RealPage, Inc., Rental Software (No. II)
The RealPage, Inc., Rental Software (No. II) MDL sits in the Middle District of Tennessee before Judge Waverly D. Crenshaw, consolidated since April 2023. The litigation alleges that RealPage's revenue-management software functioned as a mechanism for horizontally competing landlords to coordinate rental pricing — pooling non-public data on rents, occupancy, and lease terms and using a common algorithm's pricing recommendations in place of independent pricing decisions each landlord would otherwise make.
This docket sits at the center of one of the more consequential open questions in current antitrust law: whether coordination facilitated through a shared software intermediary, without direct communication among the competing defendants themselves, satisfies the legal standard for an unlawful agreement under Section 1 of the Sherman Act. How courts resolve that question — including how they treat the degree of data specificity shared through the algorithm and whether landlords retained meaningful pricing discretion — will do more to determine this docket's trajectory than any single procedural event, because it goes to whether the plaintiffs' core theory is legally viable at all before the case ever reaches a damages phase.
The existence of a companion "No. II" docket alongside related RealPage rental-software litigation elsewhere adds a structural wrinkle: because the legal theory, and likely some of the underlying software architecture at issue, overlaps across the related matters, a significant ruling on the algorithmic-coordination theory in one docket is likely to shape how the same theory is evaluated in this one, even though the two proceed on separate tracks with potentially different defendant sets and claimant pools.
Given how novel and unsettled the underlying legal theory is, this is a docket where the resolution path is genuinely harder to read from procedural posture alone than in a conventional price-fixing MDL — which is exactly the kind of situation where tracking the doctrinal development itself, not just the docket schedule, matters most. Criterica Intelligence's regulated outcomes intelligence is built to surface that structural and doctrinal read across active MDLs, this one included, without predicting how any court will ultimately rule.
Plaintiffs allege the software let competing landlords pool non-public rent, occupancy, and lease data and follow a common algorithm's pricing recommendations, functioning as a substitute for the independent pricing decisions antitrust law otherwise expects competitors to make.
Courts are still working out whether coordination facilitated through a shared software intermediary, without direct communication among the landlords themselves, meets the legal standard for an unlawful agreement — a live and unsettled question in current antitrust law.
The two matters share an overlapping algorithmic-coordination theory and proceed on separate tracks, but a significant ruling on that shared theory in one is likely to influence how the same question is evaluated in the other.
If the underlying theory doesn't survive dispositive motions, affected claims could be narrowed or dismissed before reaching a damages phase, which is why the legal-theory question matters more here than in a conventional price-fixing docket.
Statistics shown reflect historical or illustrative model outputs derived from real case data. They are not predictions or guarantees of any individual outcome. Litigation results depend on facts, jurisdiction, judge, and counsel, and vary case by case. Model accuracy is subject to selection effects and changing legal dynamics.