Recording 4 venues
KXBBSERIEASPREADKalshiSports24 open on Nov 1

Italy Serie A Spread historical data

 

Italy Serie A Spread price history on Kalshi: 380 markets, every order book change and trade, as daily Parquet files.

Example market: Pallacanestro Trieste 2004 wins by over 22.5 points

3.4 million rows380 markets25 MB7 datasets, full order book includedUpdated daily

Datasets

One file per dataset per UTC day. Data dictionary · Hourly coverage

DatasetWhat it holdsPlanSample
Order book (L2, incremental)
book_l2
Every price level and every change to the YES and NO bid books. Snapshot rows set a level; delta rows add to it.
9 columns
  • ts_recvtimestamp[ns, UTC]
  • ts_venuetimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • seqint64
  • is_snapshotbool
  • sidestring
  • pricefloat64
  • sizefloat64
Full bookSampleParquet·CSV
Order book snapshots (top 10, 1 second)
book_snap_1s
The top ten YES bid and ask levels at the end of every second in which the book changed.
43 columns
  • tstimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • bid_px_0float64
  • bid_px_1float64
  • bid_px_2float64
  • bid_px_3float64
  • bid_px_4float64
  • bid_px_5float64
  • bid_px_6float64
  • bid_px_7float64
  • bid_px_8float64
  • bid_px_9float64
  • bid_sz_0float64
  • bid_sz_1float64
  • bid_sz_2float64
  • bid_sz_3float64
  • bid_sz_4float64
  • bid_sz_5float64
  • bid_sz_6float64
  • bid_sz_7float64
  • bid_sz_8float64
  • bid_sz_9float64
  • ask_px_0float64
  • ask_px_1float64
  • ask_px_2float64
  • ask_px_3float64
  • ask_px_4float64
  • ask_px_5float64
  • ask_px_6float64
  • ask_px_7float64
  • ask_px_8float64
  • ask_px_9float64
  • ask_sz_0float64
  • ask_sz_1float64
  • ask_sz_2float64
  • ask_sz_3float64
  • ask_sz_4float64
  • ask_sz_5float64
  • ask_sz_6float64
  • ask_sz_7float64
  • ask_sz_8float64
  • ask_sz_9float64
ResearchSampleParquet·CSV
Top of book (every change)
bbo
Best YES bid and ask with sizes, one row each time any of the four values changes.
8 columns
  • ts_recvtimestamp[ns, UTC]
  • ts_venuetimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • yes_bidfloat64
  • yes_bid_sizefloat64
  • yes_askfloat64
  • yes_ask_sizefloat64
ResearchSampleParquet·CSV
Top of book (1-minute bars)
bbo_1m
Minute bars of the YES mid with closing bid and ask, plus trade count and volume.
12 columns
  • minutetimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • mid_openfloat64
  • mid_highfloat64
  • mid_lowfloat64
  • mid_closefloat64
  • yes_bid_closefloat64
  • yes_ask_closefloat64
  • book_updatesint64
  • trade_countint64
  • trade_volumefloat64
ResearchSampleParquet·CSV
Trades
trades
Every recorded fill with YES price, size, and taker side.
8 columns
  • ts_recvtimestamp[ns, UTC]
  • ts_venuetimestamp[ns, UTC]
  • tickerstring
  • seriesstring
  • trade_idstring
  • yes_pricefloat64
  • sizefloat64
  • taker_sidestring
ResearchSampleParquet·CSV
Markets (point-in-time universe)
markets
One row per market open at any time during the day: terms, strikes, times, tick size, rules, fees, and outcome.
22 columns
  • tickerstring
  • event_tickerstring
  • seriesstring
  • titlestring
  • yes_sub_titlestring
  • categorystring
  • market_typestring
  • statusstring
  • resultstring
  • open_tstimestamp[ns, UTC]
  • close_tstimestamp[ns, UTC]
  • expected_expiration_tstimestamp[ns, UTC]
  • floor_strikefloat64
  • cap_strikefloat64
  • strike_typestring
  • tick_structurestring
  • price_rangesstring
  • can_close_earlybool
  • fee_typestring
  • fee_multiplierfloat64
  • rules_primarystring
  • rules_secondarystring
ExplorerSampleParquet·CSV
Settlements
settlements
Every market that settled during the day: result, settlement value, the underlying value it settled on, and when.
15 columns
  • tickerstring
  • event_tickerstring
  • seriesstring
  • categorystring
  • resultstring
  • settlement_valuefloat64
  • expiration_valuestring
  • close_tstimestamp[ns, UTC]
  • settlement_tstimestamp[ns, UTC]
  • ts_recvtimestamp[ns, UTC]
  • floor_strikefloat64
  • cap_strikefloat64
  • strike_typestring
  • coin_price_startfloat64
  • coin_price_endfloat64
ExplorerSampleParquet·CSV
# pip install "kalshieye[pandas]"
from kalshieye import Client

kx = Client()  # reads KALSHIEYE_API_KEY
df = kx.load("bbo_1m", "2026-10-27", "2026-10-27", series="KXBBSERIEASPREAD")

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