SimpleFunctions
KalshiMay 3, 2026

Will Gujarat Titans score over 191.5 runs?

This contract is priced at 1¢ on Kalshi. Current book: 0¢ bid, 100¢ ask, 100¢ spread.

Implied probability

1¢
$1K volume
$1K liquidity
100% of event volume

Event outcomes

1

Family volume

$1K

Best sibling

Ticker

KXIPLTEAMTOTAL-26MAY03PBKSGT-GT192

Price history

1¢ current

1¢
25¢50¢75¢100¢
Apr 30, 2026May 3, 2026

Orderbook snapshot

0 / 100¢

Kalshi
100¢ spread
No public depth snapshot is cached for this contract yet.

Contract terms

Resolution, venue, and identifiers.

Resolution rules

If the total runs scored by Gujarat Titans is above 191.5 in the Punjab Kings vs Gujarat Titans IPL cricket match originally scheduled for May 3, 2026, then the market resolves to Yes.

Venue

Kalshi

Closes

May 3, 2026

Identifier

KXIPLTEAMTOTAL-26MAY03PBKSGT-GT192

Event family

This market.

This view keeps the individual contract next to its sibling outcomes. For long-tail search traffic, this is the useful context: where the current price sits inside the event, how much volume exists around the family, and which outcomes have actual depth.

Total volume

$1K

Outcomes

1

Highest price

Will Gujarat Titans score over 191.5 runs 1¢

Current share

100%

Indicators

Yield, cliff risk, volatility, and regime.

Regime

neutral

Score

0.5

Related readings

Matched from SimpleFunctions blog, opinions, technical guides, concepts, and learn pages.

Browse library
Blogmarkets

Kalshi vs Polymarket: Which Prediction Market Should You Trade?

In-depth comparison of Kalshi and Polymarket for prediction market traders. Regulatory structure, liquidity, fees, API tooling, and cross-venue trading with SimpleFunctions.

Opinioncomparison

Kalshi vs Polymarket: Mechanics, Fees, Regulation, Liquidity (2026)

Side-by-side comparison of Kalshi and Polymarket in 2026. Fee math, calibration data, withdrawal speed, and a decision tree for picking the right venue.

Opinionanalysis

Liquidity Availability Is the Real Edge in Prediction Markets

Implied yield, cliff risk, and overround all describe what to trade. Liquidity Availability Score describes whether the orderbook can absorb the trade. Why LAS is the indicator that decides who actually books P&L.

Technicalguide

Computing Liquidity Availability Score from the Orderbook

Step-by-step guide to computing the Liquidity Availability Score in TypeScript and Python, with edge cases for thin orderbooks, missing data, and the warm-cron coverage limitation.

Blogmarkets

Prediction Market Orderbook Analysis: Reading Depth, Spread, and Liquidity

How to read prediction market orderbooks. Binary settlement, spread-as-percentage, depth asymmetry, executable edge calculation, and cross-venue arbitrage analysis.

Technicalguide

Kalshi vs Polymarket: A Developer's Comparison of APIs, Orderbooks, and Liquidity

Data-driven comparison of Kalshi and Polymarket APIs, orderbooks, rate limits, and liquidity. Code examples for building on both prediction markets.

SimpleFunctions context

Index, screen, query, and monitor.

Open index