AP Poll Trend \u2013 Prefilled (Studio1Live)<\/title>\n <style>\n body{font-family:system-ui,-apple-system,Segoe UI,Roboto,Ubuntu,Cantarell,\"Helvetica Neue\",Arial,\"Noto Sans\",sans-serif;margin:0;padding:24px;background:#0b0c10;color:#e6edf3}\n h1,h2{margin:0 0 8px}\n h1{font-size:24px}\n h2{font-size:18px;color:#9fb3c8}\n .card{background:#11151a;border:1px solid #22303c;border-radius:16px;padding:16px;margin-bottom:16px;box-shadow:0 1px 2px rgba(0,0,0,.2)}\n .row{display:grid;grid-template-columns:1fr;gap:16px}\n @media(min-width:1000px){.row{grid-template-columns:2fr 1fr}}\n label{display:block;margin:8px 0 6px;color:#9fb3c8;font-size:13px}\n textarea{width:100%;height:220px;border-radius:10px;border:1px solid #2b3b4a;background:#0e1217;color:#e6edf3;padding:10px;font-family:ui-monospace,Menlo,Consolas,monospace}\n button,input[type=file]{background:#1f6feb;border:0;color:white;padding:10px 14px;border-radius:10px;cursor:pointer}\n button.secondary{background:#30363d}\n .note{font-size:12px;color:#9fb3c8}\n table{width:100%;border-collapse:collapse;font-size:14px}\n th,td{padding:8px 10px;border-bottom:1px solid #22303c;text-align:center}\n thead th{position:sticky;top:0;background:#0f141a;z-index:1}\n .badge{display:inline-block;padding:2px 8px;border-radius:999px;font-size:12px}\n .up{background:#0a7f3f33;color:#6ee7b7}\n .down{background:#7f0a0a33;color:#fca5a5}\n .flat{background:#4b556333;color:#cbd5e1}\n .legend{display:flex;flex-wrap:wrap;gap:10px;margin:8px 0 0}\n .pill{display:inline-flex;align-items:center;gap:8px;padding:6px 10px;border:1px solid #22303c;border-radius:999px;background:#0e1217}\n .swatch{inline-size:12px;block-size:12px;border-radius:3px;display:inline-block}\n .footer{font-size:12px;color:#94a3b8;margin-top:6px}\n .muted{color:#94a3b8}\n <\/style>\n\n\n<div class=\"container\" style=\"max-width:1200px;margin:0 auto\">\n <h1>AP Top 25 \u2013 Week-by-Week Trend (Preseason \u2192 Week 10)<\/h1>\n <p class=\"muted\">Prefilled from your ESPN screenshots (AP poll, left column) where clearly legible. Weeks with uncertainty are left blank (NR). You can fine-tune in the JSON editor and press <em>Update Chart<\/em>.<\/p>\n\n <div class=\"card\">\n <canvas id=\"rankChart\" height=\"120\"><\/canvas>\n <div class=\"legend\" id=\"legend\"><\/div>\n <div class=\"footer\">Hover the lines to see rank each week. Y-axis is Rank (1 at top).<\/div>\n <\/div>\n\n <div class=\"row\">\n <div class=\"card\">\n <h2>Data Table<\/h2>\n <div style=\"overflow:auto; max-height:420px\">\n <table id=\"rankTable\">\n <thead id=\"thead\"><\/thead>\n <tbody id=\"tbody\"><\/tbody>\n <\/table>\n <\/div>\n <\/div>\n\n <div class=\"card\">\n <h2>Edit \/ Import<\/h2>\n <label for=\"json\">JSON Editor<\/label>\n <textarea id=\"json\"><\/textarea>\n <div style=\"display:flex;gap:8px;margin-top:8px\">\n <button id=\"updateBtn\">Update Chart<\/button>\n <button class=\"secondary\" id=\"resetBtn\">Reset<\/button>\n <\/div>\n <p class=\"note\" style=\"margin-top:10px\">CSV supported too (<code>Week,Miami,Alabama,Texas,Notre Dame,Oregon,Georgia<\/code>)<\/p>\n <input type=\"file\" id=\"csv\" accept=\".csv\">\n <\/div>\n <\/div>\n\n <div class=\"card\">\n <h2>Blog Summary<\/h2>\n <p>\n From preseason to Week 10, Miami\u2019s path shows a sharper correction after a single loss compared with Alabama and\n other marquee brands. Several weeks later, Alabama holds a top-5 spot despite comparable setbacks while Miami slid\n from a near-consensus top-three to the back end of the top-10 and even #11, including a paradoxical dip after a win.\n This pattern trims Miami\u2019s margin for error versus programs buoyed by brand inertia and television familiarity.\n <\/p>\n <\/div>\n<\/div>\n\n<script src=\"https:\/\/cdn.jsdelivr.net\/npm\/chart.js@4.4.4\/dist\/chart.umd.min.js\"><\/script>\n<script>\nconst COLORS = [\"#22c55e\",\"#ef4444\",\"#f97316\",\"#eab308\",\"#10b981\",\"#60a5fa\"];\n\nconst DATA = {\n weeks: [\"Preseason\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\"],\n teams: [\"Miami\",\"Alabama\",\"Texas\",\"Notre Dame\",\"Oregon\",\"Georgia\"],\n ranks: {\n \/\/ Preseason from your image\n \"Miami\": [10, 5, 5, 2, 3, 2, 2, 9,11, 9,11],\n \"Alabama\": [ 8, null, null, 6,10, 8, 6, 4, 4, 4, 4],\n \"Texas\": [ 1, 7, 7, 7, 9, null, null, null, null, null, null],\n \"Notre Dame\": [ 6, 9, 8,11, null,16,13,12,12,12,12],\n \"Oregon\": [ 7, 6, 8, 8, 2, 3, 8, 6, 6, 6, 6],\n \"Georgia\": [ 5, 4, 6, 6,12,10, 9, 5, 5, 5, 5]\n }\n};\n\n\/\/ Helpers\nfunction trendBadge(curr, prev){\n if (curr == null || prev == null) return '<span class=\"badge flat\">\u2013';\n const delta = prev - curr;\n if (delta > 0) return `<span class=\"badge up\">\u2191 ${Math.abs(delta)}`;\n if (delta < 0) return `<span class=\"badge down\">\u2193 ${Math.abs(delta)}`;\n return `<span class=\"badge flat\">\u00b7`;\n}\n\nfunction renderTable(state){\n const thead = document.getElementById('thead');\n const tbody = document.getElementById('tbody');\n thead.innerHTML = `<tr><th>Week${state.teams.map(t=>`<th>${t}`).join('')}`;\n const rows = [];\n for (let i=0;i<state.weeks.length;i++){\n const week = state.weeks[i];\n const cells = [`<td><strong>${week}`];\n for (const t of state.teams){\n const v = state.ranks[t][i];\n const prev = i>0 ? 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Since 1936, this poll has served as a barometer of perceived strength, prestige and momentum across the […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-461","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/posts\/461","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/comments?post=461"}],"version-history":[{"count":3,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/posts\/461\/revisions"}],"predecessor-version":[{"id":464,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/posts\/461\/revisions\/464"}],"wp:attachment":[{"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/media?parent=461"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/categories?post=461"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/tags?post=461"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

{"id":461,"date":"2025-10-27T16:54:01","date_gmt":"2025-10-27T16:54:01","guid":{"rendered":"https:\/\/studio1live.com\/picks\/?p=461"},"modified":"2025-10-27T21:03:07","modified_gmt":"2025-10-27T21:03:07","slug":"ap-poll-fake-rankings","status":"publish","type":"post","link":"https:\/\/studio1live.com\/picks\/ap-poll-fake-rankings\/","title":{"rendered":"AP POLL FAKE RANKINGS"},"content":{"rendered":"\n

\u201cGrace & Brand: How the AP Poll Looks Like It Plays Favorites in College Football\u201d<\/strong>
By [Demetrius A Thompson], Special to the Journal<\/em><\/p>\n\n\n\n

At the heart of every college-football season lies the weekly ritual of the AP Top 25. Since 1936, this poll has served as a barometer of perceived strength, prestige and momentum across the FBS landscape. CollegeVine+3ESPN.com+3SI+3<\/a> Each week, sports writers and broadcasters across the country submit their ballots ranking the top 25 teams; a first-place vote carries 25 points, second place 24 points, and so-on to 1 point for 25th place. SI+1<\/a><\/p>\n\n\n\n

Yet, for as transparent as the process may appear, the poll repeatedly gives the appearance of grace<\/strong> being extended to certain programs\u2014losing \u201cbetter,\u201d winning \u201cbetter,\u201d and benefitting from brand value, historical prestige and television-narrative momentum. The clips you referenced\u2014of the final play in the South Carolina Gamecocks vs. Alabama game, a TikTok share of a seemingly deliberate let-up\u2014serve as an emblem of the broader suspicion: that not all wins and losses are treated equally.<\/p>\n\n\n\n

What the Poll Says \u2013 and Doesn\u2019t<\/h3>\n\n\n\nThe AP Poll is not a mechanism for playoff qualification. It is a consensus opinion<\/strong> of selected media, and though influential, it does not directly determine postseason match-ups<\/strong>. Sports Betting Dime+1<\/a> That means there is room for narrative, legacy and brand to skew perceptions.<\/p>\n\n\n\n
When media-voted polls weigh in, semantics matter. A \u201cgood loss\u201d often gets framed differently than a \u201cbad loss.\u201d A traditional powerhouse dropping a game may still linger in or near the top 10, while a mid-tier program doing the same can vanish entirely. These distinctions aren\u2019t just anecdotal\u2014they shape public perception, recruiting momentum, and television exposure.<\/p>\n\n\n\n
The Case Study: Alabama vs. Miami vs. Virginia<\/h3>\n\n\n\n
Here\u2019s the scenario you laid out:<\/p>\n\n\n\n
\n
Notre Dame incurs two losses, yet remains high in the rankings and seems to receive the benefit of the doubt regarding the nature of those losses.<\/li>\n\n\n\n
Miami and Virginia (each with one loss, including wins over teams Alabama lost to) appear to be treated less generously.<\/li>\n\n\n\n
The suggestion: there is pre-ranking, or brand-based bias, toward Alabama (a storied program) and comparatively less for the others.<\/li>\n<\/ul>\n\n\n\n
1. Brand & historical prestige<\/strong>
Alabama is among the most decorated programs in college football history, with frequent top rankings in the AP Poll and multiple championships. Wikipedia<\/a> That kind of brand creates a \u201chalo\u201d effect: voters may unconsciously give more benefit of the doubt when a loss occurs\u2014\u201cit was a quality loss\u201d or \u201cthe program still deserves ranking.\u201d
Conversely, a program without that same recent dominance may be penalized more harshly for the same kind of loss.<\/p>\n\n\n\n
2. Differential value of losses and wins<\/strong>
Let\u2019s parse the logic:<\/p>\n\n\n\n
\n
Miami beats a team (say, South Carolina?) that Alabama lost to.<\/li>\n\n\n\n
Virginia also beats a team Alabama lost to.<\/li>\n\n\n\n
Yet Miami drops to #10 (despite one loss) while Alabama remains higher (despite two losses).<\/li>\n\n\n\n
The final play clip implies a narrative that Alabama\u2019s loss might have been \u201callowed\u201d or mitigated, rather than punished.<\/li>\n<\/ul>\n\n\n\n
What this suggests is a two-tier system:<\/p>\n\n\n\n
\n
Tier 1 programs: when they lose, the loss is treated as one of \u201cearned\u201d respect (a \u201cgood\u201d loss). When they win, the win is treated as a testament to their continued dominance.<\/li>\n\n\n\n
Tier 2 programs: when they lose, the loss carries heavy weight; when they win, the win may be qualified or discounted (e.g., \u201cthey beat a beatable opponent,\u201d or \u201cwe don\u2019t yet know how great they are\u201d).<\/li>\n<\/ul>\n\n\n\n
This narrative interpretation aligns with commentary that the poll has \u201cfaulty logic and embeds brand bias.\u201d Lawless Republic+1<\/a><\/p>\n\n\n\n
3. The television\/brand effect<\/strong>
You mentioned \u201cthey talk about a brand on CBS and they play a role in who they selected.\u201d Indeed, television coverage, marquee programs and \u201cmust-see\u201d matchups shape brand narratives. A team that regularly features on national television gets more media exposure\u2014and by extension, more familiarity among voters.
When voters fill ballots weekly, familiarity often equates to perceived credibility.<\/p>\n\n\n\n
Supporting Data<\/h3>\n\n\n\n\n
The AP Poll\u2019s point system: first-place vote = 25 pts, second = 24, etc. ESPN.com+1<\/a><\/li>\n\n\n\n
The AP Poll\u2019s voter base: roughly 60+ sportswriters\/broadcasters covering FBS football; they are selected by the AP to represent various regions. AP News<\/a><\/li>\n\n\n\n
The poll is extremely volatile week to week, especially early in the season, because narratives and limited data dominate. Sports Stack Exchange<\/a><\/li>\n\n\n\n
Media analysts argue the AP Poll is \u201cbroken\u201d in its treatment of losses and wins for elite programs vs. others. Lawless Republic<\/a><\/li>\n<\/ul>\n\n\n\n
Argument Summary<\/h3>\n\n\n\n
\n
Pre-ranking and Brand Advantage<\/strong> \u2014 Teams like Alabama enter the season with built-in credibility; voters anticipate their success and are predisposed to keep them high unless dropped decisively.<\/li>\n\n\n\n
Unequal Treatment of Losses\/Wins<\/strong> \u2014 When a brand program loses, the narrative often frames that loss as \u201cbetter\u201d (e.g., \u201cthey beat a good team,\u201d \u201cit was a one-possession game\u201d) while less-established programs receive harsher treatment.<\/li>\n\n\n\n
Narrative and Media Exposure<\/strong> \u2014 Weekly exposure (TV, social media, highlight plays) shapes voters\u2019 recall and bias. A memorable clip (like the one you referenced) may feed the perception of \u201cspecial treatment.\u201d<\/li>\n\n\n\n
Transparency vs. Subjectivity<\/strong> \u2014 Although the process is transparent in terms of mechanics, the subjectivity is real: \u201cgood\u201d and \u201cbad\u201d losses, strength of schedule, brand value\u2014all are judged by human voters.<\/li>\n\n\n\n
Implications<\/strong> \u2014 For programs like Miami or Virginia, the consequence is that even with one loss and some quality wins, they may still drop because the brand ceiling is lower. Meanwhile for Alabama, two losses might be \u201cok\u201d because the brand floor is high.<\/li>\n<\/ol>\n\n\n\n
What Needs to Change<\/h3>\n\n\n\n
If the poll is truly to reflect performance rather than prestige, a few steps could help:<\/p>\n\n\n\n
\n
Greater accountability for voters<\/strong>: Encourage explicit justification of unusual jumps or falls\u2014why did a team go up\/down despite similar records?<\/li>\n\n\n\n
Stronger weight on objective metrics<\/strong>: strength of schedule, wins over quality opponents, losses to quality opponents\u2014all could be made more transparent.<\/li>\n\n\n\n
Reduce brand inertia<\/strong>: Acknowledging that historical success should not shield a program from steep drops after poor performance.<\/li>\n\n\n\n
Media literacy for voters<\/strong>: Recognize that highlight plays, brand narratives and viral clips (TikTok, social media) may unduly influence voting.<\/li>\n<\/ul>\n\n\n\n
Conclusion<\/h3>\n\n\n\n
Your observation\u2014that Alabama gets a grace pass and programs like Miami and Virginia do not\u2014is rooted in real dynamics of college football perception, media exposure and voting behavior. The AP Poll remains one of the most widely cited gauges of national standing. But the treatment of teams with similar records yet different brands reveals how much narrative matters.<\/p>\n\n\n\n# Create a second version of the HTML with the user\u2019s screenshot-derived ranks prefilled \n# where they were clearly legible (AP left column), and leave early unclear weeks as nulls.\n# Weeks covered: Preseason \u2192 Week 10.\n\nprefilled_html = r\u201d\u201d\u201d\n\n\n\n \n \n AP Poll Trend \u2013 Prefilled (Studio1Live)<\/title>\n <style>\n body{font-family:system-ui,-apple-system,Segoe UI,Roboto,Ubuntu,Cantarell,\"Helvetica Neue\",Arial,\"Noto Sans\",sans-serif;margin:0;padding:24px;background:#0b0c10;color:#e6edf3}\n h1,h2{margin:0 0 8px}\n h1{font-size:24px}\n h2{font-size:18px;color:#9fb3c8}\n .card{background:#11151a;border:1px solid #22303c;border-radius:16px;padding:16px;margin-bottom:16px;box-shadow:0 1px 2px rgba(0,0,0,.2)}\n .row{display:grid;grid-template-columns:1fr;gap:16px}\n @media(min-width:1000px){.row{grid-template-columns:2fr 1fr}}\n label{display:block;margin:8px 0 6px;color:#9fb3c8;font-size:13px}\n textarea{width:100%;height:220px;border-radius:10px;border:1px solid #2b3b4a;background:#0e1217;color:#e6edf3;padding:10px;font-family:ui-monospace,Menlo,Consolas,monospace}\n button,input[type=file]{background:#1f6feb;border:0;color:white;padding:10px 14px;border-radius:10px;cursor:pointer}\n button.secondary{background:#30363d}\n .note{font-size:12px;color:#9fb3c8}\n table{width:100%;border-collapse:collapse;font-size:14px}\n th,td{padding:8px 10px;border-bottom:1px solid #22303c;text-align:center}\n thead th{position:sticky;top:0;background:#0f141a;z-index:1}\n .badge{display:inline-block;padding:2px 8px;border-radius:999px;font-size:12px}\n .up{background:#0a7f3f33;color:#6ee7b7}\n .down{background:#7f0a0a33;color:#fca5a5}\n .flat{background:#4b556333;color:#cbd5e1}\n .legend{display:flex;flex-wrap:wrap;gap:10px;margin:8px 0 0}\n .pill{display:inline-flex;align-items:center;gap:8px;padding:6px 10px;border:1px solid #22303c;border-radius:999px;background:#0e1217}\n .swatch{inline-size:12px;block-size:12px;border-radius:3px;display:inline-block}\n .footer{font-size:12px;color:#94a3b8;margin-top:6px}\n .muted{color:#94a3b8}\n <\/style>\n\n\n<div class=\"container\" style=\"max-width:1200px;margin:0 auto\">\n <h1>AP Top 25 \u2013 Week-by-Week Trend (Preseason \u2192 Week 10)<\/h1>\n <p class=\"muted\">Prefilled from your ESPN screenshots (AP poll, left column) where clearly legible. Weeks with uncertainty are left blank (NR). You can fine-tune in the JSON editor and press <em>Update Chart<\/em>.<\/p>\n\n <div class=\"card\">\n <canvas id=\"rankChart\" height=\"120\"><\/canvas>\n <div class=\"legend\" id=\"legend\"><\/div>\n <div class=\"footer\">Hover the lines to see rank each week. Y-axis is Rank (1 at top).<\/div>\n <\/div>\n\n <div class=\"row\">\n <div class=\"card\">\n <h2>Data Table<\/h2>\n <div style=\"overflow:auto; max-height:420px\">\n <table id=\"rankTable\">\n <thead id=\"thead\"><\/thead>\n <tbody id=\"tbody\"><\/tbody>\n <\/table>\n <\/div>\n <\/div>\n\n <div class=\"card\">\n <h2>Edit \/ Import<\/h2>\n <label for=\"json\">JSON Editor<\/label>\n <textarea id=\"json\"><\/textarea>\n <div style=\"display:flex;gap:8px;margin-top:8px\">\n <button id=\"updateBtn\">Update Chart<\/button>\n <button class=\"secondary\" id=\"resetBtn\">Reset<\/button>\n <\/div>\n <p class=\"note\" style=\"margin-top:10px\">CSV supported too (<code>Week,Miami,Alabama,Texas,Notre Dame,Oregon,Georgia<\/code>)<\/p>\n <input type=\"file\" id=\"csv\" accept=\".csv\">\n <\/div>\n <\/div>\n\n <div class=\"card\">\n <h2>Blog Summary<\/h2>\n <p>\n From preseason to Week 10, Miami\u2019s path shows a sharper correction after a single loss compared with Alabama and\n other marquee brands. Several weeks later, Alabama holds a top-5 spot despite comparable setbacks while Miami slid\n from a near-consensus top-three to the back end of the top-10 and even #11, including a paradoxical dip after a win.\n This pattern trims Miami\u2019s margin for error versus programs buoyed by brand inertia and television familiarity.\n <\/p>\n <\/div>\n<\/div>\n\n<script src=\"https:\/\/cdn.jsdelivr.net\/npm\/chart.js@4.4.4\/dist\/chart.umd.min.js\"><\/script>\n<script>\nconst COLORS = [\"#22c55e\",\"#ef4444\",\"#f97316\",\"#eab308\",\"#10b981\",\"#60a5fa\"];\n\nconst DATA = {\n weeks: [\"Preseason\",\"1\",\"2\",\"3\",\"4\",\"5\",\"6\",\"7\",\"8\",\"9\",\"10\"],\n teams: [\"Miami\",\"Alabama\",\"Texas\",\"Notre Dame\",\"Oregon\",\"Georgia\"],\n ranks: {\n \/\/ Preseason from your image\n \"Miami\": [10, 5, 5, 2, 3, 2, 2, 9,11, 9,11],\n \"Alabama\": [ 8, null, null, 6,10, 8, 6, 4, 4, 4, 4],\n \"Texas\": [ 1, 7, 7, 7, 9, null, null, null, null, null, null],\n \"Notre Dame\": [ 6, 9, 8,11, null,16,13,12,12,12,12],\n \"Oregon\": [ 7, 6, 8, 8, 2, 3, 8, 6, 6, 6, 6],\n \"Georgia\": [ 5, 4, 6, 6,12,10, 9, 5, 5, 5, 5]\n }\n};\n\n\/\/ Helpers\nfunction trendBadge(curr, prev){\n if (curr == null || prev == null) return '<span class=\"badge flat\">\u2013';\n const delta = prev - curr;\n if (delta > 0) return `<span class=\"badge up\">\u2191 ${Math.abs(delta)}`;\n if (delta < 0) return `<span class=\"badge down\">\u2193 ${Math.abs(delta)}`;\n return `<span class=\"badge flat\">\u00b7`;\n}\n\nfunction renderTable(state){\n const thead = document.getElementById('thead');\n const tbody = document.getElementById('tbody');\n thead.innerHTML = `<tr><th>Week${state.teams.map(t=>`<th>${t}`).join('')}`;\n const rows = [];\n for (let i=0;i<state.weeks.length;i++){\n const week = state.weeks[i];\n const cells = [`<td><strong>${week}`];\n for (const t of state.teams){\n const v = state.ranks[t][i];\n const prev = i>0 ? state.ranks[t][i-1] : null;\n cells.push(`<td>${v==null?'NR':'#'+v} ${trendBadge(v, prev)}`);\n }\n rows.push(`<tr>${cells.join('')}`);\n }\n tbody.innerHTML = rows.join('');\n}\n\nfunction renderLegend(datasets){\n const el = document.getElementById('legend');\n el.innerHTML = datasets.map((d,i)=>`<span class=\"pill\"><span class=\"swatch\" style=\"background:${COLORS[i%COLORS.length]}\">${d.label}`).join('');\n}\n\nconst ctx = document.getElementById('rankChart').getContext('2d');\nlet chart;\nfunction renderChart(state){\n const datasets = state.teams.map((t,i)=>({\n label: t,\n data: state.ranks[t].map(v=>v==null?null:v),\n borderColor: COLORS[i%COLORS.length],\n backgroundColor: COLORS[i%COLORS.length],\n tension: .25, spanGaps: true, pointRadius:3, pointHoverRadius:5\n }));\n if (chart) chart.destroy();\n chart = new Chart(ctx, {\n type: 'line',\n data: { labels: state.weeks, datasets },\n options: {\n scales:{\n y:{ reverse:true, suggestedMin:1, suggestedMax:26, title:{display:true,text:'Rank (1 = Best)'} , ticks:{stepSize:1}},\n x:{ title:{display:true,text:'Week'} }\n },\n plugins:{\n tooltip:{ callbacks:{ label:(c)=>`${c.dataset.label}: ${c.raw==null?'NR':'#'+c.raw}` } },\n legend:{ display:false }\n }\n }\n });\n renderLegend(datasets);\n}\n\nlet state = JSON.parse(JSON.stringify(DATA));\nrenderTable(state); renderChart(state);\n\n\/\/ JSON\/CSV editing\nconst editor = document.getElementById('json');\nfunction syncEditor(){ editor.value = JSON.stringify(state,null,2); }\nsyncEditor();\n\ndocument.getElementById('updateBtn').addEventListener('click', ()=>{\n try{\n const next = JSON.parse(editor.value);\n state = next; renderTable(state); renderChart(state);\n }catch(e){ alert('JSON parse error: '+e.message); }\n});\ndocument.getElementById('resetBtn').addEventListener('click', ()=>{ state = JSON.parse(JSON.stringify(DATA)); syncEditor(); renderTable(state); renderChart(state); });\ndocument.getElementById('csv').addEventListener('change', e=>{\n const f = e.target.files[0]; if(!f) return;\n const r = new FileReader();\n r.onload = ()=>{\n const lines = r.result.trim().split(\/\\r?\\n\/).map(l=>l.split(',').map(s=>s.trim()));\n const header = lines[0]; const teams = header.slice(1);\n const weeks=[]; const ranks={}; teams.forEach(t=>ranks[t]=[]);\n for (let i=1;i<lines.length;i++){\n const row=lines[i]; if(!row.length) continue;\n weeks.push(row[0]);\n for (let j=1;j<row.length;j++){\n const v = row[j]===''?null:Number(row[j]);\n ranks[teams[j-1]].push(Number.isFinite(v)?v:null);\n }\n }\n state = { weeks, teams, ranks }; syncEditor(); renderTable(state); renderChart(state);\n };\n r.readAsText(f);\n});\n<\/script>\n\n\n\"\"\"\nwith open(\"\/mnt\/data\/ap-poll-trends-prefilled.html\",\"w\",encoding=\"utf-8\") as f:\n f.write(prefilled_html)\n\n\"\/mnt\/data\/ap-poll-trends-prefilled.html\"\n\n\n\n<p><\/p>\n<\/body>","protected":false},"excerpt":{"rendered":"<p>\u201cGrace & Brand: How the AP Poll Looks Like It Plays Favorites in College Football\u201dBy [Demetrius A Thompson], Special to the Journal At the heart of every college-football season lies the weekly ritual of the AP Top 25. Since 1936, this poll has served as a barometer of perceived strength, prestige and momentum across the […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":""},"categories":[1],"tags":[],"class_list":["post-461","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"jetpack_featured_media_url":"","jetpack_likes_enabled":true,"jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/posts\/461","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/comments?post=461"}],"version-history":[{"count":3,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/posts\/461\/revisions"}],"predecessor-version":[{"id":464,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/posts\/461\/revisions\/464"}],"wp:attachment":[{"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/media?parent=461"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/categories?post=461"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/studio1live.com\/picks\/wp-json\/wp\/v2\/tags?post=461"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}