WEBVTT 1 00:00:00.040 --> 00:00:01.600 Today, I want to tell you about a journey that 2 00:00:01.600 --> 00:00:03.879 I've been on for most of my life. Ever since 3 00:00:03.919 --> 00:00:05.799 I was a kid, I've heard tales of bigfoot and 4 00:00:05.839 --> 00:00:08.320 wild men while spending time with my friends and family. 5 00:00:09.039 --> 00:00:11.439 As I grew older and read more about the paranormal, 6 00:00:11.599 --> 00:00:14.679 my interest in encryptids and other things strange only deepened. 7 00:00:15.240 --> 00:00:17.160 That's why I'm so excited to share with you what 8 00:00:17.199 --> 00:00:21.640 I've personally become involved with the Untold Radio Network. The 9 00:00:21.719 --> 00:00:25.280 Untold Radio Network is a live streaming podcast network that 10 00:00:25.359 --> 00:00:29.359 airs a new show every day across all podcast platforms, YouTube, 11 00:00:29.359 --> 00:00:32.119 and more. They have eight different shows on all sorts 12 00:00:32.159 --> 00:00:36.119 of exciting topics such as bigfoot, cryptids, UFOs, aliens, and 13 00:00:36.200 --> 00:00:39.479 much more. I even have my own show called Weird Encounters, 14 00:00:39.479 --> 00:00:42.439 where I talk about all things strange. This is more 15 00:00:42.479 --> 00:00:45.280 than just a podcast network. It's a community that allows 16 00:00:45.320 --> 00:00:47.759 me to meet so many amazing people who share their 17 00:00:47.799 --> 00:00:51.520 stories and experiences with strange. If you're interested in hearing 18 00:00:51.520 --> 00:00:53.880 more of these stories and learning more about the paranormal 19 00:00:53.960 --> 00:00:56.679 and encryptids, make sure you check out the Untold Radio 20 00:00:56.759 --> 00:01:00.600 Network for all kinds of exciting shows. It's free to subscribe. 21 00:01:00.679 --> 00:01:04.400 So what are you waiting for visit www dot untold 22 00:01:04.519 --> 00:01:06.560 radionetwork dot com today. 23 00:01:06.760 --> 00:01:09.680 Now, what are your reporting? I got a screen going 24 00:01:09.719 --> 00:01:12.120 on here. Something just kid with my dog, something to 25 00:01:12.200 --> 00:01:15.280 kill your dog? My dog. We're flying through there over 26 00:01:15.319 --> 00:01:20.079 the tree. I don't know how it did it? Okay, damn, 27 00:01:20.159 --> 00:01:22.640 I'm really confused. All I saw was my dog coming 28 00:01:22.680 --> 00:01:24.480 over the fence and name was dead once you hit 29 00:01:24.519 --> 00:01:26.560 the grill. I didn't see any cars. All I saw 30 00:01:26.680 --> 00:01:28.000 was my dog coming over the fence. 31 00:01:44.400 --> 00:01:44.680 Happen? 32 00:01:44.920 --> 00:01:48.000 What are you reporting? We got some wonder or something 33 00:01:49.319 --> 00:01:58.640 crawling around out here? Did you see what it was? 34 00:01:58.400 --> 00:02:00.920 It was enough out here. Look, I'm new to the 35 00:02:00.959 --> 00:02:02.760 window now and I don't need anything. I don't want 36 00:02:02.799 --> 00:02:11.479 to go outside. Its fight. Hello, hit the boddy out here? 37 00:02:11.759 --> 00:02:13.520 What quent on out there? I thought of a bit 38 00:02:13.759 --> 00:02:16.840 about text nine. I don't know. Easy ann out there. 39 00:02:17.000 --> 00:02:19.800 Yeah, I'm walking right, heady, all right, folks want welcome 40 00:02:19.800 --> 00:02:22.360 our guest to the show. It is Neil from across 41 00:02:22.400 --> 00:02:25.039 the Pond in the United Kingdom. Welcome to the show, sir. 42 00:02:25.439 --> 00:02:27.520 Thank you. It's a privilege to be on the show today. 43 00:02:27.840 --> 00:02:30.120 I am so glad to have you. I was fascinated 44 00:02:30.199 --> 00:02:32.479 by your initial email that you sent in about your 45 00:02:32.520 --> 00:02:36.280 analysis and your breakdown of some of the BFRO database stuff. 46 00:02:36.319 --> 00:02:37.960 So we're definitely going to get into that, but before 47 00:02:37.960 --> 00:02:39.400 we get there, I want to start where I start 48 00:02:39.400 --> 00:02:42.560 with everybody, what in the world got you interested in 49 00:02:42.560 --> 00:02:44.080 the subject of Bigfoot to begin with? 50 00:02:44.639 --> 00:02:47.840 Like I guess, I've always been interested in the paranormal, 51 00:02:48.120 --> 00:02:52.159 had interesting things happen throughout life that you think, yeah, 52 00:02:52.240 --> 00:02:55.199 it's possible. But I guess from a big Foot perspective. 53 00:02:55.439 --> 00:02:58.400 Harry and the Hendersons was big when we were little. 54 00:02:58.879 --> 00:03:01.319 I think as time went on, but we started having 55 00:03:01.360 --> 00:03:03.639 TV shows in the UK which would cover quite a 56 00:03:03.680 --> 00:03:07.000 lot of paranoral stuff. Then Bigfoot would be introduced to 57 00:03:07.159 --> 00:03:10.479 the Paddy film. I listened to another podcast they cover 58 00:03:10.599 --> 00:03:13.479 quite a lot of paranal aspect things and been listening 59 00:03:13.479 --> 00:03:17.479 to that since it just after sort of year two thousand, 60 00:03:17.719 --> 00:03:20.159 they kept bringing up the subject to Bigfoot, and for 61 00:03:20.240 --> 00:03:22.520 me it was like, oh, okay, I thought there was 62 00:03:22.560 --> 00:03:26.280 just one sighting, and then as time progressed, there were 63 00:03:26.280 --> 00:03:30.000 more videos, there were more people talking about Bigfoot sightings, 64 00:03:30.039 --> 00:03:33.080 and that got me really intrigued. As time goes on, 65 00:03:33.599 --> 00:03:35.520 you start hearing more and more stories than you think. 66 00:03:36.240 --> 00:03:38.879 Can it really be that all these people are lying? 67 00:03:39.280 --> 00:03:42.919 It seems impossible that could be the case, And so 68 00:03:43.599 --> 00:03:45.360 I went down that rabbit hole. I suppose I could 69 00:03:45.360 --> 00:03:47.719 have chosen anything. I could have chosen aliens, I could 70 00:03:47.719 --> 00:03:52.000 have chosen ghosts, big foot side of things. It intrigued 71 00:03:52.039 --> 00:03:56.960 me because I think there's a real possibility that does exist, 72 00:03:57.479 --> 00:04:01.280 and there's so much data out there to support the existence. 73 00:04:01.479 --> 00:04:04.400 Scientists may so there's not enough data. I myself would 74 00:04:04.400 --> 00:04:07.240 probably say that as well with the BFRO database, we 75 00:04:07.280 --> 00:04:10.879 need more reports, we need more data. These sightings by 76 00:04:10.919 --> 00:04:14.680 themselves are great, they're entertaining, but if you don't put 77 00:04:14.680 --> 00:04:16.480 them together with the other sightings, you're not going to 78 00:04:16.480 --> 00:04:19.879 find those trends. You're not going to find that repetition 79 00:04:20.160 --> 00:04:23.319 that science needs. So yeah, that's what got me into Bigfoot, 80 00:04:23.319 --> 00:04:26.319 and I'm very firmly into it. But obviously, being in 81 00:04:26.319 --> 00:04:29.759 the UK, we have the odd sighting of something every 82 00:04:29.759 --> 00:04:31.920 now and again, but I don't think we're dealing with 83 00:04:32.160 --> 00:04:34.399 the same Reddit comedy. If it is to all or 84 00:04:34.439 --> 00:04:37.959 a make comedy bilder this interpretation, I guess I wanted 85 00:04:38.040 --> 00:04:41.560 to know what I could do to be more involved. 86 00:04:42.319 --> 00:04:46.839 My background, I've worked in HR for nineteen years in 87 00:04:46.920 --> 00:04:49.639 various different roles, but spent quite a lot of time 88 00:04:49.680 --> 00:04:54.680 working with data, using data sets to inform big decisions 89 00:04:54.720 --> 00:04:58.600 within PAHRD apartments. It's getting that balance of using the 90 00:04:58.680 --> 00:05:01.439 data but not drawing two many conclusions on it because 91 00:05:01.480 --> 00:05:04.519 you need that human aspect just go alongside it. The 92 00:05:04.600 --> 00:05:06.800 data is good, it points you in the right direction, 93 00:05:06.920 --> 00:05:08.360 but you've still got to have that sort of balanced 94 00:05:08.360 --> 00:05:12.399 attitude to things. So I really enjoy that about Hi's 95 00:05:12.439 --> 00:05:14.920 that if you have a decent data set, you can 96 00:05:14.959 --> 00:05:18.319 really analyze what's going on and look at multiple things 97 00:05:18.319 --> 00:05:21.399 at once. So from a HR perspective, I might look 98 00:05:21.439 --> 00:05:25.680 at say turnover, high levels of recruitment, high levels of 99 00:05:25.720 --> 00:05:28.839 sickness that are all happening in one department, and those 100 00:05:28.879 --> 00:05:32.319 three things together tell you a story about there's a 101 00:05:32.360 --> 00:05:34.879 problem in that department because you've got all these things 102 00:05:34.959 --> 00:05:37.920 going on at the same time. So that's how I 103 00:05:37.959 --> 00:05:43.319 got onto thinking what about the BFRO information. It's open 104 00:05:43.360 --> 00:05:47.199 sources on their website. Maybe we could do something with that. 105 00:05:48.000 --> 00:05:51.319 And there's something really powerful about where you take a 106 00:05:51.480 --> 00:05:54.839 data set and then add in additional things. And the 107 00:05:54.879 --> 00:05:58.639 good thing about the BFRO database is it's got georeferencing, 108 00:05:59.319 --> 00:06:03.959 so pinpoint where that sighting took place, and if you've 109 00:06:03.959 --> 00:06:05.920 got a date, you can add a date to it. 110 00:06:06.319 --> 00:06:10.000 Then you can go and find a set of data 111 00:06:10.680 --> 00:06:12.519 that will tell you what the weather was like on 112 00:06:12.600 --> 00:06:16.439 that day in that location. You can start adding in 113 00:06:16.480 --> 00:06:20.040 that information. Today it's not in the report, but even 114 00:06:20.079 --> 00:06:22.120 today I was doing some more because every day I 115 00:06:22.120 --> 00:06:23.879 get a new fought and think, oh, I wonder if 116 00:06:23.879 --> 00:06:24.480 I could try that. 117 00:06:24.519 --> 00:06:25.439 I managed to get hold of. 118 00:06:25.439 --> 00:06:29.120 The size of all the US states and the populations 119 00:06:29.120 --> 00:06:31.680 of all the US states and work out population density. 120 00:06:32.240 --> 00:06:35.600 Then from that I can work out a sighting too 121 00:06:35.639 --> 00:06:40.240 population density score, and most states are somewhere between zero 122 00:06:40.240 --> 00:06:43.040 point one and two. But then right at the top 123 00:06:43.199 --> 00:06:48.360 there's a group of states that sort of shout out Oregon, Washington, Alaska. 124 00:06:48.439 --> 00:06:52.399 And what that suggests to me is there are more 125 00:06:52.439 --> 00:06:55.639 reports coming out of those states than there is in 126 00:06:55.720 --> 00:06:59.240 terms of population density. So what you'd expect to be 127 00:06:59.279 --> 00:07:01.519 coming out as an normal, if there was an even 128 00:07:01.560 --> 00:07:06.040 distribution of sasquatch across the US, would be roughly between 129 00:07:06.120 --> 00:07:09.879 zero and two but actually looking at it. Alaska, for example, 130 00:07:10.000 --> 00:07:13.040 is one that really stood out, particularly with Fred on 131 00:07:13.079 --> 00:07:16.480 your shows. I noticed there's only twenty one sightings in 132 00:07:16.519 --> 00:07:19.560 the data set that I had from Alaska. We know 133 00:07:19.720 --> 00:07:22.319 that Fred's said that a lot of people don't want 134 00:07:22.360 --> 00:07:25.360 to come forward, but I thought, oh, that's very low. 135 00:07:25.439 --> 00:07:28.160 But when you look at the sightings for population density, 136 00:07:28.319 --> 00:07:31.959 it is off the scale. So it means that amount 137 00:07:32.000 --> 00:07:34.360 of twenty one sightings is actually higher than you'd expect 138 00:07:34.360 --> 00:07:37.879 to have based on a normal distribution of big foot 139 00:07:37.879 --> 00:07:40.920 across the US. So that was quite exciting for me 140 00:07:41.000 --> 00:07:43.000 to see this morning and think, wow, that it really 141 00:07:43.079 --> 00:07:44.120 jumps off the page. 142 00:07:44.519 --> 00:07:45.480 I love the fact that. 143 00:07:45.399 --> 00:07:48.519 You're interested in that aspect of it, because frankly, I 144 00:07:48.519 --> 00:07:50.600 don't think there's a lot of people that are doing that. 145 00:07:51.160 --> 00:07:53.920 You have people like the BFROO that are taking these 146 00:07:54.000 --> 00:07:56.560 accounts and putting them in a database that gives you 147 00:07:56.600 --> 00:07:59.079 all this data that they're inputting. Very much like you 148 00:07:59.120 --> 00:08:01.600 said with Goo locations, I could look at the weather 149 00:08:01.720 --> 00:08:05.079 and all the things that they collect during these investigations 150 00:08:05.079 --> 00:08:07.439 that they do. You also have people like Scott Tompkins 151 00:08:07.480 --> 00:08:10.240 over at the Bigfoot Mapping Project. He's pulling from the BFRO, 152 00:08:10.399 --> 00:08:12.800 but he's also pulling from some of these other databases 153 00:08:12.800 --> 00:08:15.560 and places that maybe they don't get reported to the BFRO, 154 00:08:15.759 --> 00:08:19.079 and they're getting reported in different places. Fred you mentioned 155 00:08:19.079 --> 00:08:23.319 in Alaska is another repository of tons of stories. It 156 00:08:23.439 --> 00:08:25.759 hits me every time I post one of those episodes 157 00:08:25.800 --> 00:08:28.120 from Fred where he's telling a couple of different stories 158 00:08:28.160 --> 00:08:30.120 over the course of forty five minutes or whatever I 159 00:08:30.120 --> 00:08:33.559 put together. I think to myself all the time, he's 160 00:08:33.600 --> 00:08:36.919 getting these reports directly from these people, in most cases 161 00:08:36.960 --> 00:08:40.799 their first nations, they're Native Americans, that they're not sharing 162 00:08:40.879 --> 00:08:46.360 anywhere else. So you have that subset of data that 163 00:08:46.720 --> 00:08:50.600 is collected in these repositories and other podcasts. My podcast, 164 00:08:51.159 --> 00:08:53.320 I'm shocked that there are other podcasts out there who 165 00:08:53.360 --> 00:08:56.159 cover that. I thought mine was the only one. But 166 00:08:56.320 --> 00:08:58.559 all jokes aside, you do have all of these other 167 00:08:58.600 --> 00:09:01.600 shows that interview people that I've never talked to, and 168 00:09:01.639 --> 00:09:04.159 the majority of the people I'm satisfied, And this is 169 00:09:04.159 --> 00:09:06.039 not something that I normally ask people. That I think 170 00:09:06.039 --> 00:09:09.159 I'm going to start adding to the questions that I 171 00:09:09.240 --> 00:09:12.480 ask people is have you reported this to the BFRO 172 00:09:12.759 --> 00:09:15.919 or any other organization that tracks these kind of sightings, 173 00:09:15.919 --> 00:09:19.320 because I do think that's important because they're coming in 174 00:09:19.480 --> 00:09:21.240 and talking about it on a podcast, but it may 175 00:09:21.279 --> 00:09:24.200 not necessarily be in the database, and you don't have 176 00:09:24.279 --> 00:09:27.120 that way to go back and check these things other 177 00:09:27.159 --> 00:09:29.240 than listening through an entire episode of the show, or 178 00:09:29.279 --> 00:09:32.000 whatever the case may be. So I am so thankful 179 00:09:32.000 --> 00:09:33.720 that there are people out there like you who a 180 00:09:33.919 --> 00:09:36.919 have the background and the patients to go through and 181 00:09:36.919 --> 00:09:38.840 sift through this data, because I have said it from 182 00:09:38.919 --> 00:09:40.559 day one. It's one of the reasons I started this 183 00:09:40.639 --> 00:09:44.840 podcast was to become a repository for these stories that 184 00:09:44.879 --> 00:09:47.720 people could go back and listen to ten years later. 185 00:09:48.320 --> 00:09:50.720 They might have an experience and go, Wow, this guy 186 00:09:50.759 --> 00:09:53.960 that Brian talked to in Alabama had a very similar 187 00:09:54.000 --> 00:09:58.000 experience that I had in nineteen seventy four in Alaska, 188 00:09:58.080 --> 00:10:00.159 or whatever the case may be. I think it's fascinating 189 00:10:00.200 --> 00:10:03.440 that you're doing that and you have the ability to 190 00:10:03.480 --> 00:10:06.320 extrapolate all of these things put them into something like 191 00:10:06.399 --> 00:10:08.679 this document that a couple of documents that you've sent 192 00:10:08.759 --> 00:10:11.960 over to me that make it easier for people to digest. 193 00:10:12.039 --> 00:10:15.320 You started looking into the BFRO database, how did you 194 00:10:15.399 --> 00:10:18.799 get into that? Was it overwhelming for you the process 195 00:10:18.799 --> 00:10:21.519 of getting into all of these reports? How did you 196 00:10:21.559 --> 00:10:23.600 approach that when you were starting to dive into the 197 00:10:23.679 --> 00:10:25.720 data and pull out the things that you were looking for. 198 00:10:26.279 --> 00:10:28.919 I think it was important to approach it with a 199 00:10:29.440 --> 00:10:33.000 sort of data mindset, because you can get lost in 200 00:10:33.679 --> 00:10:37.720 lots of text and information. There's a lot of data 201 00:10:37.720 --> 00:10:40.759 points within there that can be extracted out. For me, 202 00:10:41.279 --> 00:10:44.480 it was important that you can get an average from figures, 203 00:10:44.720 --> 00:10:48.840 but ultimately I wanted to put things into categories like 204 00:10:49.240 --> 00:10:52.919 low temperature, high temperature, middle range, what's an average temperature? 205 00:10:52.960 --> 00:10:56.320 That sort of thing, to try and make that data 206 00:10:56.360 --> 00:11:00.279 more valuable, because once you start grouping part to the 207 00:11:00.360 --> 00:11:04.759 data together, it then becomes more valuable as an analytical 208 00:11:04.799 --> 00:11:08.000 tool because things will jump off the page, Whereas if 209 00:11:08.039 --> 00:11:11.399 you're just staring at reports and minus leets typing in 210 00:11:11.399 --> 00:11:14.519 information into a spreadsheet, it can get a bit much. 211 00:11:14.559 --> 00:11:18.720 But there is an excitement still for me looking at 212 00:11:18.759 --> 00:11:22.159 new categories as well that aren't necessarily they're within the text, 213 00:11:22.240 --> 00:11:24.440 but they're not necessarily something that I can draw out. 214 00:11:24.879 --> 00:11:28.759 So setting up new categories around like size, height, always 215 00:11:28.759 --> 00:11:30.679 found wait a bit of a funny one, and I 216 00:11:30.679 --> 00:11:32.639 think the only people in the UK who could tell 217 00:11:32.679 --> 00:11:34.480 you what the weigh of something is probably a butcher. 218 00:11:34.960 --> 00:11:35.960 So when people. 219 00:11:35.759 --> 00:11:38.440 Say, oh, it's about four hundred pounds or eight hundred pounds, 220 00:11:38.440 --> 00:11:41.200 I think do hunters weigh their animals when they've take 221 00:11:41.240 --> 00:11:41.559 them back? 222 00:11:41.679 --> 00:11:42.240 Is what it is. 223 00:11:42.279 --> 00:11:44.320 I definitely do a great deal of hunting here in 224 00:11:44.360 --> 00:11:47.759 the UK. So yeah, it was seven foot, it was 225 00:11:47.840 --> 00:11:51.440 eight foot. Breaking out those categories making it something that 226 00:11:51.480 --> 00:11:54.320 can then be reported on in a better way, and 227 00:11:54.360 --> 00:11:57.399 we might then start seeing patterns of certain sizes of 228 00:11:57.759 --> 00:12:02.360 sasquatch correlating to Ban's or all the Canadian sightings are bigger. 229 00:12:02.759 --> 00:12:04.279 It's a bit of a task, but I feel like 230 00:12:04.360 --> 00:12:05.960 this is the tip of the iceberg. I feel like 231 00:12:06.000 --> 00:12:08.159 there's more stuff we can do every day. I'm thinking 232 00:12:08.159 --> 00:12:12.039 about new aspects that can be added into that data. 233 00:12:12.360 --> 00:12:16.240 Almost like the sighting report becomes a smaller element of 234 00:12:16.600 --> 00:12:19.000 what we're looking at, and we're actually taking in the environment, 235 00:12:19.039 --> 00:12:23.639 we're taking in regional climates, we're looking at all the 236 00:12:23.679 --> 00:12:25.879 moving part that make things complex. 237 00:12:26.120 --> 00:12:27.759 I guess that's when my hr head. 238 00:12:27.559 --> 00:12:30.200 Comes in, looking at organizations and how they function and 239 00:12:30.639 --> 00:12:32.360 if you push a button over here, it's probably going 240 00:12:32.399 --> 00:12:35.039 to add an adverse effect over here. So just getting 241 00:12:35.039 --> 00:12:37.639 my head around some of those data sets and just 242 00:12:37.720 --> 00:12:40.559 getting them into nice pots of data that can then 243 00:12:40.600 --> 00:12:42.799 be used time and time again. 244 00:12:42.960 --> 00:12:44.080 It can be correlated together. 245 00:12:44.559 --> 00:12:47.519 Are there two subsets of category that if you put 246 00:12:47.519 --> 00:12:50.399 them together they stand off a page? Certainly, things like 247 00:12:50.399 --> 00:12:55.279 temperature precipitation seems to have a significance in citing reports. 248 00:12:55.639 --> 00:12:57.919 Let's talk about some of the basics when it comes 249 00:12:57.919 --> 00:13:01.200 to the BFROL. People have heard the Bigfoot Field Researchers 250 00:13:01.279 --> 00:13:04.279 organization for many decades. It's definitely by far one of 251 00:13:04.440 --> 00:13:08.080 the biggest bigfoot organizations that are out there in the 252 00:13:08.159 --> 00:13:12.759 zeitgeist for folks to digest information from report to go 253 00:13:12.879 --> 00:13:15.440 on outings with. We've all heard of the Class B, 254 00:13:15.720 --> 00:13:18.639 Class A, Class C sidings. Can you talk a little 255 00:13:18.639 --> 00:13:21.639 bit about once you got into those, how you approached 256 00:13:21.720 --> 00:13:24.600 breaking those down, how they approach breaking those down, and 257 00:13:24.679 --> 00:13:27.240 what that means as far as your data versus say 258 00:13:27.279 --> 00:13:29.559 somebody has a Class A versus A Class B or 259 00:13:29.639 --> 00:13:32.399 Class C siding, and what some of those characteristics are 260 00:13:32.919 --> 00:13:35.000 that go into those sidings, And how did you start 261 00:13:35.039 --> 00:13:36.159 looking into that data. 262 00:13:36.759 --> 00:13:39.320 Really, I've taken their class sightings, but you know what 263 00:13:39.360 --> 00:13:41.879 they would define it as. Really, but what I found 264 00:13:42.159 --> 00:13:44.879 was so a Class A sighting is where the witness 265 00:13:44.919 --> 00:13:48.159 has a clear view of the creature, leaving little room 266 00:13:48.159 --> 00:13:53.559 for misinterpretation. They're obviously considered the most credible reports. They 267 00:13:53.639 --> 00:13:57.679 typically a close range. There tends to be more detail 268 00:13:57.759 --> 00:13:59.600 in that report, so they'll talk about the size of 269 00:13:59.639 --> 00:14:02.279 the creature, what it was doing, was it running, was 270 00:14:02.320 --> 00:14:05.519 it pishing, that sort of thing. With a class B 271 00:14:05.720 --> 00:14:08.919 sighting as footprints, they saw something, but it couldn't carry 272 00:14:08.960 --> 00:14:10.919 exactly it was a big foot. But they may have 273 00:14:10.960 --> 00:14:15.120 found footprints with it howlings or rock throwing, but they 274 00:14:15.120 --> 00:14:17.679 didn't actually see the creature. They all fit into that 275 00:14:17.759 --> 00:14:18.879 class B category. 276 00:14:19.559 --> 00:14:20.200 Primarily. 277 00:14:20.279 --> 00:14:22.279 The database is made up of class A and Class 278 00:14:22.320 --> 00:14:25.320 B to pretty much a sort of fifty fifty ratio. 279 00:14:25.759 --> 00:14:27.799 When in looking at most of the data that didn't 280 00:14:27.799 --> 00:14:32.000 seem to be a the conditions, the weather conditions, the climate, 281 00:14:32.320 --> 00:14:35.600 the environment didn't seem to have an impact on whether 282 00:14:35.639 --> 00:14:38.320 you have a Class A or Class B sighting. They 283 00:14:38.320 --> 00:14:43.279 seemed to be possible in the same weather conditions. A 284 00:14:43.320 --> 00:14:47.759 class C sighting is less direct, more ambiguous. It might 285 00:14:47.799 --> 00:14:49.919 be a friend of a friend told me this and 286 00:14:49.960 --> 00:14:50.840 I've reported it. 287 00:14:51.360 --> 00:14:53.000 I think there's any thirty on the. 288 00:14:53.000 --> 00:14:55.799 Database, So yeah, it's a bit hard to put weight 289 00:14:55.879 --> 00:14:59.840 behind thirty cases. But that's the main difference between those. 290 00:15:00.919 --> 00:15:03.200 Let's get into some of the trends that you identified, 291 00:15:03.399 --> 00:15:07.000 like the geographical trends, the seasonal figures and trends, the 292 00:15:07.039 --> 00:15:11.840 temperature like you mentioned earlier, precipitation. I guess there's a 293 00:15:11.879 --> 00:15:13.440 ton of data to go through, so we can talk 294 00:15:13.440 --> 00:15:15.200 about any and all that you want to talk about. 295 00:15:15.240 --> 00:15:17.840 But is there anything that's stuck out to you in 296 00:15:17.919 --> 00:15:20.639 any of those categories as far as the trends, whether 297 00:15:20.679 --> 00:15:24.360 it be geographical, seasonal, that stuck out to you that 298 00:15:24.480 --> 00:15:27.039 maybe surprised you a little bit. In those trends that 299 00:15:27.080 --> 00:15:27.919 you found. 300 00:15:28.159 --> 00:15:31.960 Probably would have said that you would see more bigfoot 301 00:15:31.960 --> 00:15:36.159 in the summer, But actually October is the most likely month. 302 00:15:36.519 --> 00:15:38.960 October is when most of the sightings have happened, and 303 00:15:39.120 --> 00:15:41.039 I don't really know what that could be. It could 304 00:15:41.039 --> 00:15:43.080 be it's the last of the berries so that they're 305 00:15:43.080 --> 00:15:46.399 out and about shutting up for the winter. In some states, 306 00:15:46.440 --> 00:15:49.759 I believe it out mating season is in October. Some 307 00:15:49.960 --> 00:15:53.039 deer categories may also have it. Oh, we know sascots 308 00:15:53.080 --> 00:15:55.879 could be mating in October. That's why they're out and about. 309 00:15:55.960 --> 00:16:00.639 That's an interesting one. Saturday's sprung off the page. Most 310 00:16:00.759 --> 00:16:04.159 days you have a twelve to fourteen percent chance of 311 00:16:04.200 --> 00:16:08.240 having an observation, but on a Saturday that then spikes 312 00:16:08.320 --> 00:16:10.879 up to twenty one percent. So if you think about it, 313 00:16:10.919 --> 00:16:13.519 that's a fifty percent increase on a Saturday that you're 314 00:16:13.559 --> 00:16:16.840 more likely to see a big foot or witness some 315 00:16:16.879 --> 00:16:19.320 sort of evidence of a bigfoot. Now I put that 316 00:16:19.440 --> 00:16:22.120 down to this is just my opinion from the UK. 317 00:16:22.440 --> 00:16:24.840 You may think it's slightly different. But Saturday is a 318 00:16:24.840 --> 00:16:29.720 recreational day. More people go camping, more people go hunting, fishing, 319 00:16:29.919 --> 00:16:32.879 more people out in the wilderness. It's more likely that 320 00:16:33.120 --> 00:16:35.399 you will see a big foot because of the human 321 00:16:35.440 --> 00:16:36.759 behavior on that day. 322 00:16:37.320 --> 00:16:39.320 They get drawn into campsites, that kind of thing. 323 00:16:39.600 --> 00:16:41.440 And on a Sunday that tends to be the day 324 00:16:41.480 --> 00:16:44.799 when people take off for dusk, they go back home, 325 00:16:44.960 --> 00:16:47.240 or they don't tend to stick around on the Sunday evening, 326 00:16:47.279 --> 00:16:50.759 they're not going to get the same level of sightings. 327 00:16:51.320 --> 00:16:53.600 That was why, just general sort of theory around what 328 00:16:53.679 --> 00:16:59.720 it could be that makes that differentiation. Interestingly, winter sightings 329 00:17:00.080 --> 00:17:04.319 in Alabama, Florida, Mississippi, and Georgia we're at twenty five percent, 330 00:17:04.359 --> 00:17:06.319 and that's the highest across the whole of the state. 331 00:17:06.920 --> 00:17:09.839 And I think that's probably because they are in the 332 00:17:09.920 --> 00:17:12.680 south and their climate is a bit warmer in the winter, 333 00:17:13.119 --> 00:17:15.920 so you're going to have more bigfoot walking around, you 334 00:17:16.000 --> 00:17:19.440 can have more people walking around, and therefore there is 335 00:17:19.480 --> 00:17:24.559 a more opportunity in those states to see or witness something. 336 00:17:24.759 --> 00:17:26.599 I've been quite careful in this report to use the 337 00:17:26.599 --> 00:17:30.039 word observation because although they are called Class B sightings, 338 00:17:30.559 --> 00:17:34.160 only really Class A is you can call a sighting. 339 00:17:34.319 --> 00:17:38.160 So throughout the report I talk about observations because it 340 00:17:38.240 --> 00:17:40.720 is the full range of observation. 341 00:17:41.079 --> 00:17:42.839 Full moon and waning moon. 342 00:17:43.160 --> 00:17:46.440 Obviously, that gives you more visibility, so there is a 343 00:17:46.519 --> 00:17:49.680 higher percentage of observations on a full moon or a 344 00:17:49.720 --> 00:17:55.920 waning moon. Visibility again, if there's high visibility or medium visibility, 345 00:17:56.039 --> 00:17:58.440 you're more likely to see that bigfoot. 346 00:17:58.839 --> 00:17:59.920 And of course if it's raining. 347 00:18:01.279 --> 00:18:04.319 I found that if it's light rain or if it's 348 00:18:04.359 --> 00:18:07.000 clear then you are more likely. 349 00:18:06.759 --> 00:18:07.960 To observe a bigfoot. 350 00:18:08.279 --> 00:18:11.319 If it's pouring down with rain, visibility is going to 351 00:18:11.319 --> 00:18:14.200 be bad anyway, so the likelihood of actually seen something 352 00:18:14.279 --> 00:18:17.039 is quite low. And that that's come out the sighting reports. 353 00:18:17.880 --> 00:18:20.160 It did look at something else around, like the weather 354 00:18:20.240 --> 00:18:23.039 reports for those days to see if that impacted the 355 00:18:23.119 --> 00:18:26.200 human behavior and where it said it wasn't going to rain. 356 00:18:26.839 --> 00:18:30.359 Sixty seven percent of the sightings all fit into that category, 357 00:18:30.400 --> 00:18:32.960 so it's almost like people have looked at the weather 358 00:18:33.000 --> 00:18:35.200 report before they've gone out that it's not going to rain today, 359 00:18:35.240 --> 00:18:36.039 let's go for a walk. 360 00:18:36.559 --> 00:18:37.440 That sort of played in. 361 00:18:37.880 --> 00:18:40.920 What I find fascinating is there's a human behavior element 362 00:18:40.960 --> 00:18:43.680 to this and a bigfoot behavior element. 363 00:18:44.279 --> 00:18:46.519 It's hard to draw conclusions because. 364 00:18:46.519 --> 00:18:50.160 We know where the people live, we know roughly where 365 00:18:50.279 --> 00:18:52.400 the bigfoot are going to be found. You're not going 366 00:18:52.440 --> 00:18:54.920 to find them walking down the high street. It is 367 00:18:55.079 --> 00:18:58.799 very interesting to see that could draw a conclusion from 368 00:18:58.799 --> 00:19:02.480 this data that sascotch is a fair weather creature because 369 00:19:02.519 --> 00:19:05.599 we see him more in fair weather. But actually the 370 00:19:05.640 --> 00:19:09.240 flip of that is we are fair weather people and 371 00:19:09.319 --> 00:19:12.680 so therefore we are likely to see tascots when we're 372 00:19:12.680 --> 00:19:17.839 out comfortable in favorable conditions. Just having a look on 373 00:19:17.920 --> 00:19:20.720 here to see if there's anything else that really stood out. 374 00:19:21.240 --> 00:19:24.160 A lot of the observations were in medium or very 375 00:19:24.200 --> 00:19:29.119 high air pressure, which tends to be at lower elevations. 376 00:19:29.920 --> 00:19:32.920 You can imply a height from air pressure because the 377 00:19:33.000 --> 00:19:36.119 highest air pressures around sea level, and then as you 378 00:19:36.200 --> 00:19:38.960 go up the air pressure drops, so you can get 379 00:19:39.000 --> 00:19:42.519 an idea from the data of where that took place. Obviously, 380 00:19:42.640 --> 00:19:45.279 air pressure can change on a dynamic basis on a 381 00:19:45.359 --> 00:19:47.920 day to day basis, but generally it does give an 382 00:19:47.920 --> 00:19:51.920 indication or suggests an elevation to the vast majority of 383 00:19:51.960 --> 00:19:56.400 sightings have been seen lower down, but again that's where 384 00:19:56.920 --> 00:20:00.279 humans tend to live. If we live near we don't 385 00:20:00.279 --> 00:20:02.559 tend to live on top of the mountain. Yeah, it's 386 00:20:03.039 --> 00:20:06.160 just very interesting stuff. I guess there was a real 387 00:20:07.440 --> 00:20:10.559 spike of cases between the year two thousand and two 388 00:20:10.599 --> 00:20:14.200 thousand and it might be thirteen where it went up 389 00:20:14.240 --> 00:20:18.200 into triple figures a year, and then that spite in 390 00:20:18.440 --> 00:20:21.720 two thousand and four there's two hundred and forty one sightings, 391 00:20:21.759 --> 00:20:23.839 and then two thousand and five was two hundred and nine. 392 00:20:24.640 --> 00:20:29.119 Since that point the corresponds a bit to finding big fits, 393 00:20:29.119 --> 00:20:30.920 So you've got a thing. Actually, Matt money Maker was 394 00:20:30.920 --> 00:20:33.519 probably quite stretched during that period and probably couldn't do 395 00:20:33.680 --> 00:20:36.079 a lot of the follow ups that perhaps he might 396 00:20:36.079 --> 00:20:38.240 have wanted to do, And I've got a lot of 397 00:20:38.279 --> 00:20:41.160 respect for that and what he's done for the subject 398 00:20:41.160 --> 00:20:43.880 to bigfoot, And obviously it's a volunteer group beer for 399 00:20:43.880 --> 00:20:47.359 all right, the sightings dropping off after sort of twenty 400 00:20:47.519 --> 00:20:51.839 thirteen to now, and we haven't had one hundred sightings recorded. 401 00:20:51.960 --> 00:20:54.680