I am curious for myself. The market opened about 1.75% down, quickly went to down 2.5% before 9am, and rallied all the way to closing just down 0.15% on the day, so a rally of ~1.5% from open to close. Could I have made significant money with $NDXP options today? My gut tells me no, but I want to see.
Specifically the most likely trade I would have done is buy $NDXP call options at the open for $NDX to close flat by the end of the day. Those obviously would have expired worthless as NDX did not end the day positive. But how about some others? The VIX is currently at 21, and my gut feel is it is too high to make money buying out of the money calls, but let’s see.
First, what if I had bought at the open with a strike 0.5% down from yesterday. NDX closed Friday at 19,280. 0.5% down is 19,180. NDX opened today at 18,990. The first trade for .NDXP-25-03-31-C-19,180 was at $19. So, you would have made $100 / $19 = about 5x your money. Damn. That is a lot.
OK, so how about if you bought .NDXP-25-03-31-C-19,200 at 8:48am when the market was down the full 2.5%. You could have picked it up for $9. It would have ended at $80. Almost 10X. Damn.
What about an ATM call? You could have bought .NDXP-25-03-31-C-19,000 at 8:30am for $100, and at 8:45am for $40. That would have closed at $280. Meaning 3X or 8X your money.
Damn, Well, I guess you could have made money today.
OK, I’ll start this one off by admitting this post is total procrastination. It is Friday morning and I should be doing something productive, but instead I want to look at the metrics for the 2025 OKC Thunder. The stock market is down another 2% today so don’t look there. My curiosity was peaked when on local sports radio I heard the announcer say that the game last week between OKC and the LA Clippers was the first one possession game OKC has played all year. It is late March. So, let’s dig through the numbers:
As I write this the Thunder are 61-12 with 9 regular season games left to go. They have already wrapped up the #1 seed in the Western conference, no other conference team has even locked up a playoff spot yet (!!) In 1-score games this year (defined as -3 >= final margin >= +3 and OT games) the Thunder are 1-4. So the radio talking head was wrong, it was not the Thunder’s first 1-possession game, it was just the 1st 1-possession game the Thunder have won. The Thunder are 6-2 in 2-possession games, and 54-6 in 3+ possession games. Here is the full record:
The record is sorted by point differential. OT games are boxed in, 1-possession games are in puke-yellow, and 2-possession games are in sea-foam-green. 3-possession+ games are in white.
The Thunder play a one-possession game about once a month. That is nuts. Compare the current champs, the Boston Celtics:
The Celtics have played twice as many 1-possession games (10) and won 7 of those.
So if you convert the Thunder’s 1-4 record in 1 possession games to 4-1 (or even better 5-0) then they would be 65-8 currently, and theoretically could win out to go 74-8. Only slightly crazy talk, because look at the 2016 Golden State Warriors:
Notice their good fortune in close games — they went 10-0 in games that were decided by 2-possessions. They even went 7-2 in 1 possession games, for a total of 17-2. Their 3+ possession record of 56-7 is going to end up being worse than the thunders, who could go as high as 63-6
It has been widely reported this year that OKCs average margin of victory (currently +13.1) is the largest in NBA history (all time). It handily beats the 2nd and 3rd best teams this year (Cleveland +10.4 and Boston +9.1). To put in perspective that those two are great numbers on their own, the 4th and 5th place teams this year are in the +4 range. It even handily beats Jordan’s 1995 Bulls (+12.3) and the 2015 GSW team (+10.8) that went 73-9. The current best all-time is the 71-21 Lakers at +13.9. But that need to be adjusted for pace — back in the 1970s there were many possessions per 48 minutes. No 3-point line, no offensive sets, just fast breaks and dunks (Showtime!). The metric that does this is Net Rating. Net rating adjusts for pace, making it possible to compare teams that play at different speeds. For example, a fast-paced team might have a good point differential simply because they play more possessions per game, while net rating would reveal if they’re actually more efficient on a per-possession basis. Here are the net-rating comparisons:
So, on a Net Rating basis, OKC is almost up +3 on 2016 GSW and even better than Jordan and the Bulls.
Neville’s Take:
So just how good are these Thunder? Let me make a prediction. The Thunder will be the first team to go 16-0 in the playoffs. It is very likely they sweep anyone in the West, and then the ECF will have Cleveland and Boston slug it out, the winner there being tired and no match for a rested, healthy Thunder. If you are in Vegas put some money on that prop bet and send a check my way for Father’s day. We all need it after the stock market today 🙂
Just finished a great read recommended to me by Michael Palmer — The Frackers largely centers around the events in the American shale oil boom from ~2000 till about ~2014 when the book was written and published. The cast of characters is nothing less than American Heroes- George Mitchell, Harold Hamm, Aubrey McClendon/Tom Ward, Charif Souki. Several of these heroes were bankrupted or even dead and the impact they have had on our way of life is not appreciated by as many as should.
To put it in perspective, the USA (including Alaska) has around 3-4% of the worlds proven oil reserves (around 50,000 million barrels, with a world supply of 1,500,000 million barrels). However, we are the #1 producer in the world, pumping 15% of the worlds supply (13 million barrels each day, where the world pumps 83 million barrels). In 2005 we pumped only about 5 million barrels per day, with many assuming domestic oil would run out, but the work of these people has pushed us from 5 million to 13 million. As a consequence our gas and electricity bills are less than half of western Europe — natural gas in Europe costs $10 per million BTUs, gas in Asia is about $12 per million, in the USA it is just $2-3 per million. Natural gas (produced alongside oil frequently) is also much cleaner burning than coal. If not for these men we we would be burning 2-3x as much coal, polluting the environment, and paying 3x for the ability to do so.
George Mitchell, who developed the Woodlands area north of Houston, started commercial development of horizontal drilling and fracking in the 1980s / 1990s. Oil drilling previous to Mitchell was basically drill a vertical hole in the earth like a big straw and pump it out. Most fields (like Saudi Arabia’s easy oil) are just sitting there in a giant pool. This domestic revolution was shale oil — liquid oil that is there, but trapped inside rock. It takes guts to drill down 2 miles into rock, turn that horizontal, drill another 3 miles, send dynamite explosive charges down with water and blow those rocks up to recover oil. You can see how it is much easier to just drill it in the middle east and pay the importers.
Aubrey McClendon and Tom Ward (via Chesapeake Energy) really supersized the process and embraced debt to expand operations. Aubrey in particular is someone who should be taught in OKC metro public schools as he brought forth Classen Curve, transformed the city with the olympic rowing river south of downtown, helped bring the Thunder to OKC– really changed the fate of OKC for the better. Sadly though, Obama could not have given a flip about any of this and Obama’s DOJ witch hunted him because he lived on the edge with debt and largess, so they indicted him with jail time in mind, and it was too much for Aubrey as his distracted mind was killed in a car crash 24 hours later. This is after Aubrey made many, many land owners very rich by paying billions of dollars for mineral rights. He employed more landmen then others had employees. Shame on our government at that time.
Charis Souki is super fascinating. He actually managed the restaurant in LA where OJ/Nichole Brown/Ron Goldman happened. He decided to leave LA after that and move to Louisiana and get involved in oil. Specifically he saw all the media reports that the USA was running out of oil and decided to build multibillion dollar import terminals for liquified natural gas drilled in Europe and then imported into America. At that time both the USA and rest of the world were about $2-3 per million BTU, and he foresaw a time where the rest of the world would stay at $3 and the USA would go to $10. Well, as it turned out because of this domestic shale oil boom and Russia/Ukraine the USA is at $2-3 and Europe is at $10. He reconfigured his company midstream to go from importing natural gas to exporting it, and now LNG trades at $230 per share, up 20x since 2010).
Anyways, a great read and the author is on X at @GZuckerman I love a good nonfiction story, and all Oklahomans should know this story.
I had a lightbulb moment today. I am talking a class on neural networks taught by the excellent Dr. G. at Stanford continuing education. Last lecture we talked about a simple neural network identifying an image, say a boat/plane/car/train. The neural net starts blank, and you feed it labeled images of boats/planes/etc. That input changes the weights of the perceptrons (neuron mimicking structures in a machine). These weights are simple numbers, think 4, 7, 12.5, whatever. The point is simple numbers (weights) only. These perceptrons connect to each other and have an activation function, so a 12.5 from one perceptron is fed to perceptron #2 and the 2nd perceptron may (or may not) fire a number downstream after being fed a 12.5. That’s it. After trained on numerous boats/planes/cars/trains, if you feed the network a new boat it has not seen before it is likely to spit out “boat” because this new image fed a 12.6 to the downstream perceptrons, not exactly 12.5, but much closer than plane or car.
The key point to understand in the paragraph above is the AI (specifically large language models) do not “store” source materials. There is no hard drive with images of boats that can be pulled up. The network has seen many boats and that has caused these weights to be as they are. The only memory are these numbers and weights, not source material — words or images. That bears repeating- if I have a model like gemma-2-27b that is 50GB large, those 50GB are all model weights — absolutely no supplemental material.
Think about your physics test back in college– your teacher allowed you to write anything you wanted, formulas, pictures on a 3×5 note card, and as long as you could fit it on that note card you could bring it in during test time. So your brain had the ideas and methods, but you had a note card to remember the exact derivation of final speed based on acceleration and time. What I am trying to say is that the AI language model has no note card. It does not have 50GB of weights and also the text of the Declaration of Independence, it just has 50GB of weights. Sure it has read (been trained on) the Declaration of Independence, but when I ask Grok/Claude/ChatGPT what is the 3rd line of the Declaration of Independence it *does not* pull up the internet, read the text, then tell me the answer — it simply pulls the answer out of those 50Gb of weights. (now this is not exactly true anymore, Grok and the other LLMs can search the internet and take in results, but a traditional old-school LLM like gemma-2-27b does not need, and can not use, any internet access whatsoever)
So in these 50Gb of weights (not really that big, about the size of 10 movies) it can think (or predict) words out of the Declaration of Independence. Or the emancipation proclamation.
So I asked Ara (the xAI voice assistant) to read me word for word the emancipation proclamation. It said that from my 50Gb of weights I can give you that it is 270 words long, 5 paragraphs and it could give me the gist of each section, but it probably could not recite it word for word. I pulled up Lincoln’s handwritten version from the National Archives and read along as I asked Grok to give it to me word for word, or try its best. It nailed EVERY SINGLE WORD! All from the 50Gb of weights. I even asked it to tell me about which exceptions Lincoln wrote in inside the margins, where the line spacing is off. This is a very obscure reference. If you do a google search for ’emancipation proclamation “Norfolk” and “Portsmouth” “line spacing”‘ you will not get any results. This is just something you have to read and look at. But Grok, after successfully reading me the whole thing (again from “memory” aka the 50Gb of model weights) correctly told me the exceptions for Norfolk and Portsmouth were written in between the normal line spacing.
So the lightbulb for me? An LLM is not just smart — it has a photographic memory. It does not have to recall source material on demand, it can pull EXACT COPIES of things just from its weights. Maybe today only 270 words like the Emancipation Proclamation, but tomorrow, everything.
If you are on keppra as a medication for seizures, you should know that one sip of wine will make you die. In fact, more people die each year from mixing keppra and alcohol than die from defenestration.
This year I was fortunate enough to make one really good trade and hold a portion of it through fruition. Here I will document the trade and the way it has evolved over the course of this year.
Towards the end of 2023 I shaped up what my 2024 portfolio would include. I like liquidating everything at the end of a calendar year and re-buying what I like and believe in. For 2024 I decided I would put 6% of my speculation portfolio into 3 options, 2% each which worked out to about $6,000 each option. The 3 equities I decided to buy options on were NVDA, RIVN, and QQQ. Here is the the setup in NVDA coming out of Jan-Dec 2023:
It had a great 2023, tripling from 150 to 500. Sometimes last year’s winners are also this year’s winners — look at DELL and EMC in the late 90s.
And above is the entry trade into NVDA.
My reasoning for this trade was that I like this setup. I have been blow away by AI and ChatGPT and GitHub CoPilot. During the fall I spend a decent amount of time coding for my website and app for playoffPredictor.com. To say that AI made my coding so much better is a gross understatement. You simply can’t do this development on Intel processors – it has to be GPUs and NVIDIA. So there is my conviction. Also, look at the 2023 performance of NVIDIA. There is the huge gap up from 300 to 400 in May when they announced earnings, and then really ‘UNCH’ for the rest of the year. Well, I guess going from 400 to 480 is 20% which is far from 0%, but for a speculation stock this volatile that is growing earnings by 10X over last year- yeah 20% is pretty much unchanged. I like stories like that which are due for a total repricing, not just a change in price based on what you could have bought it for yesterday.
Here notice the date and the amount. Ideally I would have made this trade on 1/2, but instead it is on 1/9. Sometimes I get nervous on these trades and just want the price to fall a bit further. If I would have made this trade on 1/2 and done $6,000 – the price was 50 cents, so I would have bought 120 contracts instead of 30. Hmm…. @#%#$^#%&. Oh well can’t live in the past. And there is no way I would have thrown $6k at such a nonsense idea. I mean 50% in 10 weeks on a $1 trillion company is nuts.
To speak to that nuts, planning my trades in December I never wanted NVDA at 750 strike and 3/15 expiration. I actually was planning on 600 strike and 4/19 expiration. But the problem was it was just too expensive. On Jan 2 the 600 call for 4/19 was trading for $10. I waited the first week of January to pull the trigger and the price got down to $8, but that’s still too expensive for me. I like to buy options that are about 0.20 cents to 0.50 cents as a rule when I’m swinging for the fences. I was watching the price the first week of January and hoping to get a better price. But the price kept going up, and by Monday 1/9 the 600 calls were trading at $20. So I said what the hell and threw down $4,500 on 30 contracts at a much higher strike of 750 for about $1.50 each. I’d rather have 30 contracts instead of 5 contracts any day. My thinking is that you can get rich at 100+ contracts and just have a good return at <10 contracts. And it is a good thing I did not end up buying the 600 strikes. They would be worth ~ $300 each contract now which is 300/10 = 3000% A 30 bagger. Very good — but as it turns out not as good as the 750s
So here is what NVDA and the call has done 2024 year to date:
In a perfect world yes this was a .38 cents to 223 opportunity: 223/.38 = 58,600% or a 586 bagger! Imagine turning $2,000 into $1,000,000…
Well all January NVDA went up and the call went up, straight from $1.50 to $5 by the end of January, and then a quick run up from $5 to $25 in the first 3 trading days of February. Very nice I turned $5k into $15k and then suddenly from $15k to $75k was quite happy (ecstatic). I decided to celebrate by purchasing an Apple Vision Pro that came out on Feb 2. So I sold my first 2 calls on Feb 5th for $25 a contract ($5,000 credit, covered my initial investment. Everything else was now house money).
After February 5th it got much more interesting. Earnings were to be released Feb 20, and wall street was all abuzz with this earnings report. I felt it could go up into earnings, but I was playing with real money now. I’d never spend that kind of money on an out of the money option into earnings, but I didn’t have to spend that money — it just grew into that valuation.
My next move was on 2/12. By that time NVDA was trading at 720, getting really close to the 750 strike. Generally I sell an option when it goes from out of the money to at the money. This time I did not really want to sell, I wanted to see where this ride would go, so I decided to sell an upside call against my call position. Normally people sell upside calls against share ownership positions; it is called a synthetic dividend. But this was a little different. Essentially I turned by 750C into a 750/930 call spread. I sold 28 contracts at 930 strike for the same expiration of 3/15. My reasoning was that I was now guaranteed $20k of profit, even if NVDA tanked. Nice!
Of course I capped my upside at $180 per contract, but 180*28 is $500,000 – so I settled for a max profit of $500,000 with $20,000 guaranteed.
On 2/18 and 2/19 NVDA fell from 730 to 670. Earnings was on 2/20, and people wanted to lock in gains before earnings. That was somewhat painful. On paper each day I lost $30k or so. Basically all those gains to $75k gone, back to $20k total return. On earnings itself I did not watch at all. I texted my son an hour after close asking “Are we eating at the Ranch or at Taco Casa tomorrow”. His response “somewhere in-between”. My pulse quickened. After earnings it was back to $750 and I took the whole family to the Ranch for dinner the following evening. It was the feast of unrealized profits! Over the past 24 hours I had made $100k on paper. Other may be used to that, but I was not.
Now here is where I normally would sell the whole position. Earnings are done. The strike price has been met. It is too risky to risk everything and theta decay will kill you now. But I decided this time to just sell 8 contracts at effectively $31 each. And let’s see what happens with the other 20 contracts.
Now here is a trade I regret. From 2/23 to 2/28 NVDA drifted down from 820 to 775. Getting close back to the 750 strike I had a fit of paper hands and sold 5 more contracts on 2/29. I guess I just wanted to guarantee $60k in profits, so I sold.
The next trade was to buy back 2 of the 930 calls. from 3/1 – 3/4 (2 trading days; Friday and Monday) the price jumped from 800 to 880 and I suddenly realized taking out the 930 calls would be possible and then I’d be forced to sell. I just did not want to sell until expiration. I could have bought back all remaining 15 930 calls on 3/1 for $2k, but I didn’t and the price shot right back to the premium I collected in the first place.
Next I decided I wanted protection. I bought put options (expiring that Friday 3/8, 1 week before my call option expiration) so that I locked in $50 per contract no matter what. The only thing that could hurt me was if it closed Friday above 800 and then opened Monday below 800. I felt comfortable with that risk (it was trading 880 at that time). Sure enough these expired worthless, but that $760 spent helped me sleep at night.
Over 3/6 and 3/7 the price kept shooting up and was bumping right against 930. Well if I was still short the 930 I would have to sell, I mean at that point it is only risk with no reward as the 930 and 750 will both have a delta of 1. Only possibility is price goes below 930 and I lose more money on the 750s (still deep in the money) than the 930s (back to at the money). So I panicked and started buying back the 930 calls. Remember that $20k premium collected? Well, here was $12k just to buy them back. I was now long 15 contracts at 750 and short 6 contracts at 930.
Well on 3/8 open it broke through 950 and I sold 5 more contracts. I like to sell at market open, but I was on the Guardians of the Galaxy ride at EPCOT, so I had to finish that first. I sold the 5 contracts just outside the gift shop at 9:35am. I also bought back the last 930C contract. I kept thinking to myself the Guardians ride was tame compared to the NVDA ride. Why there is not a theme park with the whole theme of stock and options prices I have no idea — that is a wild ride! Total spread credit was $160 per contract.
On 3/12 I bought protection for 5 of the remaining 10 contracts for $4, financing it by selling upside calls at $1,000. I mean if I get $250 per contract I’m thrilled, and this guarantees a full $100 per contract. Of course both these expired worthless, except the insurance was nice this week as it drifted down on Thursday.
Thursday morning I went ahead and sold another 5 contracts at the open. Now I am locked into a minimum return for the whole trade. This trade is pretty similar to the 2/29 trade, done out of fear of loss or paper hands, same concept.
Friday morning is expiration day. Time to harvest what is left. But first I had to buy back the $1000 strike calls, else my account could be subject to infinite risk. Divorced from the big picture it was a good sale on its own – sold on Tuesday for $1,621 and bought back on Friday for $53. I guess if you think that way its a 30x return on your money in 2 days. Of course the catch is you have to tie up tens of thousands of dollars in shares or long options in order to make a trade where you sell premium in the first place. In a lot of ways it is not fair. $1,600 is a lot of money to most of the country and it is only accessible to people who already have means. I am sure someone reading this will be young and understand the concept, but be unable to execute it for themselves because they don’t have the money already, and that is a shame. I think Robinhood at least offers people money for loaning out their stock, even just a few dollars. That seems like a good start to me.
Finally, this morning I sold 3 contracts at open and in the afternoon at 2:45pm I sold the final 2 contracts. That open price ended up being the low of the day. Oh well. And I was going to buy that ivory backscratcher.
All totaled, it comes to $291,000 on a $4,500 investment, or a 6,500% gain, a 65 bagger. You only need a few of these in life to catch the options bug permanently. Do I wish I had held on the whole time, I mean it could be more like $600,000. While the answer is of course, I don’t think I would have had the mental energy to do this all the way to $600k. For that matter you could have bought the 950C expiring 3/15 for 0.05 cents on Jan 5th, and it would have been worth $50 on March 8 – a full 100,000% return – 1000x on your money. Turn $5k into $5M. You could have also done that with MSTR in February. I wish I would because houses on the beach are not cheap and I could use an extra 1 or 2 million if they are giving it away, but oh well. That kind of thinking is a trap. It is impossible to buy the low and to sell the high.
Here is one of the profit and loss bubble charts while it was trading at it’s high. Normally that percentage you are happy at 20% and 30%. The thing says %15,000. Just unreal.
Could I have done better? Yes, but. Common strategies that people use is to roll up (higher strikes) and potentially out (further calendar date) options as they go from out-of-the-money to at-the-money. If I would have done that and say harvested 50% each time while going up in 50$ chucks, I’ll bet I could have made a lot more money (I’ll have to compute that when I get back from Spring Break to see exactly how that would have worked out). But there is no way I could have done that, mentally. That would have meant selling $80,000 of options on 2/22 and then buying $40,000 that same day, like 3/15 800C. That would have been hard. I mean even though the money fungible and holding is the same as selling today and buying it tomorrow our human caveman brains can play with house money of $80k MUCH easier than playing with fresh $40k. I mean, I just would not throw that kind of money at an option expiring in 3 weeks. That’s irresponsible. People who can master that part of their psyche and not fall into that trap I am sure are fantastic options traders, but I have not conquered that hurdle yet.
Did I make mistakes? Yes. Here you have to separate true mistakes from just price anticipation, which is unknowable. Looking back at this I made 2 mistakes:
On 2/29 when I sold the 5 contracts I should have also bought net new options at ~800 expiring 3/22. I should have used 10k of the 20k for that. That guarantees $50k on the trade, but you have to get longer on weakness if you believe in what you are doing, not just flatter.
On 3/8 I should have sold everything. In my speculation account I have a rule – everything must be harvested 1 week before expiry. In my view options with less than a week is gambling and belongs in my timing account, not my speculation account. Now, of course that was the high that Friday morning, but that is irrelevant. I have to have the discipline that everything in the speculation portfolio must have an expiration >1 week out. This would mean that the protection I bought should also have been through 3/8, not 3/15. Unfortunately this was a $100,000 mistake (ouch)
In the end I think you need some conviction to stick with a trade like this. There is no way I would stick with it if I thought NVDA would not become larger than AAPL and MSFT, which I think it will this year. Now after that, it certainly can be cut in half. But if the thesis is that every single CPU in every computer and phone is dead in the AI world, yeah that is a big market. As for now, well it is spring break and I am headed to Mexico. Cashing out this week. No crazy options positions on vacation!
I have decided how I am going to vote for in the 2024 presidential election. I realize people don’t care about my political views, but I document them for myself and my family every four years. That’s as political as I’m willing to get!
As I write this on Feb 4, a Biden vs Trump rematch looks inevitable. Trump has won Iowa and New Hampshire by 50+ points, and only one other candidate is still running, Nikki Haley, and she is losing in her home state of South Carolina by 60 points. Is Trump v Biden round 2 inevitable? I guess not, I guess one or both of them could pass before November, but short of that I don’t see how it is not Trump v Biden and the necessary delegates locked to mathematically seal it by the end of March.
So I have written on Trump before. He is a narcissist and an asshole. Well, lots of politicians are, but unlike other politicians who smile for the camera and then stab you in the back, Trump just stabs you in the front. He rubs people the wrong way. I get it. But my mom always said to judge him on policy, which she did before turning on him after Jan 6, mostly because I think she just loved me and Shelli and knew her views were opposed to ours at that time. Trump at least has an agenda — America First (really we all know it’s Trump first, and he is running this time to save his own hide from financial ruin and prison but past that you can at least give me ‘America Second’). America First is a solid guiding principle. At least he has one. Biden’s guiding principle is ‘I’m not Trump’. While true, that mode of leadership does not make our country more prosperous, our cities and streets safer, or generally do much of anything except keep the status quo. With an America First guiding principle, Trump holds people accountable and fires and replaces them as needed. He did that so many times with cabinet secretaries and staff during his first term that it became impossible to count. And sticking to America First he tried to re-ignite manufacturing in America. But places where he tried and failed like Wisconsin became disillusioned with him. I get it. We tried, we had enough, we wanted some calmness in Washington and elected Biden.
We learned some things in 2016-2020. Trump can be president and we will not have nuclear war. The stock market won’t collapse in a Trump presidency (interestingly go back and look at the fist 2 days post-election results in 2016. During that Wednesday-Thursday November 5-6 the NASDAQ and all kinds of companies favored by liberal tech elite (AAPL, MSFT, AMZN, DIS) all got drubbed – losing 5-10%. At the same time main street America companies (like JNJ, PG, X) all gained 5-10% and started rocketing north). There is a Trump Bump. Even foreign countries (like EU Europe) where Trump is hated and feared they at least respect that he fights for his countries interests (like backing out of Paris accords, moving the Embassy to Jerusalem).
Biden has been adequate. I have respected his choices, like re-nominating JPoW. I also think he has succeeded in what I wanted him to do, which was turn down the charged political atmosphere that we had in 2020. He has done that, but that alone is not good enough to deserve another 4 years. Biden will be in his mid-eighties, and that is just too old to risk again.
But that was 2020. 2020 is past and done, the election this fall is about 2024-2028. I am going to follow the advice of my mom and judge Trump by his actions, not his words or personality. Specifically, I am going to judge him by his one real decision before the election, the selection of his VP candidate. Vivek Ramaswamy is a smart, polished Washington outsider- all things Trump values. He is also brown skinned and Hindu. So much MAGA support comes from fundamentalist Christian — does Trump have the guts to select Ramaswamy and force that thinking on the white MAGA group? If he does that I’m voting for Trump in 2024. Note, I did not vote for Trump in 2020 or in 2016, so this would be a first. If he picks someone besides Vivek, I will likely not vote at all this cycle, or throw my vote away again on a 3rd party candidate like I did in 2016. It is sad, but so are the choices we have. Hopefully 2028 will offer better choices.
So the final 2023 CFP rankings have come and gone, and I reflect on the model performance. There are 3 different ways we can look at what happened — computer best teams, computer most deserving teams, and playoffPredictor.com method with committee bias.
Computer best teams involves carefully looking at margin-of-victory and using that to deduce the best teams. Close wins are punished (a 1-point win gives an m=-0.8) and blowout wins are rewarded (35-points and greater wins give an m=+0.5). This is detailed in the full method. I know it works because results are well correlated with other computers (who churn though *much* more data than I do), and I have excellent results — I finished the 2023 regular season at around 52.3% ATS, which was 6th (out of 28 computers) and 2nd (out of 17 computers) that picked all games this season. From a best team perspective — meaning bet on these teams in Vegas to win on a neutral field, here is what we have after week 14:
Teams that were ultimately selected by the committee as the 4 “committee best” are highlighted in yellow.
We see that 2 of the 4 of the “committee best” are nowhere close to the “computer best”. The computer best top 4 includes 2-loss Oregon and 1-loss Ohio State. These teams were dominant — For example, Oregon beat top-25 Oregon State by 24 points, where Washington beat them by only 7. Computers and book makers agree — if Oregon and Washington were to meet a 3rd time this season Oregon would still be a very slight favorite. The fact that Washington beat them already twice has nothing to do with where the money would land. Oregon, Ohio State, Georgia — all really, really good teams.
Now, look at it from computer “most deserving” standpoint. Most deserving involves slightly punishing 1-point and 2-point wins, and giving slight advantages to blowouts of 25 points and again 35+ points. It is a formula that is well correlated to human polls with a end of season η around 1.2. Again, see the full paper. Most deserving in 2023 were:
The computer got it exactly right, including #4 Alabama and #5 FSU. But that is not the method I have used for 10 years. What I have used is a committee bias — basically see differences between the computer most deserving and committee best, and use the average of that to predict the future. That method cratered this year. 2023 final predictions were:
The model of computer most deserving + bias predicted #2 Georgia and #4 Ohio State. But these were wrong.
What happened?
Well, to put it bluntly, the committee lied. They lie every week from week 9 right through week 13. Week 14 (the final week) they just pick who they want. Take Georgia for example — the committee had them #2 in weeks 9-10, and #1 in weeks 11-13. Rece Davis even asked the CFP chair point blank before the Bama game “is Georgia unequivocally one of the 4 best teams?” Translation — they have already done enough to get into the playoff. The votes weeks 9-13 would say yes — the computer had Georgia as low as #9 in week 9 – they had not beaten anyone. Georgia only rose to #3 in the computer most deserving by week 13 because finally they had blowout wins over Tennessee, Ole Miss, and Missouri. But that bias was so strong– as high as .11 in week 9 and always above ~.05 that even with a loss to Bama, Georgia should have been one of the best 4 in the final poll. Else, the committee was lying all those weeks 9-13. I mean in Week 9 when Georgia was #2 behind Ohio State their best wins were Kentucky, Auburn, and Florida. Teams that would finish 7-5, 6-6, and 5-7 respectively. I mean they beat Auburn by 7 when New Mexico State beat Auburn by 21. If the committee knew something and elevated them to #2 back then, they sure sold Georgia up the river in the final poll when they acted like they never had UGA in the top 5.
So what to do going forward? I could simply change the formula to have no bias and simply use the computer most deserving, but that does not work all years. Look at this over the last 10 years:
To read this take an example from 2022. The computer most deserving after week 14 was Georgia, Michigan, Ohio State, and TCU. That was #1, #2, #4, and #3 to the committee (the committee had TCU #3 and Ohio State #4). With correction for bias the method produced #1 #2 #3 #4. All 4 teams correct and the order correct.
Look at 2023. Computer most deserving are #1 #2 #3 #4. But add in bias and you get #1 #3 #5 #7. Not good. Again, the committee lied.
But look at 2017. Computer most deserving are #2 #8 #1 #6 — bad. But add in bias and you get #1 #2 #3 #5. Not perfect, but good. 2017 was the year USF went 12-0, and the committee was never going to get them to the top 4 even though the computer most deserving had them at #3.
So, I’ll keep my method for the 12-team playoff the same next year, but use a grain of salt. The method is sound, the computer is accurate, but the committee lies.
Below is a list of my most useful links on the Cisco Intranet that would be handy to get a generalist SE/SA up and productive. Of course most of these links will not work without access to the Cisco internal network via VPN, and they will not work without logging into Cisco (which is done at id.cisco.com)
Enterprise Agreement management portal – https://eaccw.cloudapps.cisco.com/app/#/ – Used to see the quotes your software sales specialist puts for EAs – knowledge worker counts, suites covered, etc.
topic – topic.cisco.com – Possibly the most important tool for any Cisco presales SE/SA. Look up every question ever asked and any answer ever given in any forum to product management or TMEs. Set data sources to “Newsgroup” to search PM/TME communications and/or “CSOne” to search all previous TAC cases. Leave the other sources unchecked.
TAC case query – https://cae-xmlkwery.cisco.com/main/casekwery.php – This is the one I like the most. There are several portals that will get the same TAC data, but this one organizes the information best.
CCW-R – https://ccrc.cisco.com/ccwr/? – where you can input a serial number and find info on ship date, who it was sold to, and if it is still under E-LLW or TAC support
CCO lookup tool – https://cdca.cloudapps.cisco.com/cdca/lookup.do – Lookup your customers CCO status, see what contracts they are associated to, and even add contracts to their profile, self-service (sometimes works). Try doing a search not on email address (takes too long), but on customer name using exact (not contains). Searching is case-sensitive, so “university of Oklahoma” returns nothing, but “University of Oklahoma” returns the records. If you want to look up yourself use it without the @cisco.com – for example “neaga”, not “neaga@cisco.com”
Smart account info via Cisco Software Central – software.cisco.com – First get access to your customers smart accounts by using the link for “Request Access to an Existing Smart Account”, then use Smart Software Manager to see their licenses, including products registered and pulling licenses.
My business reports – https://mbr.cloudapps.cisco.com – See product quotas and attainment for the region. See week to date or quarter to date numbers. Also hit dashboards->Bookings 360. Best way to see product bookings over the last 3 years by account. Hit advanced filters, change from “Sales Hierarchy” to either customer or BE.
Cisco Ready – https://rewarddash.cloudapps.cisco.com/#/sales/analysis/asset – How to find out what is at a customer. Use “Install Base” “Total Asset View”. Change the filter to get one account, and then click on the right and download to email/teams. Once downloaded, open the excel and select the data and move it to a pivot table.
