The heavily mathematical part is the proof that goes with the justification for the bidding system. Explaining the merits of the auction or explaining what the fraud is is pretty easy.
Professor Whinston didn't work at Google, did he? He just makes his opinion based on some emails found in the discovery?
For all we know, it is equally plausible that Google at some point launched a new prediction model, and in a traffic experiment it showed up the following stats: increase on campaign average cpc price, decrease on average auction discount (or whatever the metric for the gap to 2nd bid is called), and no harm to conversion cost. Team manager reported the metrics highlights to their higher ups. Emails found in discovery... ends with guys on HN throwing fraud accusations, pretty easy.
That person is an expert witness. He's there to explain to non-experts the meaning of what's been found in discovery. What he's saying to the court has likely been vetted by the prosecution.
If your claim is that the prosecution is making up wild shit, then Google's attorneys should have a field day rebutting it.
This trial is antitrust, not fraud, so Google lawyers will be rebutting it only to the point it helps them. And they will try to keep it sealed anyways. Since it doesn't seem that either party is willing to describe the auction algorithmically, we may never get to learn it, apart from reading Albert Cory substack
In particular, the linked article mentions 'squashing', and a quick research finds https://www.theregister.com/2010/09/16/yahoo_does_squashing/ where it is mentioned that ads are ranked not by bids, but rather by "bid multiplied by click probability".
In the ideal world, the first question to the auction expert should be "what price is charged, if due to click probability, the second bid ad wins the auction?" and the follow ups would be "but surely, the price charged isn't higher than the bid, or else the advertisers would notice that?" and "supposing the third bid ad wins due to the click probability, how would disabling that multiplying by click probability affect google revenue?"