UFC 106 Pay Per View Prediction: Tito Brings Attention
Original source version over here on Tapology.com.
UFC 106 is live on pay per view this Saturday night from the Mandalay Bay Events Center in Las Vegas, Nevada. While the cancellation of a Brock Lesnar vs. Shane Carwin heavyweight title fight took away the blockbuster potential of the event, the Tito Ortiz vs. Forrest Griffin bout that now takes top billing should still deliver a solid night of business for the UFC. Ortiz in particular has long been a pay per view machine, and based on his pre-fight fan buzz heading into Saturday, Tapology is predicting a healthy 510,000 buys.
We have slightly updated our method of making predictions since UFC 104, and are now using an absolute “buzz score” rather than a percentage “buzz share” for the forecast. The higher each fighter’s buzz score, the more people who have been searching and reading about that fighter online in the days leading up to the event.
Tito Ortiz receives by far the highest score of the main event and co-main event participants at just over 30. With his tabloid news presence and trash-talking expertise, Ortiz is generating serious online buzz as he prepares to make his UFC return. Griffin’s score is about half that of Ortiz but still respectable, while Anthony Johnson and Josh Koscheck add a moderate amount of kick for a co-main event.
| Fighter | Pre-Fight Buzz Score |
|---|---|
| Tito Ortiz | 30.6 |
| Forrest Griffin | 16.2 |
| Anthony Johnson | 9.3 |
| Josh Koscheck | 7.8 |
| Total | 63.9 |
Over the past five UFC pay per view events, the pre-fight buzz scores have been a strong predictor of performance with a relatively tight relationship between the scores and the ultimate pay per view figures.
The glaring exception is UFC 104, where Lyoto Machida single-handedly generated enormous online pre-fight buzz, and yet this activity did not fully transfer over into pay per view results. Our theory is that Machida had been on the cusp of stardom with immense casual fan curiosity, but that the prospect of an all-Brazilian main event was not quite accessible enough for many of those fans to place the order. Therefore despite UFC 106 coming in with a lower buzz score than UFC 104, we are sticking with the model’s prediction of 510,000 buys, which if accurate would out-do the results from the Machida-Rua card.
| Event | Main & Co-Main Event Pre-Fight Buzz Score | Reported Pay Per View Buys |
|---|---|---|
| UFC 100 | 156.9 | 1,720,000 |
| UFC 101 | 83.1 | 850,000 |
| UFC 102 | 46.6 | 435,000 |
| UFC 103 | 56.2 | 375,000 |
| UFC 104 | 81.1 | 475,000 (preliminary) |
| UFC 106 (forecast) | 63.9 | 510,000 |
Pay per view buyrate estimates are based off of the great reporting and analysis that can be found at MMAPayout.com.
Tapology’s buzz rankings are a measure of fan interest and activity. Tapology uses data from Compete Inc to measure the level of internet users checking out over 800 of the biggest names in MMA. Activity is aggregated across multiple websites and represents United States fans only.The FanPosts are solely the subjective opinions of Bloody Elbow readers and do not necessarily reflect the views of Bloody Elbow editors or staff.
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I think you’re a little crossed up there, UFC 104’s buyrates outdid most expectations proving that if anything Machida is taking off with fans in a way that Anderson never has until he fought Forrest who’s a big draw.
yes, 104 outdid some people’s expectations, but not ours. it’s way out of line in terms of the relationship between online activity (“buzz”) and the number of buys that it did.
the amount of online/buzz activity for 104 was almost at the level of 101. but 101 ended up doing almost 2X as many PPV buys. so, that is why 104 stands out and why we call it a glaring exception above.
www.tapology.com | twitter @tapology
You’re better off simply getting a connection with some cable providers in different markets and you’ll see a clear correlation by fight day.
Dana knows exactly how a fight will do on the day of the show by simply looking at the pre-orders. The projection ends up being very close.
The metrics you are using will be right sometimes and be wrong sometimes and because their are other factors at play.
If you just want to use public data then you have to use all of them and combine them with different “weights” to come up with a clear correlation. With back testing you can do that. (Time of year should also be in the mix, you should also look at hollywoods box office openings, Television competition for each past show, etc…)
I get your point but UFC 104 was never going to match what UFC 101 did anyone with any knowledge of the sport could tell you that. So something went wrong along the way because things didn’t add up it’s like if I predicted that UFC 103 would do bigger than UFC 106 anyone can clearly see that was never going to be the case.

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