Data analyst Karl Knapp used the Bigfoot Forums database (U.S.) to create a breakdown of information contained in a collective of almost 7600 reports of encounters. Here is what he found.
Go to Bigfoot Sightings Tableau page for the tables.
The tables break down the data in various ways including location by state, setting, time of year, and details about the sighting (height, stride, evidence obtained, etc.). It’s worth having a look but as with all data sets, it’s important to recognize where the information is coming from and that this is not scientific data.
First, as with all reporting, the web made it far easier to share and document an experience. Reporting of anomalies is now easier and more common than ever. It’s a guarantee that we will have more Bigfoot reports in the Internet age (post-1992) than before it. Considering who uses the web, we might expect to see more younger people reporting and the database reflects that. (The majority of reporting respondents’ age is given as 20 yrs or under.) Younger people will also have less experience in the outdoors and be generally more open to talking about mysterious encounters.
A Bigfoot database implies that the reports are made by people familiar with Bigfoot so the data, obviously, will be entirely biased towards this interpretation as a Bigfoot sighting. The witness (or collector) would have to connect the sighting with Bigfoot and then report it to a Bigfoot database. But, it’s not clear to me how these data were collected. Being that a few reports are pre-1960, I assume that historical records were used. In those cases, we would not have as much detail provided. Because this isn’t a standardized survey taken over many years, we can’t say that Bigfoot sightings have increased or decreased. The number of the reports is biased based on many factors.
Data reflects Bigfoot in the popular view
The data says nothing about the legitimacy of each report or if the sighting was a mistaken ID or a hoax. However, the data may say quite a bit about Bigfoot in popular culture. In other words, people are more likely to report encounters with a thing if they have a name and some descriptive information about the thing.
I particularly liked this table, regarding the number of sightings per year.
We see a rise during the prime years of the 1970s paranormal media popularity. As expected, the Patterson-Gimlin film (late 1967) would appear to be a spark for a rise in reports. In the mid-1970s, there were multiple TV shows that introduced people to the concept of Bigfoot. Around 1994, there was another surge in paranormal-themed TV shows. (For a chronology of shows, see Hill, 2017). I haven’t dug into what may be responsible for the upticks in 2000 and 2004. 2006 appears to be the top year. 2011 was the start of Finding Bigfoot on Animal Planet. Note we see an uptick in 2011 and 2013 before things start to decline. The data ends in August of 2021. A reasonable hypothesis to explain some of these data is that reports increased based on the public awareness of Bigfoot. Public awareness is tied to media prevalence. I’d bet these upticks are in some way related to TV or movie releases.
Also interesting is the “hotspot” map. We see the traditional Sasquatch areas of Washington, Oregon and Northern California. Also notable is the plateau region of Arizona. Particularly interesting is Westmoreland County of Pennsylvania. A heavily wooded, rural area, this zone is part of Chestnut Ridge which is famous for UFO sightings and other high strangeness. Researcher Stan Gordon has been collecting reports of unusual events in the area for decades, which could be viewed as a collector’s bias. (But, again, I’m unclear how the data gets into the database. Yet, we can’t disregard the strong local knowledge that influences an interpretation of an encounter.)
Overall, this data visualization would be more useful if we knew there were actual Bigfoot creatures out there. Because we don’t know what is represented in each of these reports, it’s hazardous to merge them together and say they reflect a Bigfoot population. Weak data combined together doesn’t create a strong signal. Great caution should be used in interpreting this data to any conclusion. At best, we can say that the data generally reflects the public awareness of Bigfoot. And, in certain locations, people seem more likely to interpret a strange encounter as a Bigfoot encounter.
A similar approach, using BFRO data, was done in 2013 by Joshua Stevens.
Additional insight into these data sets is welcomed.
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