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Backend Engineering projects

Browse public backend engineering work from Wooble professionals. These pages help candidates, recruiters, and Google discover actual shipped projects instead of thin profile lists.

Public Backend Engineering work

36 projects matched to this search intent.

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HONK LIVE — Real-Time Mumbai Bus Tracker with Smart Leave-Time Intelligence

Reduced commute anxiety for 100% of test users by delivering real-time bus ETAs and auto-calculated leave times — zero taps to know wh…

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Honk Hackathon

Reduced commuter waiting time by providing accurate real-time bus ETAs. Enabled informed travel decisions through live delay and route…

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OnRoute — Real-Time Commute Intelligence for Delhi Commuters

AI-powered bus tracker cuts commute uncertainty — live ETAs, delay predictions & leave-by alerts for 4.5M daily DTC riders

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IPL CRUNCH '26 - Backed by 289,673 Balls of Data

Analyzed 289,673 IPL deliveries across 19 seasons to prove the toss is statistically irrelevant,while middle-over execution (+7.5 runs…

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IPL Ball-by-Ball Analysis — Toss, Phase & Venue Intelligence Across 1,218 Matches

Analysed 289,673 IPL deliveries to prove that scoreboard pressure outweighs venue conditions — teams chasing 200+ at Chinnaswamy win o…

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Pitch Vision Analytics: IPL AI Strategy Engine

Built a live IPL strategy engine with phase-aware win prediction, pressure-based player intelligence, and a legal over-by-over Captain…

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IPL Crunch ’26: Decoding What Actually Wins IPL Matches

Analysed and built 4 specialized analytical datasets for toss analysis, phase-wise scoring, batting dominance, and bowling impact.

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The Aggregation Paradox: A Multi-Layered Granularity Model for Predicting Cricket Scoreboard Gravity

Late-game speed wins critical moments, but steady middle-overs volume wins match tournaments.

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Wobble IPL Analytics

“IPL victories are influenced far more by death-over performance and finishing strength than by toss advantage alone.”

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IPL'26 Analytics

Processed multi-season IPL datasets to compare toss influence, scoring phases, and top player performances with data-backed insights.

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CricMind: High-Performance IPL Analytics & AI Simulator

Processes 395,011 deliveries across 1,226 matches in under 200ms with a fully offline, zero-latency browser intelligence engine.

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IPL Insights Engine: ML-Powered Match Predictor & Player Scouting Dashboard

Achieved 82% match prediction accuracy by training a Random Forest classifier on 15+ years of historical IPL data.

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IPL MatchPulse AI – Change One Ball, Rewrite the Match

Built an AI-powered IPL match simulator to predict win probability, simulate “what-if” scenarios, and explain how toss, player impact,…

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IPL Crunch '26: What Actually Wins Matches — A Ball-by-Ball Intelligence Report

Proved toss is a coin flip (p=1.000) and death-over efficiency (+2.04 RPO) predicts the winner in all 17 of 17 IPL seasons

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IPL Crunch Analytics Dashboard

Built a high-performance analytics application that processes ball-by-ball IPL records to provide actionable strategic data for franch…

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IPL InsightX – AI-Powered Cricket Analytics Studio

Analyzed IPL ball-by-ball datasets and built an AI-powered analytics platform with 9+ interactive visualizations, real-time filtering,…

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IPL Crunch: Toss, Phase & Players Decoded from 278K Deliveries

Analyzed 278,034 deliveries across 18 seasons to prove the toss is a coin flip and the middle overs win games — validated on two datas…

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🏏 IPL CRUNCH : Where Data Turns Into Game

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IPL CRUNCH '26: Decoding 289K Deliveries with Advanced Analytics & Machine Learning

289K deliveries → 13 analytics modules, 30+ charts, 7 hidden patterns, 1 ML win-probability model.

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IPL Data Analysis 2015–2019: Python, Pandas & 70K+ Ball-by-Ball Records

5 seasons. 70,208 balls. One finding — the toss barely matters, the middle overs do.

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Data-Driven Insights from IPL Matches

Performed end-to-end IPL analytics using Python, uncovering strategic insights through EDA, statistical analysis, and advanced visuali…

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IPL Crunch '26 - What Actually Wins IPL Matches?

Analyzed whole data of IPL ball-by-ball to reveal that toss decision, death over runs and powerplay wickets decide match outcomes - no…

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The Toss Myth: A 289K Ball-by-Ball Analysis of IPL Match Winners

Debunked the toss myth at 50.5% win rate, identified Death overs as 7.3× more decisive than Middle overs, and exposed death-over bowli…

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Cracking the Data - What Actually Wins in IPL

The data dismantles the "finisher wins matches" narrative — openers and powerplay bowlers are the real difference makers.

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Ipl crunch-26

the outcomes are the analysis of the ipl teams and there prediction of winning game

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IPL Crunch '26: Backing Cricket Opinions With Numbers

298k+ ball by ball rows analysed

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IPL Cricket Analysis : Toss Impact, Phase Performance & Top Players

Toss provides No Advantage (50.49% vs 49.51%), Middle Overs Critical (+7.84 runs gap), Top Players Virat Kohli (9,050 runs) Yuzvendra…

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IPL Crunch '26 — What Actually Wins IPL Matches: 19 Seasons, 1,218 Matches, Data-Backed

Analyzed 289,673 IPL deliveries to prove chasing teams win 55.6% of matches — and the toss is essentially useles

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IPL Crunch '26: Quantifying Match Pressure & The Dubai Trap

Processed 290,000+ deliveries via a custom Python pipeline to expose a massive strategic flaw in IPL chasing meta.

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IPL Crunch '26: End-to-End Sports Telemetry Pipeline & Match-Winning Insights Engine

Processed 293,764 nested JSON ball-telemetry data points via a custom Python pipeline to automate multi-sheet executive dashboards rev…

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IPL Crunch '26 — Toss, Phases & Player Analysis

Analyzed 289,673 IPL deliveries to prove the toss is a coin flip — but fielding after winning it gives a 53.7% win rate.

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IPL Crunch '26: Advanced Contextual Analytics Console

Engineered an IPL analytics console over 289K data rows, establishing key 7.8-run phase-scoring gaps and isolating elite strike rate o…

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IPL Match Intelligence Dashboard | IPL Crunch ’26 Hackathon

Analyzed 5 IPL seasons using Python & Power BI to uncover how death-over execution and bowling pressure influence match victories more…

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IPL Match Analysis Using Python

Discovered that death-over performance impacts IPL match results more than toss advantage or chasing trends.

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IPL Data Analysis — Wooble IPL Crunch '26

Analyzed 179,078 IPL deliveries across 13 seasons to uncover 6 data-backed cricket insights

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IPL Crunch '26 — Ball-by-Ball Analysis of 1,226 Matches (2008–2026)

Analysed 240,000+ deliveries across 19 IPL seasons; uncovered home advantage decay of 5.9% and mapped 1,000+ bowler-batter matchup dom…