From fa61e4977983b2177738f699bc8f16d6cb5c85e1 Mon Sep 17 00:00:00 2001 From: bender Date: Sat, 21 Mar 2026 05:54:20 +0000 Subject: [PATCH 1/4] Update src/app/contact/page.tsx --- src/app/contact/page.tsx | 56 ++++++++++++---------------------------- 1 file changed, 16 insertions(+), 40 deletions(-) diff --git a/src/app/contact/page.tsx b/src/app/contact/page.tsx index 4a1b2d7..f628fb9 100644 --- a/src/app/contact/page.tsx +++ b/src/app/contact/page.tsx @@ -30,19 +30,13 @@ export default function ContactPage() { const socialLinks = [ { icon: Twitter, - href: "https://twitter.com", - ariaLabel: "Follow us on Twitter", - }, + href: "https://twitter.com", ariaLabel: "Follow us on Twitter"}, { icon: Linkedin, - href: "https://linkedin.com", - ariaLabel: "Connect on LinkedIn", - }, + href: "https://linkedin.com", ariaLabel: "Connect on LinkedIn"}, { icon: Github, - href: "https://github.com", - ariaLabel: "View our code on GitHub", - }, + href: "https://github.com", ariaLabel: "View our code on GitHub"}, ]; return ( @@ -74,45 +68,27 @@ export default function ContactPage() { textboxLayout="default" useInvertedBackground={true} tag="Support" - tagIcon="HelpCircle" + tagIcon={HelpCircle} tagAnimation="slide-up" faqs={[ { - id: "faq-1", - title: "What data does CricIntel analyze?", - content: - "CricIntel analyzes comprehensive ball-by-ball data from all major T20 leagues including IPL, BBL, SA20, CPL, T20 Blast, and domestic competitions worldwide. Our data comes from Cricsheet, covering thousands of matches with detailed context for every ball delivered.", - }, + id: "faq-1", title: "What data does CricIntel analyze?", content: + "CricIntel analyzes comprehensive ball-by-ball data from all major T20 leagues including IPL, BBL, SA20, CPL, T20 Blast, and domestic competitions worldwide. Our data comes from Cricsheet, covering thousands of matches with detailed context for every ball delivered."}, { - id: "faq-2", - title: "How accurate are CricIntel's predictions?", - content: - "CricIntel's XGBoost ensemble models achieve 99.2% accuracy in win probability predictions and performance forecasting. Every prediction is backed by SHAP explainability, meaning you understand the reasoning behind each insight—not just the numbers.", - }, + id: "faq-2", title: "How accurate are CricIntel's predictions?", content: + "CricIntel's XGBoost ensemble models achieve 99.2% accuracy in win probability predictions and performance forecasting. Every prediction is backed by SHAP explainability, meaning you understand the reasoning behind each insight—not just the numbers."}, { - id: "faq-3", - title: "Can CricIntel help with player discovery?", - content: - "Absolutely. Our Player Intelligence module uses unsupervised clustering and context-aware performance scoring to identify undervalued players, find similar profiles globally, and model career trajectories. Scouts can discover hidden gems across all major leagues in minutes.", - }, + id: "faq-3", title: "Can CricIntel help with player discovery?", content: + "Absolutely. Our Player Intelligence module uses unsupervised clustering and context-aware performance scoring to identify undervalued players, find similar profiles globally, and model career trajectories. Scouts can discover hidden gems across all major leagues in minutes."}, { - id: "faq-4", - title: "How does real-time match analysis work?", - content: - "Our Match Intelligence system processes ball-by-ball data in real-time to update win probability models, analyze pressure situations, and break down matchups by phase (powerplay, middle, death). Results are available instantly for commentary, strategy, and live decision-making.", - }, + id: "faq-4", title: "How does real-time match analysis work?", content: + "Our Match Intelligence system processes ball-by-ball data in real-time to update win probability models, analyze pressure situations, and break down matchups by phase (powerplay, middle, death). Results are available instantly for commentary, strategy, and live decision-making."}, { - id: "faq-5", - title: "What makes CricIntel different?", - content: - "CricIntel combines three unique advantages: deep cricket domain knowledge baked into feature engineering, production-grade ML models with SHAP explainability, and an interactive dashboard that transforms insights into actionable strategy. We're not just numbers—we're intelligence.", - }, + id: "faq-5", title: "What makes CricIntel different?", content: + "CricIntel combines three unique advantages: deep cricket domain knowledge baked into feature engineering, production-grade ML models with SHAP explainability, and an interactive dashboard that transforms insights into actionable strategy. We're not just numbers—we're intelligence."}, { - id: "faq-6", - title: "Who uses CricIntel?", - content: - "CricIntel is designed for franchises (strategy and scouting), analysts (match preparation and commentary), scouts (talent discovery), coaches (tactical planning), and cricket media (data-driven storytelling). Anyone making cricket decisions benefits from CricIntel insights.", - }, + id: "faq-6", title: "Who uses CricIntel?", content: + "CricIntel is designed for franchises (strategy and scouting), analysts (match preparation and commentary), scouts (talent discovery), coaches (tactical planning), and cricket media (data-driven storytelling). Anyone making cricket decisions benefits from CricIntel insights."}, ]} faqsAnimation="slide-up" ariaLabel="CricIntel FAQ section" -- 2.49.1 From 31233119918024f4a4aa613015cad1c260643431 Mon Sep 17 00:00:00 2001 From: bender Date: Sat, 21 Mar 2026 05:54:20 +0000 Subject: [PATCH 2/4] Update src/app/page.tsx --- src/app/page.tsx | 142 ++++++++++++++--------------------------------- 1 file changed, 41 insertions(+), 101 deletions(-) diff --git a/src/app/page.tsx b/src/app/page.tsx index 09bda66..519dd3d 100644 --- a/src/app/page.tsx +++ b/src/app/page.tsx @@ -10,7 +10,7 @@ import TestimonialCardTwelve from '@/components/sections/testimonial/Testimonial import FaqBase from '@/components/sections/faq/FaqBase'; import FooterCard from '@/components/sections/footer/FooterCard'; import Link from 'next/link'; -import { Sparkles, Brain, Zap, Code, BarChart3, Users, HelpCircle, ThumbsUp, Twitter, Linkedin, Github } from 'lucide-react'; +import { Sparkles, Brain, Zap, Code, BarChart3, Users, HelpCircle, ThumbsUp, Twitter, Linkedin, Github, User, TrendingUp, ClipboardList, Target, DollarSign, Database, Globe, Activity, Trophy, Layers, GitBranch, Cpu } from 'lucide-react'; export default function HomePage() { const navItems = [ @@ -60,10 +60,10 @@ export default function HomePage() { imageAlt="CricIntel Analytics Dashboard" mediaAnimation="slide-up" marqueeItems={[ - { text: "1000+ Matches Analyzed" }, - { text: "Real-time Predictions" }, - { text: "Global Coverage" }, - { text: "AI-Powered Insights" } + { type: "text-icon", text: "1000+ Matches Analyzed", icon: BarChart3 }, + { type: "text-icon", text: "Real-time Predictions", icon: Zap }, + { type: "text-icon", text: "Global Coverage", icon: Globe }, + { type: "text-icon", text: "AI-Powered Insights", icon: Brain } ]} marqueeSpeed={30} showMarqueeCard={true} @@ -107,28 +107,20 @@ export default function HomePage() { tagAnimation="slide-up" features={[ { - title: "Player Intelligence", - description: "Context-aware performance scoring, career trajectory modeling, and style-based player clustering to identify undervalued talent and similar profiles globally.", - bentoComponent: "icon-info-cards", - items: [ - { icon: "User", label: "Performance Scores", value: "Context-Aware" }, - { icon: "TrendingUp", label: "Career Paths", value: "Predicted" }, - { icon: "Users", label: "Player Clusters", value: "By Style" } + title: "Player Intelligence", description: "Context-aware performance scoring, career trajectory modeling, and style-based player clustering to identify undervalued talent and similar profiles globally.", bentoComponent: "icon-info-cards", items: [ + { icon: User, label: "Performance Scores", value: "Context-Aware" }, + { icon: TrendingUp, label: "Career Paths", value: "Predicted" }, + { icon: Users, label: "Player Clusters", value: "By Style" } ] }, { - title: "Match Intelligence", - description: "Real-time win probability modeling, pressure situation analysis, and detailed phase-wise breakdown of bowling and batting matchups with contextual insights.", - bentoComponent: "animated-bar-chart" + title: "Match Intelligence", description: "Real-time win probability modeling, pressure situation analysis, and detailed phase-wise breakdown of bowling and batting matchups with contextual insights.", bentoComponent: "animated-bar-chart" }, { - title: "Team Strategy", - description: "Optimal batting order construction, best XI selection against specific oppositions, and IPL auction value estimation powered by machine learning.", - bentoComponent: "3d-stack-cards", - items: [ - { icon: "ClipboardList", title: "Batting Order", subtitle: "Optimization", detail: "Data-driven lineup construction" }, - { icon: "Target", title: "Best XI", subtitle: "Selection", detail: "Opposition-specific analysis" }, - { icon: "DollarSign", title: "Auction Value", subtitle: "Estimation", detail: "IPL pricing intelligence" } + title: "Team Strategy", description: "Optimal batting order construction, best XI selection against specific oppositions, and IPL auction value estimation powered by machine learning.", bentoComponent: "3d-stack-cards", items: [ + { icon: ClipboardList, title: "Batting Order", subtitle: "Optimization", detail: "Data-driven lineup construction" }, + { icon: Target, title: "Best XI", subtitle: "Selection", detail: "Opposition-specific analysis" }, + { icon: DollarSign, title: "Auction Value", subtitle: "Estimation", detail: "IPL pricing intelligence" } ] } ]} @@ -150,40 +142,27 @@ export default function HomePage() { tagAnimation="slide-up" features={[ { - title: "Cricsheet Data Foundation", - description: "Comprehensive ball-by-ball data covering thousands of T20 matches across IPL, BBL, SA20, CPL, T20 Blast, and domestic competitions worldwide.", - bentoComponent: "orbiting-icons", - centerIcon: "Database", + title: "Cricsheet Data Foundation", description: "Comprehensive ball-by-ball data covering thousands of T20 matches across IPL, BBL, SA20, CPL, T20 Blast, and domestic competitions worldwide.", bentoComponent: "orbiting-icons", centerIcon: Database, items: [ - { icon: "Globe", ring: 1 }, - { icon: "Activity", ring: 1 }, - { icon: "BarChart3", ring: 2 }, - { icon: "Zap", ring: 2 }, - { icon: "Target", ring: 3 }, - { icon: "Trophy", ring: 3 } + { icon: Globe, ring: 1 }, + { icon: Activity, ring: 1 }, + { icon: BarChart3, ring: 2 }, + { icon: Zap, ring: 2 }, + { icon: Target, ring: 3 }, + { icon: Trophy, ring: 3 } ] }, { - title: "Feature Pipeline", - description: "Deep cricket domain knowledge transforms raw ball-by-ball data into meaningful features capturing context, phase dynamics, and player interactions.", - bentoComponent: "3d-task-list", - items: [ - { icon: "Layers", label: "Context Extraction", time: "Real-time" }, - { icon: "GitBranch", label: "Phase Analysis", time: "Streaming" }, - { icon: "Cpu", label: "Aggregation", time: "Batch" } + title: "Feature Pipeline", description: "Deep cricket domain knowledge transforms raw ball-by-ball data into meaningful features capturing context, phase dynamics, and player interactions.", bentoComponent: "3d-task-list", items: [ + { icon: Layers, label: "Context Extraction", time: "Real-time" }, + { icon: GitBranch, label: "Phase Analysis", time: "Streaming" }, + { icon: Cpu, label: "Aggregation", time: "Batch" } ] }, { - title: "ML & Explainability", - description: "XGBoost ensemble models for prediction accuracy combined with SHAP for model explainability—every insight includes reasoning, not just numbers.", - bentoComponent: "marquee", - centerIcon: "Brain", - variant: "text", - texts: [ - "XGBoost Ensembles", - "SHAP Explainability", - "Real-time Inference", - "Continuous Learning" + title: "ML & Explainability", description: "XGBoost ensemble models for prediction accuracy combined with SHAP for model explainability—every insight includes reasoning, not just numbers.", bentoComponent: "marquee", centerIcon: Brain, + variant: "text", texts: [ + "XGBoost Ensembles", "SHAP Explainability", "Real-time Inference", "Continuous Learning" ] } ]} @@ -205,28 +184,13 @@ export default function HomePage() { tagAnimation="slide-up" metrics={[ { - id: "matches", - value: "1000+", - title: "T20 Matches Analyzed", - description: "Comprehensive historical and ongoing match data", - imageSrc: "https://webuild-dev.s3.eu-north-1.amazonaws.com/users/user_3BF4j2bxRdT4nJ0q7EnEjwa2Qxd/a-beautifully-designed-stat-card-showing-1774072042418-e0be0ae8.png", - imageAlt: "Matches analyzed stat" + id: "matches", value: "1000+", title: "T20 Matches Analyzed", description: "Comprehensive historical and ongoing match data", imageSrc: "https://webuild-dev.s3.eu-north-1.amazonaws.com/users/user_3BF4j2bxRdT4nJ0q7EnEjwa2Qxd/a-beautifully-designed-stat-card-showing-1774072042418-e0be0ae8.png", imageAlt: "Matches analyzed stat" }, { - id: "coverage", - value: "6 Leagues", - title: "Global T20 Coverage", - description: "IPL, BBL, SA20, CPL, T20 Blast & Domestic", - imageSrc: "https://webuild-dev.s3.eu-north-1.amazonaws.com/users/user_3BF4j2bxRdT4nJ0q7EnEjwa2Qxd/a-dynamic-visualization-showing-global-t-1774072043067-c6f48e9a.png", - imageAlt: "Global league coverage" + id: "coverage", value: "6 Leagues", title: "Global T20 Coverage", description: "IPL, BBL, SA20, CPL, T20 Blast & Domestic", imageSrc: "https://webuild-dev.s3.eu-north-1.amazonaws.com/users/user_3BF4j2bxRdT4nJ0q7EnEjwa2Qxd/a-dynamic-visualization-showing-global-t-1774072043067-c6f48e9a.png", imageAlt: "Global league coverage" }, { - id: "accuracy", - value: "99.2%", - title: "Model Accuracy", - description: "XGBoost ensemble predictions with SHAP validation", - imageSrc: "https://webuild-dev.s3.eu-north-1.amazonaws.com/users/user_3BF4j2bxRdT4nJ0q7EnEjwa2Qxd/a-machine-learning-model-visualization-s-1774072043382-7869ef54.png", - imageAlt: "Model accuracy rate" + id: "accuracy", value: "99.2%", title: "Model Accuracy", description: "XGBoost ensemble predictions with SHAP validation", imageSrc: "https://webuild-dev.s3.eu-north-1.amazonaws.com/users/user_3BF4j2bxRdT4nJ0q7EnEjwa2Qxd/a-machine-learning-model-visualization-s-1774072043382-7869ef54.png", imageAlt: "Model accuracy rate" } ]} ariaLabel="CricIntel metrics section" @@ -238,28 +202,16 @@ export default function HomePage() {