By The Numbers
■ No. of documents analyzed: More than 6,600
■ No. of markets studied: 23, in 15 states
■ No. of big league teams in those markets: 72 (including MLS expansion teams in Atlanta and Orlando)
■ No. of network affiliates: 87
■ No. of ads: 2,439
■ Total spending: $14.52 million
Methodology
Like the candidates themselves, SportsBusiness Journal began preparing for Election Day back before the polling booths for state primaries had even opened.
A database of candidates, political action committees and network affiliates was set up in early 2014. We then, in March, began tracking the spending of candidates during sports programming.
We elected to track general election races that would be held in any U.S. market that was home to at least one MLB, NFL, NBA, NHL, MLS or WNBA team. From there, we narrowed our focus to the races within those 45 markets that were, at the time, projected to have at least one highly contested race at the federal or gubernatorial level. To establish this criteria, we used polling data available online by RealClear Politics, Huffington Post, FiveThirtyEight, Rasmussen Reports and local media.
The Federal Communications Commission requires local ABC, CBS, NBC and Fox affiliates to provide detailed contract information about their political advertisers to the FCC.
As a result of those filters, the filings included in our study began with ad purchase orders placed on March 19, the day after Illinois’ primary closed — Illinois being one of the nation’s early primary states — and continuing with orders placed through Oct. 22. While the contract cutoff date was Oct. 22, that’s not to say the data reflects advertising only until that date. Purchases made on or before Oct. 22 for ad time after that day were included in our research — and not surprisingly, there was a large volume of ads due to run between Oct. 22 and Election Day: 22 percent, to be specific. That’s how many of the 2,439 ads purchased on or before Oct. 22 will run between Oct. 22 and Nov. 4.
When the dust settled, we had analyzed more than 6,600 contracts, invoices, revisions and rebates involving 30 different political races in 23 big league markets in 15 states.
But from the airing of the first spot that we tracked — a $2,000, 60-second ad during coverage of the French Open bought by Georgia gubernatorial candidate Jason Carter that aired on WXIA-NBC in Atlanta — to an onslaught of buys in the final days of the process, there were many obstacles. For example, some candidates secured spots during sports programming as far as four months in advance, only to adjust them once teams’ television schedules were finalized, or fully reviewed. For example, the Florida Democratic Party in July ordered a spot on both ends of a Sept. 7 CBS NFL doubleheader in Jacksonville, only to be told by the station in late July that there was no Game 2 on CBS that week. Similar scenarios occurred throughout the fall, as candidates blindly ordered “all prime-time college football” or “one per every NFL game.” Other times, Mother Nature fooled with the ad cycle (rainouts affected some MLB games and U.S. Open tennis coverage), and an occasional sweep in the MLB playoffs meant some planned late-series ads had to be moved or refunded by the affiliate.
In Ohio, the governor’s race was expected this spring to be closer than it now appears to be, but we kept tracking the state because the incumbent kept buying ads, and because we found that Cincinnati stations were generating revenue as a result of the neck-and-neck Kentucky Senate race as well. Additionally, a runoff in Georgia and a late candidate withdrawal in Kansas disrupted the selling process for several affiliates.
In regard to the physical filings themselves, the FCC does not have a standard template for stations to fill out, and there is little continuity across the filing landscape. And because all the data provided to the FCC is entered manually at the individual stations, there were frequent contract revisions (sometimes because of input errors) and make-goods that had to be accounted for in the research so as to include them in our tabulations as well.
The research presented here was compiled and analyzed by David Broughton and Brandon McClung.
