And the spread!
Note that the technique described below was also used in this study of mine of a wider spectrum of Super Bowls (actually all of them until the date of that study).
At 1:26 pm today, 3 hours before kickoff, I posted a simple tweet: "The red and white team by ten."
I could not remember the name of the red and white team as being the Kansas City Chiefs but figured that any reader would know who I am talking about. (I did not yet know that the SFO team would come out in red and white jerseys and gold pants. For the purposes of this analysis, it is important to know that their standard colors are red and gold with a bit of white, while the KC team's colors are considered here to be red and white with a bit of yellow. The importance of this all will become clearer below.)
I did not change the tweet after seeing the uniforms of the players on the field mostly because I wanted to preserve the timing and intention of the original thought.
I also did not hashtag the tweet because I did not want to draw those who would probably be more interested in the football than the astrology.
And I did not bet on this game because a. it is illegal and b.the karma of profiting off of men hurting each other does not sound appealing at all!
So, my sole gambling based on this analysis was with my reputation. Of course, I am pleased that I was right and more pleased to see once again that Vedic astrology can carry us through in any situation. Perhaps even just reaping the reward of an ego and/or reputation boost is itself too much. I feel conflicted.
Thus, I want to hurry and let you know how I did it, so that I don't feel guilty, and I don't feel any false ownership of this technique. It is a pretty simple one, and again, it has held fast across all Super Bowls.
Ok, so, what you do is of course pull up the chart of the start of the game.
Next, you look for the grahas (planets) that represent the team colors.
In order of importance:
1) red == Mars
2) white == Venus
3) hint of yellow == Jupiter
1) red == Mars
2) gold == Sun
3) hint of white == Venus
Mars and Venus are both incredibly strong in the above chart. So, really the deciding discriminator is Jupiter for KC compared to Sun for SF. Normally, the color difference between the two teams is more drastic, but this is what we have to go on for this game.
Another way to find the two teams in a chart is by home team (fourth house) and away team (tenth house), but that was not available 3 hours before the Super Bowl.
Of these two grahas, Jupiter is much better positioned than Sun. Jupiter is in its own sign, whereas Sun is conjoined an archenemy, Saturn, and that Saturn is very strong in its own sign.
I did not catch what time the half time was (actually I did not watch much because again, karma, but I liked the commercials I did see), but at about half way through the time span of the game, Leo was rising, and so, Sun and hence SF seemed to have the upper hand.
But at about 9:04 pm Miami time, that Leo ascendant was over with, and Jupiter by house position gained the upper hand, aspecting the tenth house of fame and glory. Moreover, the prize of the win (an eleventh house indication) started to be theirs as the D-11 started to show enough of a separation between Moon (light blue or silver) and Jupiter (yellow) to enact a hamsa yoga there trining in from the fifth house, thus aspecting the first and eleventh houses of the D-11, themselves each being 11th house indications of the prize.
So, there you have it. There is not much to it, but I hope you are now realizing that not only the winner can be discerned, but the dynamics of play within the game.
As to how I got the 10 point spread (actually, KC won by 11), I do not have an exciting answer except that I used intuition and "kinesiology" to test the intuition. In times past, I have helped friends win gambling spreads by walking through the dynamics of play and surmising the spread accordingly.
I hope this was of interest, and as always, please comment below with any ideas or questions.
Using natural language processing, a system of using artificial intelligence to understand text, the author constructs a predictor based on a simple, constrained, description of the solar system on the start dates of various world historical events (n=7819). This predictor is then statistically shown to be effective at characterizing similar events of the past. An online offering of this predictor for use of characterizing the future accompanies this paper.
Understandably, the future is a subject of shared fascination.
Future history is a term of ripe heritage. Typically, it is used to describe works of science fiction. What if future historical events could be predicted computationally, even if hazily?
This paper shows that the simple solar system astronomy of historical event start dates can map onto similar major world events of the past as numerically measured by textual analysis of one-sentence descriptors. By looking at the astronomy that accompanies future dates, those textual characterizations can easily be employed to see astronomy mappings onto historical events.
Methods and Materials
The project makes heavy use of the Mathematica system of knowledge representation, computation, and analysis.
Characterization of Historic Events Dataset
The first step is to seek the historical events. What counts as a true historical event? What counts as the start date? How does one even characterize a world event given differing cultural perceptions? For ancient events, how confident can one be for either the start date or the description?
These are all excellent questions that the author largely side stepped by employing Mathematica’s “Historical Events” feature. There were 7819 such events available thereby with start dates and one-line descriptions included. The sources from Mathematica for this historical event dataset are numerous. They can be found through this mechanism.
The following is a set of descriptors for 400 or so example historic events out of the 7819.
I spoke with the great Sonia Masocco in January of 2017. I recommend Sonia’s herbal services at the highest level.
The audio to the interview was initially lost and then found 2.5 years later but in somewhat of a corrupted state. I am so glad to finally release the partial transcript of this interview about plants and planets. I hope you will enjoy reading the conversation as much as I had in having it!
Renay Oshop (RO): So here we are. AyurAstro is with Sonia Masocco. I thought of Sonia directly and exclusively with the theme of plants and planets. She has developed quite a wonderful teaching program and Ayurvedic phyto-products down there in Albuquerque, New Mexico. I am really happy to have Sonia Masocco join me for today. Hi Sonia!
Sonia Masocco (SM): Hello and thank you for having me! I am very excited actually to share my phytotherapy knowledge with all of you, and I am very excited about this topic, about the plants and the planets, because it is something that has given passion to me for quite a long time.
RO: Wonderful, I can’t wait to hear more. I have a few prepared questions for you. I wanted to ask you first how did you begin your work with plants?
SM: Well, now I am aging myself, but it was around twenty years ago. I was in Hong Kong, and I was basically in a work environment that was not conducive to my basic dreams and soulwork, and I actually found someone who worked with essences. My first approach to working with clients was actually working with the Bach flower remedies, and they did work on a very subtle, mental, emotional level. And that was just the start, the tipping point to make me dive deeper into the plant world.
So, it started with the essences, making very, very subtle medicine, and it worked more on the mental, emotional, negative aspects of the psyche and turning that into positive gifts, into basically being fascinated by the fact that you can have one plant that can, on the subtle level, yield these effects on emotions, but on a deeper level also work on bruises or contusions. So, I said I have to learn about this as well.
So, from essences I went to very deep – I call it the most strong of the plant medicines which is actually aromatherapy – and basically I find it to be a little bit more of a jackhammer of plant medicines, and then basically from there, I found another medium which was in both Western and Indian herbs as herbs themselves.
So, it has been quite a journey, and I am still very passionate about using plant matter, but I do see them as helpers and not something that we should rely on day in and day out.
RO: Forgive me, but I would like to interject a subquestion, because that stimulates so many great, wonderful ideas in me. Thank you for that. My first, biggest question really is that, when you speak of the Bach remedies dealing with the manas and the psyche, would you say that plants have a special affinity to say the manomayokosha? Do they start with the annamayokosha with the bruises and such and then lift up and out, or is it from the outside, from the astral body in, would you say?
I wanted to explore the sidereal charts of spiritual leaders. I mostly wanted to explore an offhand conjecture that there would not be much Scorpio there, by which I mean that I did not expect to see many ascendants, Suns, Moons, or atmakarakas (AK) in Scorpio for that rarefied group.
Who counts though as a spiritual leader? I decided to, without prejudice, take all entries on this Astro-databank page with B or higher Rodden ranking. There were 85 such entries.
Being relatively stringent with the ranking meant that Rama, Krishna, Jesus, or the Buddha could not be included. Those who were left included people as disparate as founders of religions to mere founders of spiritual magazines.
I am a jyotishi, so when I attended a literary festival today that is largely centered on the enigma of Sita in the Ramayana, I immediately thought of Rama's Jyotish chart.
There is much to process here. Indeed, I believe the whole of the multi-tome epic of the Ramayana is contained in this square, but I want to center your attention on the seventh house for Rama, locus of spouse.
How does it make sense for Rama to have an exalted Mars in His house of spouse?
The answer is that it does not, if we start and end with the idea that Sita is meek, submissive, subservient, and most critically, only some kind of victim of Dharma.
Let me take you on a bit of a journey, a short Sitayana in Jyotish, if you will.
Let's start at the beginning, Rama's Saturn mahadasha, for according to Vasistha's Yoga, Rama as a youth and not yet a God was fairly morose.
[Edit: this study was subsequently repeated with NFL player data, and the same negative results held and in the same way.]
It was a topic of conversation: does body mass index (BMI) or even height or weight vary among the sun signs?
Ayurveda would say that they may vary by Ascendant, not particularly the sun sign, but getting good data on the Ascendant is a notable difficulty, because the Ascendant depends on the birth time of day.
Getting tens of thousands of charts with that level of precision is nearly unheard of.
A psychology prof from France named Michel Gauquelin compiled thousands of charts in the 1950's and 1960's that included birth time and hence Ascendant information. I am a little skeptical of the quality of these charts, as many are from the 1800's and more worringly, many use Local Mean Time, which if you back-engineer, describe the birth time as being at 10 am or 11 am on the dot.
So, I feel I can not use Gauquelin's data. I am always on the lookout, then, for credible birth or event data, scouring data science competition sites like Kaggle for the elusive ideal data set.
I came across SoFIFA.com in that way. It gives very good data on the various thousands of professional male soccer players associated with FIFA, including their birth date and height and weight. Birth time and place are not given.
However, if I could just "scrape" that data, that would give me a way to test the conjecture that BMI or even height or weight may vary by sun sign. So, that is what I did.
I recently had some serious dental pain. It was a must lie down, tears in my eyes, think I am going to die kind of pain.
The only problem was that it was the weekend, and my dentist would not be open for two more days. So, what do I do?
Inspired by some principles of Ayurveda, I made the following. It worked for me.
Each day I made a fresh batch of the following:
2 tsp turmeric (classically said to reduce inflammation)
1 tsp neem (classically said to reduce infection)
1 tsp salt (as a kind of anupaan, to make the solution absorb better)
1/2 tsp nutmeg (classically said to reduce pain)
1/2 tsp fresh garlic (classically said to reduce vata and pain)
I added the mix to 2 cups of water and simmered for 2 to 5 minutes. I let it cool to room temperature and strained the solution. I added a teaspoon of sesame oil to improve coverage.
Then I swished for a minute about an ounce of the tea every twenty minutes until the pain abated. It did not take long.
A student and I were discussing the charts of birth, renunciation, and enlightenment for the Buddha, Siddhartha Gautama. These charts are amazing and worthy of many blog posts, a goal for another time. They are sourced from Buddhist Astrology, a really excellent book.
Perhaps I can just say for now that witnessing a Great One's chart is like They are right there, in front of you.
What I want to focus on here is the Jyotish of the Four Sights. I can not do the topic justice, but I would like to add a bit to the discourse.
The basic idea is that Shrii Gautama saw as a young man four sights, "four holy messengers", that led to his enlightenment: 1. an elderly man, 2. a sick man, 3. a dead man, and 4. a saddhu (holy man/monk), in that order.
Some say he saw them all at once, a day before renunciation. Others say that he saw them at different times. Based on the birth chart of the Buddha, I am inclined to think that the sights happened at different times and also not right before the renunciation chart took place. The order of the sights also makes sense from the birth chart.
Rather than showing you about that, I want to show you here the more important themes raised by the sights themselves. Let's begin by seeing where the themes of one through four are in anyone's chart:
[Edit: The latest and greatest on this project, including source files, can be seen at the publication link here.]
I have posted a few times here about a rich dataset that I have.
Data were obtained from Stanford's SNAP data repository of Amazon.com reviews that gave daily misspelling rates; astronomical data were from Wolfram's Mathematica software and its astronomy resources.
Here is what the dataset looks like. Click on each picture to enlarge.
Each of the 5296 rows represents a sequential day in a 14.5 year span of Amazon review misspelling rates during Jan 1, 2000 to Jul 1, 2014.
Across the top are the labels. In each column is a simple, stable, linear function of the right ascension (i.e., the astrological Tropical degree) of the planet, moon, or star at midnight at the start of that day in London, UK. Retrogressions of the planets are also included.
The final column is the log of difference of the misspelling rate of the day from the 27-day SNIP baseline. (The Moon's right ascension completes its cycle every 27 and change days. That is the shortest cycle for any of the right ascensions.) Thus, it is the data over time minus its background noise. The following is a graph of this column's data over time.
SNIP stands for Sensitive Nonlinear Iterative Peak-clipping algorithm. This method preserves any cyclic patterns -- such as the planetary placements and retrogressions -- while discarding "background noise" in the data, which would tend to obfuscate the patterns. The SNIP method is not subjective. It comes out of processing signals within spectra and is unprejudiced. Note that the SNIP method comes from signal processing and tends to preserve cyclic behavior in spectra.
The apparent cyclicity hidden within this data is revealed via a correlelogram:
The thin bands represent the start and end of Mercury retrograde across 14.5 years with Mercury retrograde analysis being the original motivator for acquiring this data.
For today's study, the data for the first 80% of days were developed into a training group, and that of the subsequent 20% of days were isolated as a test group for prediction.
What was doing the training and testing? They were done entirely by an automated machine learning (AI) algorithm from BigML.com called DeepNet. DeepNet* was applied to the training set of the first 80% of days. This DeepNet was then tested or evaluated on the last 20% of days. The DeepNet is a hands-off technique offered to anyone for free.
The chart below displays ridiculously good results as given in the usual AI industry way: the error rates for predictions for the 20% test group by DeepNet (in green) is dramatically smaller than other standard methods of prediction, in gray, which are based on the mean (average) rate of the training data or an approach assuming random chance. Moreover, the strong R-squared suggests good correlation of predicted misspelling rates to actual values only for the astronomical data of the DeepNet.
Astro-databank is the resource for researchers in astrology. It is a repository of birth information of many thousands of people and events and includes biographic data as well as the birth time, place, and date. Of high utility is the included Rodden Rating which tells us the accuracy of each chart.
An AA rating is "Data as recorded by the family or state". The expectation of many researchers is that AA data is of the highest accuracy possible and can be used freely. In the following, I show statistically that it is extremely unlikely that the AA rating charts altogether are accurate. I will be considering charts of people only and only those born at or after 1930.
From here on, I will try to state things as explicitly as possible.
The common assumption (the null hypothesis) is that AA rating charts are all of high accuracy and hence, taken altogether, exhibit behavior of high accuracy. My assertion (the alternate hypothesis) is that AA rating charts do not exhibit behavior of accurate birth data.
One behavior of accurate birth data is that the minute of birth is evenly distributed. That is to say, a birth time of 8 minutes after the hour is not expected to happen much more or less than a birth time of 9 minutes after the hour, for example.
The following is a simulation of a uniform distribution so that you you know what its plot looks like.