboard, and an Emacs window, trying to figure out how online traffic varied throughout the night. Whereas on a typical night it’s hard to collate real-world events with online behavior, last night’s game was different. Whether you were watching online or on television, the commercials and game events happened at the exact same moment, which gave us the opportunity to watch second-by-second shifts in web traffic.

One of the most interesting observations was how much online traffic fluctuated before and after commercial breaks. Across sports sites, we saw upticks of 5% to 15% in traffic just as the game went to a commercial break, and that traffic drained off just as quickly when the game resumed play. That trend was present across every commercial break during the game. Perhaps unsurprisingly, the vast majority of those upticks were on mobile devices.

After watching that trend for the first half, I expected a similar increase in traffic during halftime. But, interestingly, halftime elicited exactly the opposite response; sports traffic dropped by 15% to 50% during the break, and the majority of that drop was on mobile.

Because it’s so difficult to know for certain that the same person is using multiple devices, most analyses of second-screen behavior have measured device usage via surveys. In this case, though, because we saw behavior that was so tightly coupled to events taking place on TV screens, we can start to get a sense of the scale of multi-device usage across the web. And, with patterns in usage as strong as we saw, it’s clear that a large portion of people tuning in were actively engaged on second screens in response to game events.