WNBA Prediction Data — Kalshi & Polymarket
Tick-by-tick trades and L2 order-book depth for 42 WNBA series on Kalshi & Polymarket — WNBA spreads and totals, player points and rebounds, season win totals. 4,958 series-days covering May 2025 – present; 1.4M trades · $87.4M turnover over the last 30 captured days. Every contract captured co-located with nanosecond venue and receive timestamps — sold as day bundles, €1 per day, bought as a guest with instant download.
WNBA on Kalshi & Polymarket
WNBA game lines, player props, win totals and all-team markets.
Every series below is archived at full feed resolution — each contract file carries every trade print (price, size, side) and Level-2 order-book updates in one normalized, zstd-compressed schema. A series-day bundle holds all contracts of the series for one UTC day.
Most traded WNBA series (last 30 days)
Ranked by USD turnover from our own daily statistics — the series a market maker or bot builder should start with.
| # | Series | Venue | Trades (30d) | Turnover (30d) | Days | |
|---|---|---|---|---|---|---|
| 1 | Women's Pro Basketball Game | Kalshi | 489,350 | $45.0M | 17 | Buy days |
| 2 | Women's Pro Basketball Total | Kalshi | 305,412 | $13.0M | 17 | Buy days |
| 3 | Women's Pro Basketball Spread | Kalshi | 218,303 | $11.6M | 17 | Buy days |
| 4 | WNBA (games & props) | Polymarket | 74,837 | $9.5M | 27 | Buy days |
| 5 | Women's Pro Basketball 1st Half Spread | Kalshi | 34,237 | $1.6M | 14 | Buy days |
| 6 | Women's Pro Basketball Player Points | Kalshi | 43,877 | $1.0M | 14 | Buy days |
| 7 | Women's Pro Basketball 1st Quarter Total | Kalshi | 22,857 | $718.0K | 14 | Buy days |
| 8 | Women's Pro Basketball 1st Half Winner | Kalshi | 13,405 | $687.5K | 16 | Buy days |
| 9 | Women's Pro Basketball 1st Quarter Spread | Kalshi | 15,529 | $602.6K | 14 | Buy days |
| 10 | Women's Pro Basketball 3rd Quarter Total | Kalshi | 17,735 | $585.5K | 14 | Buy days |
Trades and USD turnover summed over every contract of the series, from the recorded tick data; 30 days to 2026-09-22. Series without statistics in the window are omitted.
WNBA activity per venue
| Venue | Series | With stats | Trades (30d) | Turnover (30d) |
|---|---|---|---|---|
| Kalshi | 41 | 40 | 1,292,503 | $77.9M |
| Polymarket | 1 | 1 | 74,837 | $9.5M |
30 days to 2026-09-22, from our own daily statistics per contract.
WNBA — development since capture
4,915,459 trades and $287.4M of USD turnover across 41 series since 2026-07-18; busiest single series-day 2026-08-16 with $8.9M, biggest contract KXWNBAGAME-26AUG16INDATL-IND (2026-08-16, $3.0M).
| Month | Series active | Days | Trades | Turnover (USD) | Avg / day | Contracts traded | L2 updates | vs previous month |
|---|---|---|---|---|---|---|---|---|
| Sep 2026 (month to date) | 40 | 22 | 439,120 | $29.2M | $1.3M | 6,452 | 175.4M | — |
| Aug 2026 | 41 | 31 | 3,750,360 | $228.9M | $7.4M | 20,810 | 413.9M | — |
| Jul 2026 | 8 | 14 | 725,979 | $29.3M | $2.1M | — | — | — |
WNBA series — trades and USD turnover summed per calendar month (UTC) over every contract, from our own daily statistics of the recorded tick data. Days = captured UTC days; a partial month shows no month-over-month change. Contracts traded and L2 (order-book) updates exist for days captured with the extended statistics.
WNBA — turnover by weekday
Sundays are the busiest day at about $3.9M of USD turnover, averaged over the captured days of the last 30.
| Weekday (UTC) | Avg turnover / day | USD | Avg trades | Days |
|---|---|---|---|---|
| Monday | $2.5M | 37.6K | 5 | |
| Tuesday | $3.4M | 53.7K | 5 | |
| Wednesday | $1.8M | 27.6K | 4 | |
| Thursday | $1.8M | 27.5K | 4 | |
| Friday | $3.5M | 54.2K | 4 | |
| Saturday | $3.6M | 61.1K | 4 | |
| Sunday | $3.9M | 57.3K | 4 |
WNBA series — average USD turnover and trades per weekday over the captured days of the last 30, from our own daily statistics; weekdays without a captured day show —.
Rising WNBA series — 30 days vs the 30 before
| # | Series | Venue | Turnover (30d) | Prior 30d | Growth (avg / day) | Trades (30d) |
|---|---|---|---|---|---|---|
| 1 | WNBA RPG Leader | Kalshi | $23.0K | $3.9K | +193.2 % | 397 |
| 2 | Pro Women's Basketball MVP | Kalshi | $93.4K | $27.2K | +71.5 % | 6,731 |
| 3 | WNBA APG Leader | Kalshi | $12.9K | $3.8K | +67.9 % | 875 |
| 4 | WNBA Coach of the Year | Kalshi | $10.6K | $3.3K | +59.0 % | 488 |
| 5 | WNBA Defensive Player of the Year | Kalshi | $10.9K | $3.7K | +46.2 % | 1,226 |
Growth of average USD turnover per captured day, the 30 days to 2026-09-22 against the 30 days before; series need ≥ 10 captured days in both windows and ≥ $10K of turnover in the current one. From our own daily statistics.
WNBA prediction markets — trades and turnover per day
Every captured UTC day of the last 30, summed over the 42 WNBA series — how much these markets trade day by day, from our own tick capture.
| UTC day | Series with stats | Contracts traded | Trades | Turnover | Buy share | L2 updates |
|---|---|---|---|---|---|---|
| 2026-09-22 | 40 | 947 | 122,030 | $8.1M | 63 % | 27.7M |
| 2026-09-21 | 40 | 642 | 43,800 | $3.1M | 61 % | 20.3M |
| 2026-09-20 | 40 | 1,196 | 72,318 | $5.1M | 69 % | 29.9M |
| 2026-09-19 | 40 | 1,017 | 94,924 | $5.7M | 65 % | 29.6M |
| 2026-09-18 | 40 | 1,249 | 83,278 | $6.0M | 62 % | 30.0M |
| 2026-09-17 | 40 | 476 | 9,556 | $797.0K | 71 % | 15.7M |
| 2026-09-16 | 24 | 158 | 2,006 | $94.0K | 85 % | 11.1M |
| 2026-09-15 | 24 | 108 | 1,306 | $38.2K | 88 % | 7.1M |
| 2026-09-14 | 23 | 52 | 530 | $12.0K | 73 % | 390.7K |
| 2026-09-13 | 20 | 56 | 383 | $6.8K | 58 % | 327.2K |
| 2026-09-12 | 20 | 34 | 335 | $2.6K | 89 % | 133.3K |
| 2026-09-11 | 20 | 33 | 384 | $8.6K | 86 % | 182.9K |
| 2026-09-10 | 20 | 42 | 400 | $4.8K | 78 % | 208.3K |
| 2026-09-09 | 20 | 39 | 681 | $16.3K | 75 % | 224.6K |
| 2026-09-08 | 20 | 38 | 646 | $9.8K | 90 % | 164.1K |
| 2026-09-07 | 20 | 40 | 442 | $9.5K | 79 % | 320.3K |
| 2026-09-06 | 20 | 46 | 875 | $6.7K | 64 % | 333.9K |
| 2026-09-05 | 20 | 42 | 775 | $11.3K | 34 % | 339.5K |
| 2026-09-04 | 20 | 55 | 724 | $18.6K | 93 % | 219.7K |
| 2026-09-03 | 19 | 58 | 902 | $14.3K | 66 % | 251.3K |
| 2026-09-02 | 19 | 56 | 1,225 | $20.8K | 66 % | 326.4K |
| 2026-09-01 | 19 | 68 | 1,600 | $31.4K | 65 % | 471.1K |
| 2026-08-31 | 40 | 398 | 60,104 | $3.3M | 58 % | 7.7M |
| 2026-08-30 | 40 | 909 | 155,759 | $10.5M | 63 % | 23.6M |
| 2026-08-29 | 40 | 1,138 | 148,296 | $8.7M | 66 % | 22.7M |
| 2026-08-28 | 40 | 890 | 132,418 | $7.7M | 63 % | 19.0M |
| 2026-08-27 | 40 | 693 | 99,251 | $6.3M | 62 % | 14.2M |
| 2026-08-26 | 41 | 869 | 106,478 | $6.9M | 65 % | 17.4M |
| 2026-08-25 | 41 | 807 | 142,798 | $8.5M | 67 % | 19.3M |
| 2026-08-24 | 41 | 891 | 83,116 | $6.1M | 64 % | 13.9M |
Per UTC day, summed over every WNBA series that has statistics for that day, from every trade print of every contract in our tick archive. Trades and USD turnover are exact; contracts traded, buy share and L2 (order-book) updates exist for days captured with the extended statistics — earlier days show —.
Most traded WNBA contracts on 2026-09-22
The single event contracts with the most USD turnover on the newest captured day — with open and close price and the outcome implied by the last print.
Single contracts ranked by USD turnover on 2026-09-22 (UTC), from every trade print in our tick archive. Prices quote 0..1; the implied outcome reads the last print of the day (≥ 0.97 Yes/Up, ≤ 0.03 No/Down) — venues publish the official result. Each contract’s day file is sold individually, the whole series day as a bundle.
Biggest WNBA moves in the last 24 hours
From the live prediction-movers snapshot (contracts of this topic's series only, settled markets filtered). Intraday — not part of the archived dataset.
| Contract | Venue | Price 24h ago → now | Δ | 24h turnover |
|---|---|---|---|---|
| KXWNBAMVP-26-AWIL | Kalshi | 0.97 → 0.88 | -0.09 | $29.2K |
Live contracts ranked by absolute 24-hour price change (contracts quote 0..1; settled or near-settled contracts excluded). Snapshot 2026-09-23 16:18 UTC. Full list in the prediction movers.
Kalshi WNBA series
Largest archive first. Each series page lists its exact coverage, day count and recent days; day bundles are bought in the shop calendar.
Polymarket WNBA series
Largest archive first. Each series page lists its exact coverage, day count and recent days; day bundles are bought in the shop calendar.
| Series | Venue | Interval | Days | Coverage | Size | Price/day | |
|---|---|---|---|---|---|---|---|
| WNBA (games & props) | Polymarket | event | 297 | May 2025 – present | 13.7 GB | €1 | Buy days |
Why buy WNBA prediction-market data here
Four things every page on this site is built on — and the reason the numbers above exist at all.
We record everything
The complete public feed of each venue as it was published: every Level-2 snapshot and update at the venue's full book depth, every trade with its aggressor side, every quote, funding, mark-price and liquidation event — for every instrument the venue lists, every UTC day since we added the venue. Nothing sampled, no top-N cut, no on-demand capture.
Institutional grade
Captured co-located at the venue with the exchange timestamp and our receive timestamp in integer nanoseconds, an event-id chain that makes any gap visible, and one normalized schema across 35+ venues — the same capture our own high-frequency trading engine and enterprise feeds run on.
€1 per instrument-day
Any instrument-day is €1, series-day bundles start at €1 — no subscription, no minimum order, no tiers to unlock. Credit packs lower the effective price and never expire, and every venue has free full-day samples to test against first.
Self-service for everyone
Pick the days in the Data Shop, pay by card as a guest and download immediately — no sales call, no enterprise contract, no KYC. Coding agents buy the same files through the MCP server, and the free Agent Skill teaches them the format.
WNBA prediction-market data — FAQ
Does Kalshi have WNBA markets?
Yes — spreads, totals, team totals, player points and rebounds props, win totals and all-team/all-defensive selections. Polymarket lists WNBA games and props as one family.
How is WNBA prediction-market data sold?
One purchase covers every contract of the series for one UTC day — every trade print and the complete Level-2 book per contract, captured co-located with nanosecond timestamps — €1 per series-day, bought as a guest with instant download.
How far back does the WNBA data go?
Coverage runs May 2025 – present — 4,958 series-days across 42 series on Kalshi & Polymarket. Each series page lists its exact span.
Can I get WNBA prediction-market data as CSV or Parquet?
Yes — trades export as gzipped CSV or Parquet at no extra cost, with integer microsecond UTC timestamps that load straight into pandas, polars or DuckDB. Both venues record full order-book depth without a separate BBO stream, so book data ships in the native tick file — the free reader script converts it locally. See the formats overview.
How much does WNBA prediction-market data cost?
€1 per series-day bundle — every contract of the series for that UTC day — no subscription, no minimum order. Pick days in the shop calendar, pay as a guest, download immediately.
Do I need an account or a sales call?
No. Pick the WNBA series-days in the Data Shop, pay by card as a guest and download immediately — no subscription, no minimum order, no KYC, no enterprise contract, no sales call. Coding agents buy the same bundles through the MCP server.
How is the WNBA data captured?
Co-located at the venue, message by message: every Level-2 update and every trade print carries the exchange timestamp and our receive timestamp in integer nanoseconds, an event-id chain makes any gap visible, and one normalized schema across 35+ venues means a parser written for Binance reads these files unchanged. It is the same capture our own high-frequency trading engine runs on — nothing sampled, no top-N cut.
What was the busiest WNBA trading day?
2026-08-16 — $8.9M of USD turnover over 118,399 trades in a single series-day. Since our statistics began on 2026-07-18, 41 WNBA series recorded 4,915,459 trades and $287.4M in total; the biggest single contract was KXWNBAGAME-26AUG16INDATL-IND on 2026-08-16 at $3.0M. Sundays are the busiest weekday at about $3.9M per day.