Results for “sports-data”

Sports betting fundamentals including spreads, moneylines, totals, parlays, teasers, props, and futures. Use when analyzing sports betting markets, converting odds formats, evaluating bet types, or building a sports betting strategy. Also trigger for 'point spread', 'moneyline', 'over under', 'parlay', 'prop bet', 'teaser', 'sports odds', or 'sportsbook'.

Coaching Analyst

Access prediction market data from Polymarket and Kalshi, including markets, prices, trades, orderbooks, positions, and cross-platform market matching. Use when you need current odds, historical market data, or wallet-level prediction market analysis.

Track key contacts who change jobs and draft warm outreach to movers at ICP companies

查询A股、港股、美股个股/指数/ETF的详细数据，包括：K线/分时、财务报表（三大报表多期查询，支持跨市场批量对比）、资金流向、技术指标、筹码分析、股东结构、分红除权、业绩预告、公司简况、ETF基金数据（详情/持仓/净值）；以及大盘指数、行业/板块行情、板块成份股、板块区间涨幅排行、指数成份股、热搜、新股日历、投资日历等市场数据。

Time-Series Data

贺炜（体育解说）认知与表达框架（压缩蒸馏）：文学比喻嵌入赛况、克制激情、终场金句… 触发：足球诗人解说 等。非煽动球迷对立

Facilitate a structured sprint retrospective to surface insights and produce actionable improvements with owners and deadlines.

Log workouts, plan routines, track progress, and get intelligent coaching for any fitness level.

SUPERSEDED by persistent-cache-gap-filling (v2.8.0). Cache data during symbol selection for instant repeat runs.

Roll dice, track scores, and manage game stats for tabletop gaming. Use when rolling dice, tracking scores, ranking players, reviewing history.

Prediction markets data - Polymarket, Kalshi markets, prices, positions, and trades. Use when: the user needs market data, stock analysis, watchlists, or portfolio workflows.

Tracks team OKRs with quarter banner, objective columns, key result progress bars, owner avatars, and status pills.

Emu: Generative Pretraining in Multimodality

Expert-level PostgreSQL database administration, advanced queries, performance tuning, and production operations

Turn sprint inputs into a kickoff-ready brief with goals, tickets, risks, and team context.

Score raw leads as HOT/WARM/COOL based on config-driven weights from agency.config.json

Create game plans with strategy and tactics. TRIGGERS - Use when user needs help with game-plan related tasks.

Apache Spark, Hadoop, distributed computing, and large-scale data processing for petabyte-scale workloads

AutoAugment: Learning Augmentation Strategies from Data

Use HasData APIs for web scraping and structured web data extraction.

Create game plans with strategy and tactics. TRIGGERS - Use when user needs help with game-plan related tasks.

Build a USASpending relationship snapshot for the incumbent and buying agency on a pursuit row. Use when user needs award flows and rel counts before battlecard or teaming work — deterministic from DuckDB bulk.

Facilitate a structured sprint retrospective — what went well, what didn't, and prioritized action items with owners and deadlines. Use when running a retrospective, reflecting on a sprint, creating action items from team feedback, or learning how to run effective retros.

Transforms scattered competitor data into a decision-ready product strategy report with positioning maps, feature matrices, pricing analysis, and opportunity windows.

Synthesize retrospectives into themes, root causes, decisions, and team improvements.

Fan one question out across every connected source and return a single ranked, deduplicated, attributed result set.

Use HasData APIs for web scraping and structured web data extraction.

EL2N: Deep Learning on a Data Diet