Every team in pro sports has a social media operation now. Most also have a vague sense that the activity matters. What very few teams have is a number. How many tickets does a tweet sell? What's an Instagram follower actually worth, in dollars, today?
For a Major League franchise, the question wasn't academic. Social activity had shifted significantly between seasons, and leadership wanted a financial answer — to defend social investment in budget conversations and price the audience appropriately when partners came to the table.
The Hard Part: Isolating Social
Social posts don't happen in a vacuum. Posting volume spikes during the season, when ticket sales spike. Paid media runs alongside organic. Team performance — by far the largest driver of ticket revenue — moves in ways the social calendar follows. We built an econometric model on weekly ticket transactions and weekly posting activity, controlling explicitly for paid media spend, in-season vs. out-of-season effects, team performance, and seasonality.
The relationship between social and ticket revenue is real, but it lives underneath three or four other things that move at the same time. The job is peeling those off.
An early decision was whether to model each platform separately or treat social as a combined effect. Posting activity across platforms is highly correlated, and follower overlap is significant — the same fan is on Instagram, Facebook, and X. Modeling them independently would overstate each one's unique contribution. We treated social as a single coordinated activity, with YouTube and TikTok modeled separately given their less correlated audiences.
What the Model Found
social's contribution to revenue
across major platforms
between posts and revenue
The model suggested social activity drove between 7.5% and 17.5% of ticket revenue, with a wide confidence band. We recommended planning against the lower end of that range — better to underclaim and overdeliver in a finance conversation than the reverse.
One finding worth pulling out: the relationship between posting and ticket revenue was actually stronger out of season than in season. The slope of the line was similar in both periods, but the in-season relationship was noisier. So many other things move during the season — winning streaks, individual player news, weather — that the marginal impact of any single post is harder to see. Out of season, when those signals quiet down, social's signal stands out.
From Aggregate Lift to Per-Follower Value
Once you have a defensible estimate of social's revenue contribution, the next step is dividing it across the audience. The team had roughly 1.5 million followers each on its two largest platforms, but those audiences overlap. We ran a simulation drawing on platform-overlap studies to estimate total unique followers — about 2.5 million, not the 3 million the platform-by-platform sum would suggest. Dividing modeled revenue contribution by unique audience produced a per-follower value the team could use both internally and in partnership pricing.
The methodology generalizes well past sports. Any organization with a meaningful social audience and a measurable revenue outcome — DTC retailers, subscription services, hospitality, media — has the same underlying question. The harder pieces aren't the regression itself. They're the framing decisions: which channels to combine, what to control for, how to translate aggregate lift into a per-unit number.
Thinking about how to value your social audience or social investment? Say hello.