BM25 is pretty similar everywhere: if a word in your query appears a lot in a document, the score for that document (for that one query) goes up, especially if that word isn't in very many other documents.
There are a couple of tuning parameters, and the notion of what a "word" is varies based on the tokenizer and stemming you use.
So it won't be exactly the same, but it's likely to be close.
Curious how the ranking holds up on messy product text versus something like ParadeDB.
BM25 is pretty similar everywhere: if a word in your query appears a lot in a document, the score for that document (for that one query) goes up, especially if that word isn't in very many other documents.
There are a couple of tuning parameters, and the notion of what a "word" is varies based on the tokenizer and stemming you use.
So it won't be exactly the same, but it's likely to be close.