What Kalshi’s Missing Combo Categories Actually Mean

The missing Kalshi combo categories after July 2026 reflect a classification break, not evidence that combo trading stopped. Pew Research Center reports combined Kalshi and Polymarket volume for August, but its topic breakdown ends in July because the availability of category data for combos changed (Pew Research Center).

Choose the measure and month you want to compare; the tool shows whether Pew’s series supports it.

The Break Removes Topic Detail, Not Aggregate Volume

Pew’s data provider, The Block, normally treats Kalshi combos as a separate category and maps them to substantive topics where possible. Pew ended its category analysis in July because the availability of that category data changed.

Aggregate volume remained available. Pew reports a combined $47 billion for Kalshi and Polymarket in August, but it does not extend its sports, politics, cryptocurrency and other breakdown into that month. The $47 billion figure also cannot be treated as Kalshi-only volume.

Measure	Available After July?	Meaning of the Break
Combined Kalshi and Polymarket volume	Yes, for August	Aggregate activity remains measurable
Volume by topic	No	Combos cannot be classified consistently under the earlier method
Combo trading itself	Not reported as absent	Missing classifications do not mean zero activity

A dataset can therefore show continued overall trading while lacking the metadata needed to divide that trading among subjects. Treating missing topic volume as zero would confuse an unavailable classification with an observed absence of trades.

A Combo Can Belong to More Than One Topic

Kalshi describes each combo as a unique market with its own order book, priced through a request-for-quote system. Its settlement value is the product of the underlying positions, including any component that settles between $0 and $1 (Kalshi Help Center).

The traded object can span several subjects. A combo containing three football outcomes can reasonably be classified as sports. One combining a sports result with an entertainment outcome is genuinely cross-category.

An analyst then has four possible treatments:

• classify the entire combo by a primary leg;
• place it in a separate “combos” or “cross-category” group;
• assign its full volume to every represented topic, which double-counts it; or
• allocate its volume across the legs using a documented rule.

None is a neutral representation of the data. Each produces different topic totals and shares.

If the component metadata required by an established mapping rule becomes unavailable, continuing the old series can create a false trend. An apparent decline in sports share, for example, could represent newly unclassified sports combos rather than a change in what traders were trading.

Exchange Sharding Does Not Identify a Combo’s Topic

Kalshi also started moving combo creation away from its default exchange instance in August 2026. Its API documentation says a multivariate collection supporting all combos was created on shard 1 on Aug. 10. Combos over two specified legacy collections began being created there on Aug. 17.

Kalshi added an exchange_index field to market and event data and describes it as the authoritative source for identifying the correct exchange instance (Kalshi API documentation).

This timing does not establish that sharding caused The Block’s category-data limitation. Neither Pew nor Kalshi makes that claim.

It does show why a durable collection pipeline cannot use the default exchange instance, collection ticker or shard as a substitute for topic metadata. A combos exchange identifies infrastructure. It does not reveal whether the underlying legs concern sports, politics, cryptocurrency or entertainment.

July 2026 Is the Last Comparable Topic Month

For a topic-level time series based on Pew’s method, July 2026 should be the comparison endpoint unless later data are reconstructed under a consistent taxonomy. Pew’s final comparable month reports:

July 2026 Kalshi Category	Notional Taker Volume
Sports	$31.4 billion
Cryptocurrency	$6.1 billion
Politics	$169 million
Other	$2.4 billion

These figures are notional taker volumes. Each contract traded by a taker counts at its $1 potential payout rather than its transaction price (Pew Research Center). They do not measure the dollars traders paid, the amount of capital at risk or the number of contracts as an unweighted count.

That definition must remain fixed in any comparison. A series based on transaction value cannot be joined directly to the reported notional taker-volume series merely because both are labeled “volume.”

A Reconstruction Needs Explicit Unknowns

A reconstructed dataset should retain at least five fields:

1. the platform’s raw category, when available;
2. a combo or multivariate-market flag;
3. the categories of all recoverable underlying legs;
4. the mapping rule and taxonomy version; and
5. an “unknown” category rather than a guessed assignment.

Researchers should publish the share of volume with known categories for each month. When coverage drops, the output should show both the classified amount and the coverage rate.

Unknown combos should remain in the denominator when calculating category shares. Silently excluding them would inflate the shares of every visible category. If $1 of unclassified volume is removed from the denominator, the known categories appear more dominant even though their measured volume has not changed.

A reconstructed post-July series also should not be appended directly to Pew’s earlier categories if the new method differs. The defensible choices are to use a fixed pre-break window or rebuild the full history with one reproducible combo-mapping method.

Aggregate volume can continue across the break when collection remains complete, but topic trends cannot. The same caution applies to settled-market category histories and cross-platform data comparisons: a stable-looking label is comparable only while its definition and coverage remain stable.