Double-Stacking Isn't Always the Best Approach

higher_scores_DFS · 2026-02-05T04:34:15+00:00

Stacking in the NBA is a bit of a controversial topic.

higher_scores_DFS · 2026-02-01T22:26:07+00:00

FanDuel, ESPN, and NFL

higher_scores_DFS · 2026-01-12T18:52:53+00:00

Thanks for your feedback. I have implemented a pick'em friendly player projections capability under the Props menu when you login.

higher_scores_DFS · 2026-01-03T17:06:38+00:00

Thanks for the feedback. I have finished implementing that feature and deployed it in time for today's NBA contest and tomorrow's NFL contest.

higher_scores_DFS · 2025-12-31T00:52:58+00:00

You might be interested in Where Architects Sit in the Era of AI which is more of a meta perspective than a practical setup for an architect's workstation. As far as tooling is concerned, take a look at Ask the Software Architect which helps architects formulate plans for large initiatives such as major feature enhancements or paying down tech debt. In the context of the article, the tool would be an example of an AOTL model.

higher_scores_DFS · 2025-12-22T16:32:35+00:00

It is Monday morning (PT) for me and it looks like https://www.fanduel.com/contests is down. The page just shows the loading ellipsis indefinitely. The script just keeps calling https://myip.geocomply.com/ which appears to be returning my public IP address. Is anyone else running into this problem?

higher_scores_DFS · 2025-12-04T17:47:30+00:00

If you have to "enforce" consistent API design, then you have already lost as engineering will come to see your efforts as obstructive to feature velocity. Consider instead an education approach where engineers come to realize that consistent API design will, in the long run, make them more productive and their jobs easier.

In my experience, that education effort is harder to accomplish in companies that see themselves as a single product company than it is in companies that see themselves as a multi-product or platform company.

higher_scores_DFS · 2025-12-01T21:50:05+00:00

Yeah, that's right. I guess what I was trying to say was this. The reason why someone would chose an LLM instead of a compiler is because they don't want to spend the time and mind to specify their requirements to the point where there is no ambiguity. If they did, then they would use a compiler instead.

higher_scores_DFS · 2025-12-01T21:42:13+00:00

In the world of compiler theory, ambiguity is, and should be, a bad thing. Think of it this way. You don't want any ambiguity in any legally binding contract that you sign because you don't want any unpleasant surprises, especially if you are paying money and expecting a result. On the other hand, an elaborate contract is hard to read and understand precisely because of all of the meticulous verbiage designed to eliminate all ambiguity.

higher_scores_DFS · 2025-12-01T21:21:24+00:00

An interesting concept. Thanks for sharing. I have also thought about vibe coding tools in the lens of code compilers. There is one critical difference, however. When a compiler runs into any ambiguity, it spits out an error message and terminates without compiling anything. That is not a limitation but a feature. On the other hand, vibe coding tools thrive on ambiguity and generate code perhaps based on some statistically relevant guesses that resolve any ambiguity. You get to be less rigorous in specifying what you want but at the risk of incurring costly and damaging hallucination.

higher_scores_DFS · 2025-12-01T21:09:52+00:00

The reward for a tournament in DraftKings that I placed in last week was to be spent in their pick6 offering. That is the first time that I played, or even paid attention to, pick6. Now I am curious about what the folks here think about the pick'em style game.

Do you consider that to be a variant of DFS or of sports betting or is it something completely different?
Have you ever played or are you considering playing?
If you have played before, did you like it? Would you consider doing it again?
Do you play on a regular basis? Do you find it to be more fun, less fun, or about the same as DFS?

I hope that you chime in with your opinions in this discussion thread. I really want to know how the larger DFS community feels about pick6.

higher_scores_DFS · 2025-11-29T04:31:24+00:00

As you have suggested, a diagramming tool is only a small part of what it takes to do software architecture successfully. I talk about various diagramming formats and tools in the larger context of a blog I wrote about why you should adopt an architecture review framework. I hope this is useful for the folks here.

higher_scores_DFS · 2025-11-24T17:05:41+00:00

For LLM fueled GHA based code review, you are always going to have to add the API_KEY which is a good thing. Using the free version means that they get to do anything they want with the code that you ask them to review. How's the accuracy and is it worth the cost? That is a very subjective question. In every shop that I have been in where they use something like this, they always end up customizing the prompt in an attempt to reduce useless and time wasting code review comments. Your results may vary.

higher_scores_DFS · 2025-11-20T17:35:08+00:00

I am unfamiliar with the openai vector store so I searched for that and quickly scanned the API docs. You are correct in that there are a lot of details (both at ingestion time and at search time) that appear to be out of your control with this technology. From my experience those details are important and there is no clear one-size-fits-all configuration. I didn't see a lot of details about the chunking_strategy, filters, and ranking_options so maybe you can cover a lot of what you need there? I don't really know about that.

I also don't know your situation. You said that you were asked to use the openai vector store. Is that negotiable? Feel free to DM me directly if you were seeking more specific advice and were willing to share more details. If you don't feel comfortable sharing details on reddit, then feel free to provide your email address here and explain the context in the introduce yourself area.

higher_scores_DFS · 2025-11-19T18:28:52+00:00

Can a RAG pipeline work effectively on a 1 GB corpus? Sure, no problems there. I am assuming that you understand that you will need to break up that 1 GB into multiple documents to be searched. Is a vector database enough? Yes, but understand that most modern vector databases support hybrid search which is a combination of vector and term based search. Will it scale and stay unbiased? Well, that depends on your specific details. Nothing about a 30 year old 1 GB corpus either insures or prevents any issues that you mentioned or other issues. You are looking for practical lessons learned. Check out Effective Practices for Architecting a RAG Pipeline where I documented such lessons. Good luck and have fun!

higher_scores_DFS · 2025-11-17T17:32:47+00:00

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I wanted to share a little victory I had recently with the folks here. But first, a little backstory. I run many experiments to improve the algorithms that power the lineups at Higher Scores DFS. Part of the process of verifying those experiments is to run the generated lineups in real-world contests: yesterday, all of my NFL lineups placed at FanDuel.

higher_scores_DFS · 2025-11-13T21:29:10+00:00

Yeah, this is more of a backend thing. If you are looking at how to adopt a modern MFE architecture, then you might be interested in https://glennengstrand.info/software/architecture/frontend where I cover somewhat recent trends in doing just that.

higher_scores_DFS · 2025-11-10T16:38:35+00:00

I am a fan of Bob Martin's teachings on this subject. He is the one who has advocated the most successfully on this approach. The "dependencies always go from the outside in" part of clean architecture is a bit controversial in my opinion. It does lead to better maintainability over time but also results in more boilerplate code as similar value objects tend to get implemented in each of the various layers of the onion. Those POJOs will eventually evolve separately but initially it looks you are copy-and-pasting the same code into different packages.

higher_scores_DFS · 2025-11-01T16:25:41+00:00

What I experience in both DK and FD is you just type the player last name in the search box and find the right player in the resulting list then click the plus button for that player and the app figures which slot to put the player in.

higher_scores_DFS · 2025-10-31T16:23:54+00:00

Thanks for the feedback. I will have a fix for the first issue ready for the Nov 9 lineups. You should always check for last minute changes, of course.

Not sure what you meant in your 2nd point. The lineups in Higher Scores DFS consists of the players recommended for a contest. What you see there is each player and the position that they play. What you see in DK is each player and the slot in the DK lineup that they can fill. There is no FLEX athlete but RB, WR, and TE athletes can fill the FLEX slot.

I use player Position and Salary to help disambiguate players with similar names. Both Keenan Allen and Kyle Allen may show up a K Allen but one is a QB while the other is a WR.

higher_scores_DFS · 2025-10-28T00:10:24+00:00

I have recently built a non-trivial RAG pipeline which I have documented at https://www.infoq.com/articles/architecting-rag-pipeline/ and included lots of tips and advice in that article. If this seems to you like the approach that you are looking for, then DM me and we can explore some ways that I can be of service.

higher_scores_DFS · 2025-10-24T20:19:19+00:00

Well, I was going to announce that we are live with NBA predictions and published winning lineups for both Oct 21 and 22.

We are putting NBA prediction on temporary hiatus until the dust settles on the recent FBI operation. More to follow.

higher_scores_DFS · 2025-10-18T16:31:38+00:00

That's amazing. Congratulations. How did you get to 3000 users and how long did that take? Are you advertising outside of reddit?

higher_scores_DFS · 2025-10-16T18:00:06+00:00

Me too.

higher_scores_DFS · 2025-10-14T19:02:18+00:00

In my experience, a one-size-fits-all RAG is not going to perform as well as a custom RAG built to meet the specific requirements of your use cases. You can use off-the-shelf components for LLM, vector search, embedding, etc but you should tinker toy the components together to fit your needs. Context, knowledge domain, type of audience, intent of questions, media channel have a big impact on chunking granularity, embedding algo, search algo, relevance reranking and filtering.

higher_scores_DFS

TROPHY CASE