Dynamic pricing behaves like a thermostat, which is why a ticket price moves

The objective is a sales curve

A venue with a fixed date and a fixed capacity has to sell a specific number of places by a specific moment, after which unsold inventory is worth nothing. Dynamic pricing systems are configured against a target sales curve describing how much should have sold by each point before the event. When actual sales run ahead of that curve, the system raises prices, because demand is evidently stronger than the pricing assumed.

When sales fall behind, it lowers them, since the alternative is arriving at the date with inventory that expires unsold. The mechanism is therefore a feedback loop with a target, which is why comparing it to a thermostat is more accurate than comparing it to an auction.

Why prices fall as well as rise

The public perception of dynamic pricing is that it only ever increases, which reflects attention rather than how the systems actually behave. Fixtures with weak demand see reductions, sometimes substantial ones, because the operator would rather sell at a lower level than hold empty seats. Those reductions are less visible because nobody complains about them and because they often appear as offers rather than as headline price changes.

The asymmetry in perception is reinforced by the fact that high-demand fixtures are the ones most people are trying to buy. Across a full season the system moves in both directions far more evenly than the discussion of it suggests.

Sections are priced separately

A venue is divided into categories that are treated as separate inventories, each with its own sales curve and its own price behaviour. This means a fixture can be selling strongly in one category and weakly in another, with prices moving in opposite directions on the same day. It also means the relative cost of two sections is not fixed, and a section that is usually more expensive can temporarily become the cheaper option.

Buyers who check only one category see a fraction of what is happening and frequently conclude that prices only move upward. Comparing across categories is the simplest way to see the system working in both directions at once.

What the buyer can infer

A price that has risen indicates demand ahead of expectation, which also implies that availability is contracting and waiting carries real risk. A price that has fallen indicates the opposite, and suggests that waiting further may produce a better outcome, though not indefinitely. Near the date the system's behaviour changes character, since remaining inventory is about to become worthless and the incentive to discount grows sharply.

That endgame is highly variable between operators and events, which is why late strategies work spectacularly sometimes and fail completely at other times. The reliable inference is directional rather than numerical, telling a buyer which way pressure is running rather than what will happen next.

Why it spread despite being unpopular

Fixed pricing leaves money uncollected on high-demand events and leaves seats empty at low-demand ones, both of which are visible losses to an operator. Dynamic pricing addresses both, and it also captures value that would otherwise flow to resellers buying underpriced inventory to sell on. That second argument is the one operators make publicly, since it reframes the practice as competing with resale rather than as extracting more from buyers.

Supporters generally dislike it because it makes attendance unpredictable in cost and rewards those able to buy at short notice. The disagreement is genuine and unlikely to resolve, since the two sides are optimising for different things.