11 “smoky in here” graphs from Bama vs. Tennessee

SB Nation

Whew! That was fun, if occasionally nerve-wracking. The SEC and CFP implications are obviously important, and perhaps less so are the accolades like “consecutive ranked teams defeated;” but a rivalry game

is a precious thing, and Bama won this one. Roll Tide!

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Stats	Alabama	Tennessee
Points	37	20
Game Excitement	4.6	4.6
Total yards	373	410
Rush yards	120	142
Rush attempts	32	33
Yards per rush	3.8	4.3
Pass yards	253	268
Pass attempts	19-29	28-44
Yards per pass	8.7	6.1
1st downs	23	27
3rd down eff	5-11	5-13
4th down eff	1-1	4-5
Explosiveness	1.13	1.21
Turnovers	1	1
Tackles	41	28
Sacks	4	0
Penalties-Yds	7-59	10-66
Possession	31:04	28:56

It wasn’t without its flaws though. For one, there’s a sobering way to look at this given the 99-yard INT-to-TD by Zabien Brown to close the first half. Without that likely-10-to-14-point swing, this game looks more like a 30-24 or 30-27 win. So, another “fingers crossed til the end” win … which is honestly how this game still felt at times. (Good thing Alabama had a few playmakers — notably Ryan Williams, Daniel Hill, Josh Cuevas, Germie Bernard, and Ty Simpson — come up big in moments to keep the chains moving.)

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SR and XR by Down

Alabama vs. Tennessee • Oct 18, 2025

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But you can tell a more optimistic story, too. After all, the Vols started going for it on 4th down as early as the 1st quarter — albeit a sensible 4-and-1 slightly inside Bama territory — and they came up with 4/5 of them (80% SR). Listen, the announcers reminded us that Heupel’s gang might just be good at 4th downs (our one stop Saturday was, I think, their first failed 4th down conversion all season). But, regardless of your offense’s quality, an 80% SR on 4th down (100% during non-garbage time) is just mathematically unlikely. It reminds me of the UGA comeback last year (with their frustrating 5/5 on 4th down). In either of these games, one fewer conversion there makes these games essentially over.

To a lesser extent, it even reminds me of Alabama’s 4th down successes the last few weeks, including a 4th-and-8 at Mizzou, but our last two wins have both been 2-3 4th down ratios, not crazy. Alabama’s first half 3rd down performance against Georgia this year was also pretty unlikely.

Speaking of: also in the downs chart is Bama’s continued over-performance on 3rd down. The Vols struggled there relative to their other downs, resulting in some important stops in what was supposed to be a “stop them once and win” shootout. (So much for that.)

The run defense is probably bad

There are some good charts this week, but I’ll get some of the bad out of the way first. I’ve waffled on the run defense the last few weeks: we’ve now had obvious busts against Georgia and Tennessee, but also mixed signals against vaunted rush offenses like Missouri and Vanderbilt. It’s genuinely confusing.

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SR and XR by Play Type (Bar Chart)

Alabama vs. Tennessee • Oct 18, 2025

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'#26262660' : 'transparent'; }, borderColor: function(context) { const value = context.dataset.data[context.dataIndex]; return value > 0 ? 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Chart failed to load. Please refresh the page.

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But Tennessee made it clear once again that this rush defense can very much be had. We suspected that that orange offense would get some points, but many of us hoped that shutting down the pass would more than alleviate that.

In some ways, we got that, with a critical INT and a relatively low passing SR from the Vols. We also mostly forced the Vols into a surprisingly clock-burning offense: their TOP was only a few minutes less than Alabama’s, and exceeded the Tide’s until late in the game. Plus, the box score prints Tennessee’s Yards Per Rush as 4.3 yards, which is fine but not high.

But their efficiency was high … just look at the rushers chart:

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Top rushers

Alabama vs. Tennessee • Oct 18, 2025

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'#666' : dataset.borderColor, lineWidth: dataset.label === '# Plays' ? 1 : dataset.borderWidth, hidden: !chart.isDatasetVisible(i), datasetIndex: i }; }).filter((item, index) => { // Apply the same filter logic as above const dataset = chart.data.datasets[index]; if (!dataset || !dataset.data) return false; if (dataset.label === '# Plays') return true; // Always show # Plays if (dataset.label && (dataset.label.includes('NCAA Avg SR') || dataset.label.includes('Quarters') || dataset.label.includes('50/50'))) return false; return dataset.data.some((value) => value > 0); }); } return []; } } }, tooltip: 'top-rushers' === 'win-probability' ? { mode: 'index', intersect: false, callbacks: { title: function(tooltipItems) { if (tooltipItems && tooltipItems[0]) { return 'Play ' + (tooltipItems[0].dataIndex + 1); } return ''; }, label: function(context) { const selectedTeamWinProb = context.parsed.y; const opponentWinProb = 100 - selectedTeamWinProb; const selectedTeam = context.dataset.selectedTeam || 'Team'; const opponentTeam = context.dataset.opponentTeam || 'Opponent'; return [ selectedTeam + ': ' + selectedTeamWinProb.toFixed(1) + '%', opponentTeam + ': ' + opponentWinProb.toFixed(1) + '%' ]; }, afterLabel: function(context) { if (context.dataset.playTexts && context.dataset.playTexts[context.dataIndex]) { return '\n' + context.dataset.playTexts[context.dataIndex]; } return ''; } } } : { filter: function(tooltipItem) { if ('top-rushers'.includes('play-map')) { return !tooltipItem.dataset.label.includes('< 0') && !tooltipItem.dataset.label.includes('Quarters') && !tooltipItem.dataset.label.includes('Drive'); } return !tooltipItem.dataset.label.includes('NCAA Avg SR') && !tooltipItem.dataset.label.includes('50/50') && !tooltipItem.dataset.label.includes(' ds.label === 'Win Probability'); if (wpDataset && wpDataset.segmentColors) { wpDataset.segment = { borderColor: function(ctx) { // Use p1DataIndex (ending point) so the line inherits the destination color // This makes momentum shifts more visually intuitive const index = ctx.p1DataIndex; if (index !== undefined && wpDataset.segmentColors[index]) { return wpDataset.segmentColors[index]; } return wpDataset.borderColor || '#8B0000'; } }; } } // Initialize the chart const ctx = canvas.getContext('2d'); const chart = new Chart(ctx, { type: 'bar', data: chartData, options: chartOptions }); // Store reference to prevent re-initialization canvas.chartInstance = chart; console.log('CFB Chart initialized successfully'); } catch (error) { console.error('Error initializing CFB chart:', error); // Fallback: show error message in canvas container const container = document.getElementById('cfb-chart-1760896782777-794dej3nm').parentNode; if (container) { container.innerHTML = '

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Lead RB DeSean Bishop is good, but is he this good? He shredded the Alabama offense for a 78.5% SR; 11 successful rushes total, with 3 of those being explosive. Blegh.

Their backup, Peyton Lewis, didn’t do much, but they picked up some success from other backs (plus one explosive scramble from otherwise-inefficient QB Joey Aguilar).

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SR and XR by Distance to Go

Alabama vs. Tennessee • Oct 18, 2025

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'rgba(255, 255, 255, 0.2)' : 'transparent'; }, borderRadius: 4, align: 'center', anchor: 'center' }, legend: 'distance-bars' === 'win-probability' ? { display: false } : 'bar' === 'line' ? { position: 'top', align: 'start', labels: 'distance-bars'.includes('play-map') ? { usePointStyle: true, generateLabels: function(chart) { // Call the original generateLabels to get default styling const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter and customize each label const filteredLabels = labels.filter(label => { return !label.text.includes(' { const dataset = chart.data.datasets[label.datasetIndex]; if (dataset && dataset.label) { if (dataset.label.includes('Rush')) { label.pointStyle = 'circle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else if (dataset.label.includes('Pass')) { label.pointStyle = 'triangle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else { label.pointStyle = 'rect'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } } }); return filteredLabels; }, boxWidth: 20, padding: 12 } : { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, generateLabels: function(chart) { const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter out reference areas and ensure white fill const filteredLabels = labels.filter(label => { return !label.text.includes('NCAA Avg SR') && !label.text.includes('50/50') && !label.text.includes('Quarters'); }); // Ensure white fill for all line chart legend boxes filteredLabels.forEach((label) => { label.fillStyle = 'white'; }); return filteredLabels; } } } : { position: 'top', align: 'start', labels: { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, filter: function(legendItem, chartData) { return !legendItem.text.includes('NCAA Avg SR') && !legendItem.text.includes('Quarters') && !legendItem.text.includes('50/50'); }, generateLabels: function(chart) { const data = chart.data; if (data.datasets.length) { return data.datasets.map((dataset, i) => { // Handle backgroundColor arrays (like in Overall Team Performance chart) let fillColor = dataset.backgroundColor; if (dataset.label === '# Plays') { fillColor = 'white'; } else if (Array.isArray(dataset.backgroundColor)) { // For datasets with backgroundColor arrays, use the first color for legend fillColor = dataset.backgroundColor[0]; } return { text: dataset.label, fillStyle: fillColor, strokeStyle: dataset.label === '# Plays' ? 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Plus, the Bama defense is still giving up the short stuff (a continued trend from my post in the Feed this week), which probably mostly just a comment on the rush defense.

So, overall it’s another confounding week for this “break don’t bend” rushing defense, which keeps contributing to wins while simultaneously giving us all headaches.

But, some better news ahead

We can revisit a few of the prior charts for good news; too:

The Alabama rushing offense can feel frustrating, but we ended up with a 48% rushing SR. That’s pretty good! It was only 3.8 yards per rush, but “success” can mean converting on short yardage situations, and that’s fine by me.
The Alabama rushers had an OK day: lead back Jam Miller was more efficient than he looked (at least after he warmed back up), Daniel Hill was a monster in the 4th quarter, and Germie Bernard pulled a few rabbits out of a few hats to make his rushing line look surprisingly great.
And Alabama is still outperforming opponents from long and medium distance. That speaks to some flexibility in how this offense moves the ball, and helps explain how we also get solid success from short yardage.

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Overall Team Performance

Alabama vs. Tennessee • Oct 18, 2025

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Please refresh the page.'); return; } setTimeout(initChart, 100); return; } // Check if canvas element exists const canvas = document.getElementById('cfb-chart-1760899063563-ukmr8atki'); if (!canvas) { console.warn('Canvas element not found yet, retrying...'); setTimeout(initChart, 100); return; } // Prevent multiple chart instances if (canvas.chartInstance) { console.log('Chart already initialized'); return; } try { // Register the datalabels plugin Chart.register(ChartDataLabels); // Embed actual chart data directly const chartData = { "labels": [ "Alabama", "Tennessee" ], "datasets": [ { "label": "Explosiveness Rate (XR)", "data": [ 0.18333333333333332, 0.15584415584415584 ], "backgroundColor": [ "rgba(101, 0, 20, 0.8)", "rgba(128, 65, 0, 0.8)" ], "stack": "SRXR", "datalabels": { "display": false } }, { "label": "Success Rate (SR)", "data": [ 0.5166666666666667, 0.4675324675324675 ], "backgroundColor": [ "rgba(175, 40, 60, 0.8)", "rgba(244, 142, 37, 0.8)" ], "stack": "SRXR", "datalabels": { "display": true }, "playCountData": [ 60, 77 ] }, { "type": "line", "data": [ 0.42, 0.42 ], "label": "NCAA Avg SR", "borderColor": "#757575", "borderWidth": 2, "borderDash": [ 3, 3 ], "pointRadius": 0, "datalabels": { "display": false } }, { "type": "line", "data": [ null, null ], "label": "# Plays", "backgroundColor": "rgba(0, 0, 0, 0)", "borderColor": "rgba(0, 0, 0, 0)", "borderWidth": 0, "pointRadius": 0, "showLine": false, "fill": false, "datalabels": { "display": false } } ], "teamColors": { "success": "rgba(175, 40, 60, 0.8)", "explosive": "rgba(101, 0, 20, 0.8)", "light": "rgba(245, 229, 233, 0.8)" }, "opponentColors": { "success": "rgba(244, 142, 37, 0.8)", "explosive": "rgba(128, 65, 0, 0.8)", "light": "rgba(255, 243, 230, 0.8)" }, "teamPlayCount": 60, "opponentPlayCount": 77, "currentParams": { "year": 2025, "week": 8, "seasonType": "regular", "team": "Alabama", "gameId": "401752738" } }; // Chart options (WordPress-safe) const chartOptions = { responsive: true, maintainAspectRatio: false, animation: { duration: 1 // Minimal animation to trigger layout calculation (fixes label positioning) }, elements: 'bar' === 'line' ? 'overall-team-performance'.includes('play-map') ? { line: { tension: 0, borderWidth: 0 } } : 'overall-team-performance' === 'win-probability' ? { line: { tension: 0.15, borderWidth: 2.2, fill: false }, point: { pointRadius: 0, pointHoverRadius: 4 } } : { line: { tension: 0.25, borderWidth: 2.2 }, point: { pointRadius: 'overall-team-performance'.includes('team-lines') ? 0 : undefined } } : {}, plugins: { datalabels: { display: function(context) { // Suppress data labels on line charts if ('bar' === 'line') { return false; } return context.dataset.datalabels && context.dataset.datalabels.display === true; }, formatter: function(value, context) { // Special handling for Overall Team Performance chart if ('overall-team-performance' === 'overall-team-performance' && context.dataset.label === 'Success Rate (SR)') { // Use the stored play count data if (context.dataset.playCountData && context.dataset.playCountData[context.dataIndex]) { return context.dataset.playCountData[context.dataIndex]; } // Fallback to percentage if play count data not available return Math.round(value * 100) + '%'; } // Handle bar charts with count data (play-type, quarter, down, etc.) if (context.dataset.label && context.dataset.label.includes(' SR') && (chartData.teamCounts || chartData.oppCounts)) { // Find the first team SR dataset in the chart to determine team order const allDatasets = context.chart.data.datasets; const teamSRDataset = allDatasets.find(d => d.label && d.label.includes(' SR') && !d.label.includes('NCAA')); // If this is the first team's SR dataset, use teamCounts if (teamSRDataset && context.dataset.label === teamSRDataset.label && chartData.teamCounts) { return chartData.teamCounts[context.dataIndex] || 0; } // Otherwise, use oppCounts for the second team else if (chartData.oppCounts) { return chartData.oppCounts[context.dataIndex] || 0; } } // For player charts, show value only if > 0 (matches non-embedded behavior) if ('overall-team-performance'.includes('top-rushers') || 'overall-team-performance'.includes('top-passers') || 'overall-team-performance'.includes('top-receivers')) { // Hide data labels for zero or negative values, show actual value for positive values return value > 0 ? value : null; } // For other charts, show values based on type if (typeof value === 'number') { // If value is between 0 and 1, treat as percentage if (value >= 0 && value 0 ? '#26262660' : 'transparent'; }, borderColor: function(context) { const value = context.dataset.data[context.dataIndex]; return value > 0 ? 'rgba(255, 255, 255, 0.2)' : 'transparent'; }, borderRadius: 4, align: 'center', anchor: 'center' }, legend: 'overall-team-performance' === 'win-probability' ? { display: false } : 'bar' === 'line' ? { position: 'top', align: 'start', labels: 'overall-team-performance'.includes('play-map') ? { usePointStyle: true, generateLabels: function(chart) { // Call the original generateLabels to get default styling const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter and customize each label const filteredLabels = labels.filter(label => { return !label.text.includes(' { const dataset = chart.data.datasets[label.datasetIndex]; if (dataset && dataset.label) { if (dataset.label.includes('Rush')) { label.pointStyle = 'circle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else if (dataset.label.includes('Pass')) { label.pointStyle = 'triangle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else { label.pointStyle = 'rect'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } } }); return filteredLabels; }, boxWidth: 20, padding: 12 } : { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, generateLabels: function(chart) { const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter out reference areas and ensure white fill const filteredLabels = labels.filter(label => { return !label.text.includes('NCAA Avg SR') && !label.text.includes('50/50') && !label.text.includes('Quarters'); }); // Ensure white fill for all line chart legend boxes filteredLabels.forEach((label) => { label.fillStyle = 'white'; }); return filteredLabels; } } } : { position: 'top', align: 'start', labels: { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, filter: function(legendItem, chartData) { return !legendItem.text.includes('NCAA Avg SR') && !legendItem.text.includes('Quarters') && !legendItem.text.includes('50/50'); }, generateLabels: function(chart) { const data = chart.data; if (data.datasets.length) { return data.datasets.map((dataset, i) => { // Handle backgroundColor arrays (like in Overall Team Performance chart) let fillColor = dataset.backgroundColor; if (dataset.label === '# Plays') { fillColor = 'white'; } else if (Array.isArray(dataset.backgroundColor)) { // For datasets with backgroundColor arrays, use the first color for legend fillColor = dataset.backgroundColor[0]; } return { text: dataset.label, fillStyle: fillColor, strokeStyle: dataset.label === '# Plays' ? '#666' : dataset.borderColor, lineWidth: dataset.label === '# Plays' ? 1 : dataset.borderWidth, hidden: !chart.isDatasetVisible(i), datasetIndex: i }; }).filter((item, index) => { // Apply the same filter logic as above const dataset = chart.data.datasets[index]; if (!dataset || !dataset.data) return false; if (dataset.label === '# Plays') return true; // Always show # Plays if (dataset.label && (dataset.label.includes('NCAA Avg SR') || dataset.label.includes('Quarters') || dataset.label.includes('50/50'))) return false; return dataset.data.some((value) => value > 0); }); } return []; } } }, tooltip: 'overall-team-performance' === 'win-probability' ? { mode: 'index', intersect: false, callbacks: { title: function(tooltipItems) { if (tooltipItems && tooltipItems[0]) { return 'Play ' + (tooltipItems[0].dataIndex + 1); } return ''; }, label: function(context) { const selectedTeamWinProb = context.parsed.y; const opponentWinProb = 100 - selectedTeamWinProb; const selectedTeam = context.dataset.selectedTeam || 'Team'; const opponentTeam = context.dataset.opponentTeam || 'Opponent'; return [ selectedTeam + ': ' + selectedTeamWinProb.toFixed(1) + '%', opponentTeam + ': ' + opponentWinProb.toFixed(1) + '%' ]; }, afterLabel: function(context) { if (context.dataset.playTexts && context.dataset.playTexts[context.dataIndex]) { return '\n' + context.dataset.playTexts[context.dataIndex]; } return ''; } } } : { filter: function(tooltipItem) { if ('overall-team-performance'.includes('play-map')) { return !tooltipItem.dataset.label.includes('< 0') && !tooltipItem.dataset.label.includes('Quarters') && !tooltipItem.dataset.label.includes('Drive'); } return !tooltipItem.dataset.label.includes('NCAA Avg SR') && !tooltipItem.dataset.label.includes('50/50') && !tooltipItem.dataset.label.includes(' ds.label === 'Win Probability'); if (wpDataset && wpDataset.segmentColors) { wpDataset.segment = { borderColor: function(ctx) { // Use p1DataIndex (ending point) so the line inherits the destination color // This makes momentum shifts more visually intuitive const index = ctx.p1DataIndex; if (index !== undefined && wpDataset.segmentColors[index]) { return wpDataset.segmentColors[index]; } return wpDataset.borderColor || '#8B0000'; } }; } } // Initialize the chart const ctx = canvas.getContext('2d'); const chart = new Chart(ctx, { type: 'bar', data: chartData, options: chartOptions }); // Store reference to prevent re-initialization canvas.chartInstance = chart; console.log('CFB Chart initialized successfully'); } catch (error) { console.error('Error initializing CFB chart:', error); // Fallback: show error message in canvas container const container = document.getElementById('cfb-chart-1760899063563-ukmr8atki').parentNode; if (container) { container.innerHTML = '

Chart failed to load. Please refresh the page.

'; } } } // Start loading scripts sequentially function startLoading() { // First, check if scripts are already loaded (multiple embeds on same page) if (typeof Chart !== 'undefined' && typeof ChartDataLabels !== 'undefined') { initChart(); return; } // Load Chart.js first if (typeof Chart === 'undefined') { loadScript('https://cdn.jsdelivr.net/npm/chart.js@3.9.1/dist/chart.min.js', function() { // Then load ChartDataLabels if (typeof ChartDataLabels === 'undefined') { loadScript('https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2.2.0', function() { initChart(); }); } else { initChart(); } }); } else if (typeof ChartDataLabels === 'undefined') { // Chart.js loaded but not ChartDataLabels loadScript('https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2.2.0', function() { initChart(); }); } else { initChart(); } } // Initialize when DOM is ready if (document.readyState === 'loading') { document.addEventListener('DOMContentLoaded', startLoading); } else { startLoading(); } })();

Plus, I buried the lede here, but after weeks of my griping Alabama’s underperformance in the advanced metrics in close wins … we showed a good overall efficiency advantage (52% to 47% SR) against the Vols.

We also technically had an advantage in Explosiveness Rate (18% to 16%), but it’s a little fools’ gold considering that our overall Explosiveness Index was 1.13 (very low) to the Vols’ 1.21 (just pretty low). That is, we had some of those 15-ish yard pickups, but weren’t getting any huge plays … even compared to the Vols, who hardly got any huge plays.

I mean, you can see it in the Play Map:

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Play Map: Alabama

Alabama vs. Tennessee • Oct 18, 2025

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In a not-particularly-positive trend from this season, the Tide isn’t picking up big chunk plays. This Play Map is at least somewhat respectable, with some really solid drives in the 3rd quarter especially. You can see some explosives sprinkled in across the first three quarters. But there weren’t that many, and they were just little baby <20 yard explosives. Behold all of that white expanse at the top of this chart, totally undisturbed by any plays by Ty and his vaunted receivers.

Sure, it also doesn’t help that every time we play a team with a “bad secondary” — FSU, Tennessee — their strategy seems to be “just take the PI calls” whenever Ty airs it out. And, unfortunately, it appears to be a good idea. Makes me wonder if NCAA ball needs an “Egregious PI” sub-category that they can enforce more like the NFL, rather than doling out measly 15-yard punishments for PI’s that kill potentially >30 yard receptions.

Trend reversals abound

Well, well, here’s a nice surprise:

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SR and XR by Red Zone

Alabama vs. Tennessee • Oct 18, 2025

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Please refresh the page.'); return; } setTimeout(initChart, 100); return; } // Check if canvas element exists const canvas = document.getElementById('cfb-chart-1760899145369-h8x05zkgc'); if (!canvas) { console.warn('Canvas element not found yet, retrying...'); setTimeout(initChart, 100); return; } // Prevent multiple chart instances if (canvas.chartInstance) { console.log('Chart already initialized'); return; } try { // Register the datalabels plugin Chart.register(ChartDataLabels); // Embed actual chart data directly const chartData = { "labels": [ "Red Zone", "Other" ], "datasets": [ { "data": [ 0, 0.23404255319148937 ], "stack": "Team", "label": "Alabama XR", "backgroundColor": "rgba(101, 0, 20, 0.8)", "datalabels": { "display": false } }, { "data": [ 0.6923076923076923, 0.46808510638297873 ], "stack": "Team", "label": "Alabama SR", "backgroundColor": "rgba(175, 40, 60, 0.8)", "datalabels": { "display": true } }, { "data": [ 0, 0.21818181818181817 ], "stack": "Opponent", "label": "Tennessee XR", "backgroundColor": "rgba(128, 65, 0, 0.8)", "datalabels": { "display": false } }, { "data": [ 0.45454545454545453, 0.4727272727272727 ], "stack": "Opponent", "label": "Tennessee SR", "backgroundColor": "rgba(244, 142, 37, 0.8)", "datalabels": { "display": true } }, { "type": "line", "data": [ 0.42, 0.42 ], "label": "NCAA Avg SR", "borderColor": "#757575", "borderWidth": 2, "borderDash": [ 3, 3 ], "pointRadius": 0, "datalabels": { "display": false } }, { "type": "line", "data": [ null, null ], "label": "# Plays", "backgroundColor": "rgba(0, 0, 0, 0)", "borderColor": "rgba(0, 0, 0, 0)", "borderWidth": 0, "pointRadius": 0, "showLine": false, "fill": false, "datalabels": { "display": false } } ], "teamCounts": [ 13, 47 ], "oppCounts": [ 22, 55 ], "currentParams": { "year": 2025, "week": 8, "seasonType": "regular", "team": "Alabama", "gameId": "401752738" } }; // Chart options (WordPress-safe) const chartOptions = { responsive: true, maintainAspectRatio: false, animation: { duration: 1 // Minimal animation to trigger layout calculation (fixes label positioning) }, elements: 'bar' === 'line' ? 'red-zone-bars'.includes('play-map') ? { line: { tension: 0, borderWidth: 0 } } : 'red-zone-bars' === 'win-probability' ? { line: { tension: 0.15, borderWidth: 2.2, fill: false }, point: { pointRadius: 0, pointHoverRadius: 4 } } : { line: { tension: 0.25, borderWidth: 2.2 }, point: { pointRadius: 'red-zone-bars'.includes('team-lines') ? 0 : undefined } } : {}, plugins: { datalabels: { display: function(context) { // Suppress data labels on line charts if ('bar' === 'line') { return false; } return context.dataset.datalabels && context.dataset.datalabels.display === true; }, formatter: function(value, context) { // Special handling for Overall Team Performance chart if ('red-zone-bars' === 'overall-team-performance' && context.dataset.label === 'Success Rate (SR)') { // Use the stored play count data if (context.dataset.playCountData && context.dataset.playCountData[context.dataIndex]) { return context.dataset.playCountData[context.dataIndex]; } // Fallback to percentage if play count data not available return Math.round(value * 100) + '%'; } // Handle bar charts with count data (play-type, quarter, down, etc.) if (context.dataset.label && context.dataset.label.includes(' SR') && (chartData.teamCounts || chartData.oppCounts)) { // Find the first team SR dataset in the chart to determine team order const allDatasets = context.chart.data.datasets; const teamSRDataset = allDatasets.find(d => d.label && d.label.includes(' SR') && !d.label.includes('NCAA')); // If this is the first team's SR dataset, use teamCounts if (teamSRDataset && context.dataset.label === teamSRDataset.label && chartData.teamCounts) { return chartData.teamCounts[context.dataIndex] || 0; } // Otherwise, use oppCounts for the second team else if (chartData.oppCounts) { return chartData.oppCounts[context.dataIndex] || 0; } } // For player charts, show value only if > 0 (matches non-embedded behavior) if ('red-zone-bars'.includes('top-rushers') || 'red-zone-bars'.includes('top-passers') || 'red-zone-bars'.includes('top-receivers')) { // Hide data labels for zero or negative values, show actual value for positive values return value > 0 ? value : null; } // For other charts, show values based on type if (typeof value === 'number') { // If value is between 0 and 1, treat as percentage if (value >= 0 && value 0 ? '#26262660' : 'transparent'; }, borderColor: function(context) { const value = context.dataset.data[context.dataIndex]; return value > 0 ? 'rgba(255, 255, 255, 0.2)' : 'transparent'; }, borderRadius: 4, align: 'center', anchor: 'center' }, legend: 'red-zone-bars' === 'win-probability' ? { display: false } : 'bar' === 'line' ? { position: 'top', align: 'start', labels: 'red-zone-bars'.includes('play-map') ? { usePointStyle: true, generateLabels: function(chart) { // Call the original generateLabels to get default styling const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter and customize each label const filteredLabels = labels.filter(label => { return !label.text.includes(' { const dataset = chart.data.datasets[label.datasetIndex]; if (dataset && dataset.label) { if (dataset.label.includes('Rush')) { label.pointStyle = 'circle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else if (dataset.label.includes('Pass')) { label.pointStyle = 'triangle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else { label.pointStyle = 'rect'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } } }); return filteredLabels; }, boxWidth: 20, padding: 12 } : { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, generateLabels: function(chart) { const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter out reference areas and ensure white fill const filteredLabels = labels.filter(label => { return !label.text.includes('NCAA Avg SR') && !label.text.includes('50/50') && !label.text.includes('Quarters'); }); // Ensure white fill for all line chart legend boxes filteredLabels.forEach((label) => { label.fillStyle = 'white'; }); return filteredLabels; } } } : { position: 'top', align: 'start', labels: { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, filter: function(legendItem, chartData) { return !legendItem.text.includes('NCAA Avg SR') && !legendItem.text.includes('Quarters') && !legendItem.text.includes('50/50'); }, generateLabels: function(chart) { const data = chart.data; if (data.datasets.length) { return data.datasets.map((dataset, i) => { // Handle backgroundColor arrays (like in Overall Team Performance chart) let fillColor = dataset.backgroundColor; if (dataset.label === '# Plays') { fillColor = 'white'; } else if (Array.isArray(dataset.backgroundColor)) { // For datasets with backgroundColor arrays, use the first color for legend fillColor = dataset.backgroundColor[0]; } return { text: dataset.label, fillStyle: fillColor, strokeStyle: dataset.label === '# Plays' ? '#666' : dataset.borderColor, lineWidth: dataset.label === '# Plays' ? 1 : dataset.borderWidth, hidden: !chart.isDatasetVisible(i), datasetIndex: i }; }).filter((item, index) => { // Apply the same filter logic as above const dataset = chart.data.datasets[index]; if (!dataset || !dataset.data) return false; if (dataset.label === '# Plays') return true; // Always show # Plays if (dataset.label && (dataset.label.includes('NCAA Avg SR') || dataset.label.includes('Quarters') || dataset.label.includes('50/50'))) return false; return dataset.data.some((value) => value > 0); }); } return []; } } }, tooltip: 'red-zone-bars' === 'win-probability' ? { mode: 'index', intersect: false, callbacks: { title: function(tooltipItems) { if (tooltipItems && tooltipItems[0]) { return 'Play ' + (tooltipItems[0].dataIndex + 1); } return ''; }, label: function(context) { const selectedTeamWinProb = context.parsed.y; const opponentWinProb = 100 - selectedTeamWinProb; const selectedTeam = context.dataset.selectedTeam || 'Team'; const opponentTeam = context.dataset.opponentTeam || 'Opponent'; return [ selectedTeam + ': ' + selectedTeamWinProb.toFixed(1) + '%', opponentTeam + ': ' + opponentWinProb.toFixed(1) + '%' ]; }, afterLabel: function(context) { if (context.dataset.playTexts && context.dataset.playTexts[context.dataIndex]) { return '\n' + context.dataset.playTexts[context.dataIndex]; } return ''; } } } : { filter: function(tooltipItem) { if ('red-zone-bars'.includes('play-map')) { return !tooltipItem.dataset.label.includes('< 0') && !tooltipItem.dataset.label.includes('Quarters') && !tooltipItem.dataset.label.includes('Drive'); } return !tooltipItem.dataset.label.includes('NCAA Avg SR') && !tooltipItem.dataset.label.includes('50/50') && !tooltipItem.dataset.label.includes(' ds.label === 'Win Probability'); if (wpDataset && wpDataset.segmentColors) { wpDataset.segment = { borderColor: function(ctx) { // Use p1DataIndex (ending point) so the line inherits the destination color // This makes momentum shifts more visually intuitive const index = ctx.p1DataIndex; if (index !== undefined && wpDataset.segmentColors[index]) { return wpDataset.segmentColors[index]; } return wpDataset.borderColor || '#8B0000'; } }; } } // Initialize the chart const ctx = canvas.getContext('2d'); const chart = new Chart(ctx, { type: 'bar', data: chartData, options: chartOptions }); // Store reference to prevent re-initialization canvas.chartInstance = chart; console.log('CFB Chart initialized successfully'); } catch (error) { console.error('Error initializing CFB chart:', error); // Fallback: show error message in canvas container const container = document.getElementById('cfb-chart-1760899145369-h8x05zkgc').parentNode; if (container) { container.innerHTML = '

Chart failed to load. Please refresh the page.

'; } } } // Start loading scripts sequentially function startLoading() { // First, check if scripts are already loaded (multiple embeds on same page) if (typeof Chart !== 'undefined' && typeof ChartDataLabels !== 'undefined') { initChart(); return; } // Load Chart.js first if (typeof Chart === 'undefined') { loadScript('https://cdn.jsdelivr.net/npm/chart.js@3.9.1/dist/chart.min.js', function() { // Then load ChartDataLabels if (typeof ChartDataLabels === 'undefined') { loadScript('https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2.2.0', function() { initChart(); }); } else { initChart(); } }); } else if (typeof ChartDataLabels === 'undefined') { // Chart.js loaded but not ChartDataLabels loadScript('https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2.2.0', function() { initChart(); }); } else { initChart(); } } // Initialize when DOM is ready if (document.readyState === 'loading') { document.addEventListener('DOMContentLoaded', startLoading); } else { startLoading(); } })();

In a sharp reversal of recent trends, the Tide did really well in the Red Zone: they outperformed the Vols by 21 points (69% to 48% SR), but even more remarkably, they outperformed their performance elsewhere on the field by the same amount. Sure, you don’t see (and don’t really expect) explosives in that line, but that is a very, very strong performance there.

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SR, XR, and Play Count by Drive: Alabama

Alabama vs. Tennessee • Oct 18, 2025

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Please refresh the page.'); return; } setTimeout(initChart, 100); return; } // Check if canvas element exists const canvas = document.getElementById('cfb-chart-1760899173796-nlo22qnl9'); if (!canvas) { console.warn('Canvas element not found yet, retrying...'); setTimeout(initChart, 100); return; } // Prevent multiple chart instances if (canvas.chartInstance) { console.log('Chart already initialized'); return; } try { // Register the datalabels plugin Chart.register(ChartDataLabels); // Embed actual chart data directly const chartData = { "labels": [ "Drive 2", "Drive 4", "Drive 6", "Drive 8", "Drive 10", "Drive 12", "Drive 14", "Drive 16", "Drive 18" ], "datasets": [ { "label": "Alabama XR", "data": [ 0.2727272727272727, 0.16666666666666666, 0, 0.2857142857142857, 0, 0.125, 0.4444444444444444, 0, 0 ], "backgroundColor": "rgba(101, 0, 20, 0.8)", "stack": "SRXR", "yAxisID": "y", "datalabels": { "display": false } }, { "label": "Alabama SR", "data": [ 0.5454545454545454, 0.5, 0, 0.7142857142857143, 0, 0.5, 0.8888888888888888, 0.5, 0 ], "backgroundColor": "rgba(175, 40, 60, 0.8)", "stack": "SRXR", "yAxisID": "y", "datalabels": { "display": false } }, { "label": "Plays in drive", "data": [ 11, 6, 3, 7, 3, 8, 9, 10, 3 ], "backgroundColor": "rgba(148, 148, 148, 0.8)", "stack": "Plays", "yAxisID": "y1", "datalabels": { "display": true } } ], "currentParams": { "year": 2025, "week": 8, "seasonType": "regular", "team": "Alabama", "gameId": "401752738" } }; // Chart options (WordPress-safe) const chartOptions = { responsive: true, maintainAspectRatio: false, animation: { duration: 1 // Minimal animation to trigger layout calculation (fixes label positioning) }, elements: 'bar' === 'line' ? 'team-drive-metrics'.includes('play-map') ? { line: { tension: 0, borderWidth: 0 } } : 'team-drive-metrics' === 'win-probability' ? { line: { tension: 0.15, borderWidth: 2.2, fill: false }, point: { pointRadius: 0, pointHoverRadius: 4 } } : { line: { tension: 0.25, borderWidth: 2.2 }, point: { pointRadius: 'team-drive-metrics'.includes('team-lines') ? 0 : undefined } } : {}, plugins: { datalabels: { display: function(context) { // Suppress data labels on line charts if ('bar' === 'line') { return false; } return context.dataset.datalabels && context.dataset.datalabels.display === true; }, formatter: function(value, context) { // Special handling for Overall Team Performance chart if ('team-drive-metrics' === 'overall-team-performance' && context.dataset.label === 'Success Rate (SR)') { // Use the stored play count data if (context.dataset.playCountData && context.dataset.playCountData[context.dataIndex]) { return context.dataset.playCountData[context.dataIndex]; } // Fallback to percentage if play count data not available return Math.round(value * 100) + '%'; } // Handle bar charts with count data (play-type, quarter, down, etc.) if (context.dataset.label && context.dataset.label.includes(' SR') && (chartData.teamCounts || chartData.oppCounts)) { // Find the first team SR dataset in the chart to determine team order const allDatasets = context.chart.data.datasets; const teamSRDataset = allDatasets.find(d => d.label && d.label.includes(' SR') && !d.label.includes('NCAA')); // If this is the first team's SR dataset, use teamCounts if (teamSRDataset && context.dataset.label === teamSRDataset.label && chartData.teamCounts) { return chartData.teamCounts[context.dataIndex] || 0; } // Otherwise, use oppCounts for the second team else if (chartData.oppCounts) { return chartData.oppCounts[context.dataIndex] || 0; } } // For player charts, show value only if > 0 (matches non-embedded behavior) if ('team-drive-metrics'.includes('top-rushers') || 'team-drive-metrics'.includes('top-passers') || 'team-drive-metrics'.includes('top-receivers')) { // Hide data labels for zero or negative values, show actual value for positive values return value > 0 ? value : null; } // For other charts, show values based on type if (typeof value === 'number') { // If value is between 0 and 1, treat as percentage if (value >= 0 && value 0 ? '#26262660' : 'transparent'; }, borderColor: function(context) { const value = context.dataset.data[context.dataIndex]; return value > 0 ? 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'#666' : dataset.borderColor, lineWidth: dataset.label === '# Plays' ? 1 : dataset.borderWidth, hidden: !chart.isDatasetVisible(i), datasetIndex: i }; }).filter((item, index) => { // Apply the same filter logic as above const dataset = chart.data.datasets[index]; if (!dataset || !dataset.data) return false; if (dataset.label === '# Plays') return true; // Always show # Plays if (dataset.label && (dataset.label.includes('NCAA Avg SR') || dataset.label.includes('Quarters') || dataset.label.includes('50/50'))) return false; return dataset.data.some((value) => value > 0); }); } return []; } } }, tooltip: 'team-drive-metrics' === 'win-probability' ? { mode: 'index', intersect: false, callbacks: { title: function(tooltipItems) { if (tooltipItems && tooltipItems[0]) { return 'Play ' + (tooltipItems[0].dataIndex + 1); } return ''; }, label: function(context) { const selectedTeamWinProb = context.parsed.y; const opponentWinProb = 100 - selectedTeamWinProb; const selectedTeam = context.dataset.selectedTeam || 'Team'; const opponentTeam = context.dataset.opponentTeam || 'Opponent'; return [ selectedTeam + ': ' + selectedTeamWinProb.toFixed(1) + '%', opponentTeam + ': ' + opponentWinProb.toFixed(1) + '%' ]; }, afterLabel: function(context) { if (context.dataset.playTexts && context.dataset.playTexts[context.dataIndex]) { return '\n' + context.dataset.playTexts[context.dataIndex]; } return ''; } } } : { filter: function(tooltipItem) { if ('team-drive-metrics'.includes('play-map')) { return !tooltipItem.dataset.label.includes('< 0') && !tooltipItem.dataset.label.includes('Quarters') && !tooltipItem.dataset.label.includes('Drive'); } return !tooltipItem.dataset.label.includes('NCAA Avg SR') && !tooltipItem.dataset.label.includes('50/50') && !tooltipItem.dataset.label.includes(' ds.label === 'Win Probability'); if (wpDataset && wpDataset.segmentColors) { wpDataset.segment = { borderColor: function(ctx) { // Use p1DataIndex (ending point) so the line inherits the destination color // This makes momentum shifts more visually intuitive const index = ctx.p1DataIndex; if (index !== undefined && wpDataset.segmentColors[index]) { return wpDataset.segmentColors[index]; } return wpDataset.borderColor || '#8B0000'; } }; } } // Initialize the chart const ctx = canvas.getContext('2d'); const chart = new Chart(ctx, { type: 'bar', data: chartData, options: chartOptions }); // Store reference to prevent re-initialization canvas.chartInstance = chart; console.log('CFB Chart initialized successfully'); } catch (error) { console.error('Error initializing CFB chart:', error); // Fallback: show error message in canvas container const container = document.getElementById('cfb-chart-1760899173796-nlo22qnl9').parentNode; if (container) { container.innerHTML = '

Chart failed to load. Please refresh the page.

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SR, XR, and Play Count by Drive: Tennessee

Alabama vs. Tennessee • Oct 18, 2025

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Please refresh the page.'); return; } setTimeout(initChart, 100); return; } // Check if canvas element exists const canvas = document.getElementById('cfb-chart-1760899182761-dshsothi1'); if (!canvas) { console.warn('Canvas element not found yet, retrying...'); setTimeout(initChart, 100); return; } // Prevent multiple chart instances if (canvas.chartInstance) { console.log('Chart already initialized'); return; } try { // Register the datalabels plugin Chart.register(ChartDataLabels); // Embed actual chart data directly const chartData = { "labels": [ "Drive 1", "Drive 3", "Drive 5", "Drive 7", "Drive 9", "Drive 11", "Drive 13", "Drive 15", "Drive 17", "Drive 19" ], "datasets": [ { "label": "Tennessee XR", "data": [ 0, 0.1, 0.2, 0, 0.13333333333333333, 0.25, 0.2, 0.07692307692307693, 0.2222222222222222, 0.2857142857142857 ], "backgroundColor": "rgba(128, 65, 0, 0.8)", "stack": "SRXR", "yAxisID": "y", "datalabels": { "display": false } }, { "label": "Tennessee SR", "data": [ 0.6666666666666666, 0.2, 0.6, 0, 0.4666666666666667, 0.75, 0.2, 0.6153846153846154, 0.3333333333333333, 0.5714285714285714 ], "backgroundColor": "rgba(244, 142, 37, 0.8)", "stack": "SRXR", "yAxisID": "y", "datalabels": { "display": false } }, { "label": "Plays in drive", "data": [ 3, 10, 10, 1, 15, 4, 5, 13, 9, 7 ], "backgroundColor": "rgba(148, 148, 148, 0.8)", "stack": "Plays", "yAxisID": "y1", "datalabels": { "display": true } } ], "currentParams": { "year": 2025, "week": 8, "seasonType": "regular", "team": "Alabama", "gameId": "401752738" } }; // Chart options (WordPress-safe) const chartOptions = { responsive: true, maintainAspectRatio: false, animation: { duration: 1 // Minimal animation to trigger layout calculation (fixes label positioning) }, elements: 'bar' === 'line' ? 'opponent-drive-metrics'.includes('play-map') ? { line: { tension: 0, borderWidth: 0 } } : 'opponent-drive-metrics' === 'win-probability' ? { line: { tension: 0.15, borderWidth: 2.2, fill: false }, point: { pointRadius: 0, pointHoverRadius: 4 } } : { line: { tension: 0.25, borderWidth: 2.2 }, point: { pointRadius: 'opponent-drive-metrics'.includes('team-lines') ? 0 : undefined } } : {}, plugins: { datalabels: { display: function(context) { // Suppress data labels on line charts if ('bar' === 'line') { return false; } return context.dataset.datalabels && context.dataset.datalabels.display === true; }, formatter: function(value, context) { // Special handling for Overall Team Performance chart if ('opponent-drive-metrics' === 'overall-team-performance' && context.dataset.label === 'Success Rate (SR)') { // Use the stored play count data if (context.dataset.playCountData && context.dataset.playCountData[context.dataIndex]) { return context.dataset.playCountData[context.dataIndex]; } // Fallback to percentage if play count data not available return Math.round(value * 100) + '%'; } // Handle bar charts with count data (play-type, quarter, down, etc.) if (context.dataset.label && context.dataset.label.includes(' SR') && (chartData.teamCounts || chartData.oppCounts)) { // Find the first team SR dataset in the chart to determine team order const allDatasets = context.chart.data.datasets; const teamSRDataset = allDatasets.find(d => d.label && d.label.includes(' SR') && !d.label.includes('NCAA')); // If this is the first team's SR dataset, use teamCounts if (teamSRDataset && context.dataset.label === teamSRDataset.label && chartData.teamCounts) { return chartData.teamCounts[context.dataIndex] || 0; } // Otherwise, use oppCounts for the second team else if (chartData.oppCounts) { return chartData.oppCounts[context.dataIndex] || 0; } } // For player charts, show value only if > 0 (matches non-embedded behavior) if ('opponent-drive-metrics'.includes('top-rushers') || 'opponent-drive-metrics'.includes('top-passers') || 'opponent-drive-metrics'.includes('top-receivers')) { // Hide data labels for zero or negative values, show actual value for positive values return value > 0 ? value : null; } // For other charts, show values based on type if (typeof value === 'number') { // If value is between 0 and 1, treat as percentage if (value >= 0 && value 0 ? '#26262660' : 'transparent'; }, borderColor: function(context) { const value = context.dataset.data[context.dataIndex]; return value > 0 ? 'rgba(255, 255, 255, 0.2)' : 'transparent'; }, borderRadius: 4, align: 'center', anchor: 'center' }, legend: 'opponent-drive-metrics' === 'win-probability' ? { display: false } : 'bar' === 'line' ? { position: 'top', align: 'start', labels: 'opponent-drive-metrics'.includes('play-map') ? { usePointStyle: true, generateLabels: function(chart) { // Call the original generateLabels to get default styling const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter and customize each label const filteredLabels = labels.filter(label => { return !label.text.includes(' { const dataset = chart.data.datasets[label.datasetIndex]; if (dataset && dataset.label) { if (dataset.label.includes('Rush')) { label.pointStyle = 'circle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else if (dataset.label.includes('Pass')) { label.pointStyle = 'triangle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else { label.pointStyle = 'rect'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } } }); return filteredLabels; }, boxWidth: 20, padding: 12 } : { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, generateLabels: function(chart) { const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter out reference areas and ensure white fill const filteredLabels = labels.filter(label => { return !label.text.includes('NCAA Avg SR') && !label.text.includes('50/50') && !label.text.includes('Quarters'); }); // Ensure white fill for all line chart legend boxes filteredLabels.forEach((label) => { label.fillStyle = 'white'; }); return filteredLabels; } } } : { position: 'top', align: 'start', labels: { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, filter: function(legendItem, chartData) { return !legendItem.text.includes('NCAA Avg SR') && !legendItem.text.includes('Quarters') && !legendItem.text.includes('50/50'); }, generateLabels: function(chart) { const data = chart.data; if (data.datasets.length) { return data.datasets.map((dataset, i) => { // Handle backgroundColor arrays (like in Overall Team Performance chart) let fillColor = dataset.backgroundColor; if (dataset.label === '# Plays') { fillColor = 'white'; } else if (Array.isArray(dataset.backgroundColor)) { // For datasets with backgroundColor arrays, use the first color for legend fillColor = dataset.backgroundColor[0]; } return { text: dataset.label, fillStyle: fillColor, strokeStyle: dataset.label === '# Plays' ? '#666' : dataset.borderColor, lineWidth: dataset.label === '# Plays' ? 1 : dataset.borderWidth, hidden: !chart.isDatasetVisible(i), datasetIndex: i }; }).filter((item, index) => { // Apply the same filter logic as above const dataset = chart.data.datasets[index]; if (!dataset || !dataset.data) return false; if (dataset.label === '# Plays') return true; // Always show # Plays if (dataset.label && (dataset.label.includes('NCAA Avg SR') || dataset.label.includes('Quarters') || dataset.label.includes('50/50'))) return false; return dataset.data.some((value) => value > 0); }); } return []; } } }, tooltip: 'opponent-drive-metrics' === 'win-probability' ? { mode: 'index', intersect: false, callbacks: { title: function(tooltipItems) { if (tooltipItems && tooltipItems[0]) { return 'Play ' + (tooltipItems[0].dataIndex + 1); } return ''; }, label: function(context) { const selectedTeamWinProb = context.parsed.y; const opponentWinProb = 100 - selectedTeamWinProb; const selectedTeam = context.dataset.selectedTeam || 'Team'; const opponentTeam = context.dataset.opponentTeam || 'Opponent'; return [ selectedTeam + ': ' + selectedTeamWinProb.toFixed(1) + '%', opponentTeam + ': ' + opponentWinProb.toFixed(1) + '%' ]; }, afterLabel: function(context) { if (context.dataset.playTexts && context.dataset.playTexts[context.dataIndex]) { return '\n' + context.dataset.playTexts[context.dataIndex]; } return ''; } } } : { filter: function(tooltipItem) { if ('opponent-drive-metrics'.includes('play-map')) { return !tooltipItem.dataset.label.includes('< 0') && !tooltipItem.dataset.label.includes('Quarters') && !tooltipItem.dataset.label.includes('Drive'); } return !tooltipItem.dataset.label.includes('NCAA Avg SR') && !tooltipItem.dataset.label.includes('50/50') && !tooltipItem.dataset.label.includes(' ds.label === 'Win Probability'); if (wpDataset && wpDataset.segmentColors) { wpDataset.segment = { borderColor: function(ctx) { // Use p1DataIndex (ending point) so the line inherits the destination color // This makes momentum shifts more visually intuitive const index = ctx.p1DataIndex; if (index !== undefined && wpDataset.segmentColors[index]) { return wpDataset.segmentColors[index]; } return wpDataset.borderColor || '#8B0000'; } }; } } // Initialize the chart const ctx = canvas.getContext('2d'); const chart = new Chart(ctx, { type: 'bar', data: chartData, options: chartOptions }); // Store reference to prevent re-initialization canvas.chartInstance = chart; console.log('CFB Chart initialized successfully'); } catch (error) { console.error('Error initializing CFB chart:', error); // Fallback: show error message in canvas container const container = document.getElementById('cfb-chart-1760899182761-dshsothi1').parentNode; if (container) { container.innerHTML = '

Chart failed to load. Please refresh the page.

'; } } } // Start loading scripts sequentially function startLoading() { // First, check if scripts are already loaded (multiple embeds on same page) if (typeof Chart !== 'undefined' && typeof ChartDataLabels !== 'undefined') { initChart(); return; } // Load Chart.js first if (typeof Chart === 'undefined') { loadScript('https://cdn.jsdelivr.net/npm/chart.js@3.9.1/dist/chart.min.js', function() { // Then load ChartDataLabels if (typeof ChartDataLabels === 'undefined') { loadScript('https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2.2.0', function() { initChart(); }); } else { initChart(); } }); } else if (typeof ChartDataLabels === 'undefined') { // Chart.js loaded but not ChartDataLabels loadScript('https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2.2.0', function() { initChart(); }); } else { initChart(); } } // Initialize when DOM is ready if (document.readyState === 'loading') { document.addEventListener('DOMContentLoaded', startLoading); } else { startLoading(); } })();

And I alluded to this a bit earlier, but this is a weird one: Tennessee was the team with the longest drives in this one, with four double-digit drives, including ones of 15 and 13 plays. (Heck, there’s another 9-play one in there too). That looks … much more like Alabama in 2025 than Tennessee. Meanwhile, Alabama’s longest drives were 11, 10, 9, and 8. Respectable, but well below the highs we’ve seen in recent games.

Both teams had duds (3 three-and-outs for Alabama, and a few stalled drives from the Vols, including that safety), but on average Alabama was just moderately more efficient and came up with drive-extending plays when they needed them.

Ok fine I’ll talk about win probability

I thought the win probability chart would be really interesting in this one, given the traded shots we saw between these teams (at least through the first 3 quarters). And, well, you get some of that action:

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Win Probability

Alabama vs. Tennessee • Oct 18, 2025

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"showLine": true, "fill": false, "tension": 0, "order": 90, "datalabels": { "display": false } }, { "label": "Quarters", "data": [ { "x": 32, "y": 0 }, { "x": 32, "y": 100 }, { "x": 158, "y": 100 }, { "x": 158, "y": 0 }, { "x": 77, "y": 0 }, { "x": 77, "y": 100 }, { "x": 158, "y": 100 }, { "x": 158, "y": 0 }, { "x": 112, "y": 0 }, { "x": 112, "y": 100 }, { "x": 158, "y": 100 }, { "x": 158, "y": 0 } ], "borderColor": "rgba(0,0,0,0.1)", "borderWidth": 1, "pointRadius": 0, "showLine": true, "fill": false, "tension": 0, "order": 100, "datalabels": { "display": false } } ], "currentParams": { "year": 2025, "week": 8, "seasonType": "regular", "team": "Alabama", "gameId": "401752738" } }; // Chart options (WordPress-safe) const chartOptions = { responsive: true, maintainAspectRatio: false, animation: { duration: 1 // Minimal animation to trigger layout calculation (fixes label positioning) }, elements: 'line' === 'line' ? 'win-probability'.includes('play-map') ? { line: { tension: 0, borderWidth: 0 } } : 'win-probability' === 'win-probability' ? { line: { tension: 0.15, borderWidth: 2.2, fill: false }, point: { pointRadius: 0, pointHoverRadius: 4 } } : { line: { tension: 0.25, borderWidth: 2.2 }, point: { pointRadius: 'win-probability'.includes('team-lines') ? 0 : undefined } } : {}, plugins: { datalabels: { display: function(context) { // Suppress data labels on line charts if ('line' === 'line') { return false; } return context.dataset.datalabels && context.dataset.datalabels.display === true; }, formatter: function(value, context) { // Special handling for Overall Team Performance chart if ('win-probability' === 'overall-team-performance' && context.dataset.label === 'Success Rate (SR)') { // Use the stored play count data if (context.dataset.playCountData && context.dataset.playCountData[context.dataIndex]) { return context.dataset.playCountData[context.dataIndex]; } // Fallback to percentage if play count data not available return Math.round(value * 100) + '%'; } // Handle bar charts with count data (play-type, quarter, down, etc.) if (context.dataset.label && context.dataset.label.includes(' SR') && (chartData.teamCounts || chartData.oppCounts)) { // Find the first team SR dataset in the chart to determine team order const allDatasets = context.chart.data.datasets; const teamSRDataset = allDatasets.find(d => d.label && d.label.includes(' SR') && !d.label.includes('NCAA')); // If this is the first team's SR dataset, use teamCounts if (teamSRDataset && context.dataset.label === teamSRDataset.label && chartData.teamCounts) { return chartData.teamCounts[context.dataIndex] || 0; } // Otherwise, use oppCounts for the second team else if (chartData.oppCounts) { return chartData.oppCounts[context.dataIndex] || 0; } } // For player charts, show value only if > 0 (matches non-embedded behavior) if ('win-probability'.includes('top-rushers') || 'win-probability'.includes('top-passers') || 'win-probability'.includes('top-receivers')) { // Hide data labels for zero or negative values, show actual value for positive values return value > 0 ? value : null; } // For other charts, show values based on type if (typeof value === 'number') { // If value is between 0 and 1, treat as percentage if (value >= 0 && value 0 ? '#26262660' : 'transparent'; }, borderColor: function(context) { const value = context.dataset.data[context.dataIndex]; return value > 0 ? 'rgba(255, 255, 255, 0.2)' : 'transparent'; }, borderRadius: 4, align: 'center', anchor: 'center' }, legend: 'win-probability' === 'win-probability' ? { display: false } : 'line' === 'line' ? { position: 'top', align: 'start', labels: 'win-probability'.includes('play-map') ? { usePointStyle: true, generateLabels: function(chart) { // Call the original generateLabels to get default styling const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter and customize each label const filteredLabels = labels.filter(label => { return !label.text.includes(' { const dataset = chart.data.datasets[label.datasetIndex]; if (dataset && dataset.label) { if (dataset.label.includes('Rush')) { label.pointStyle = 'circle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else if (dataset.label.includes('Pass')) { label.pointStyle = 'triangle'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } else { label.pointStyle = 'rect'; label.pointStyleWidth = 4; label.fillStyle = 'white'; } } }); return filteredLabels; }, boxWidth: 20, padding: 12 } : { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, generateLabels: function(chart) { const original = Chart.defaults.plugins.legend.labels.generateLabels; const labels = original.call(this, chart); // Filter out reference areas and ensure white fill const filteredLabels = labels.filter(label => { return !label.text.includes('NCAA Avg SR') && !label.text.includes('50/50') && !label.text.includes('Quarters'); }); // Ensure white fill for all line chart legend boxes filteredLabels.forEach((label) => { label.fillStyle = 'white'; }); return filteredLabels; } } } : { position: 'top', align: 'start', labels: { usePointStyle: false, boxWidth: 12, boxHeight: 12, padding: 12, filter: function(legendItem, chartData) { return !legendItem.text.includes('NCAA Avg SR') && !legendItem.text.includes('Quarters') && !legendItem.text.includes('50/50'); }, generateLabels: function(chart) { const data = chart.data; if (data.datasets.length) { return data.datasets.map((dataset, i) => { // Handle backgroundColor arrays (like in Overall Team Performance chart) let fillColor = dataset.backgroundColor; if (dataset.label === '# Plays') { fillColor = 'white'; } else if (Array.isArray(dataset.backgroundColor)) { // For datasets with backgroundColor arrays, use the first color for legend fillColor = dataset.backgroundColor[0]; } return { text: dataset.label, fillStyle: fillColor, strokeStyle: dataset.label === '# Plays' ? '#666' : dataset.borderColor, lineWidth: dataset.label === '# Plays' ? 1 : dataset.borderWidth, hidden: !chart.isDatasetVisible(i), datasetIndex: i }; }).filter((item, index) => { // Apply the same filter logic as above const dataset = chart.data.datasets[index]; if (!dataset || !dataset.data) return false; if (dataset.label === '# Plays') return true; // Always show # Plays if (dataset.label && (dataset.label.includes('NCAA Avg SR') || dataset.label.includes('Quarters') || dataset.label.includes('50/50'))) return false; return dataset.data.some((value) => value > 0); }); } return []; } } }, tooltip: 'win-probability' === 'win-probability' ? { mode: 'index', intersect: false, callbacks: { title: function(tooltipItems) { if (tooltipItems && tooltipItems[0]) { return 'Play ' + (tooltipItems[0].dataIndex + 1); } return ''; }, label: function(context) { const selectedTeamWinProb = context.parsed.y; const opponentWinProb = 100 - selectedTeamWinProb; const selectedTeam = context.dataset.selectedTeam || 'Team'; const opponentTeam = context.dataset.opponentTeam || 'Opponent'; return [ selectedTeam + ': ' + selectedTeamWinProb.toFixed(1) + '%', opponentTeam + ': ' + opponentWinProb.toFixed(1) + '%' ]; }, afterLabel: function(context) { if (context.dataset.playTexts && context.dataset.playTexts[context.dataIndex]) { return '\n' + context.dataset.playTexts[context.dataIndex]; } return ''; } } } : { filter: function(tooltipItem) { if ('win-probability'.includes('play-map')) { return !tooltipItem.dataset.label.includes('< 0') && !tooltipItem.dataset.label.includes('Quarters') && !tooltipItem.dataset.label.includes('Drive'); } return !tooltipItem.dataset.label.includes('NCAA Avg SR') && !tooltipItem.dataset.label.includes('50/50') && !tooltipItem.dataset.label.includes(' ds.label === 'Win Probability'); if (wpDataset && wpDataset.segmentColors) { wpDataset.segment = { borderColor: function(ctx) { // Use p1DataIndex (ending point) so the line inherits the destination color // This makes momentum shifts more visually intuitive const index = ctx.p1DataIndex; if (index !== undefined && wpDataset.segmentColors[index]) { return wpDataset.segmentColors[index]; } return wpDataset.borderColor || '#8B0000'; } }; } } // Initialize the chart const ctx = canvas.getContext('2d'); const chart = new Chart(ctx, { type: 'line', data: chartData, options: chartOptions }); // Store reference to prevent re-initialization canvas.chartInstance = chart; console.log('CFB Chart initialized successfully'); } catch (error) { console.error('Error initializing CFB chart:', error); // Fallback: show error message in canvas container const container = document.getElementById('cfb-chart-1760899481447-kssa83twj').parentNode; if (container) { container.innerHTML = '

Chart failed to load. Please refresh the page.

'; } } } // Start loading scripts sequentially function startLoading() { // First, check if scripts are already loaded (multiple embeds on same page) if (typeof Chart !== 'undefined' && typeof ChartDataLabels !== 'undefined') { initChart(); return; } // Load Chart.js first if (typeof Chart === 'undefined') { loadScript('https://cdn.jsdelivr.net/npm/chart.js@3.9.1/dist/chart.min.js', function() { // Then load ChartDataLabels if (typeof ChartDataLabels === 'undefined') { loadScript('https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2.2.0', function() { initChart(); }); } else { initChart(); } }); } else if (typeof ChartDataLabels === 'undefined') { // Chart.js loaded but not ChartDataLabels loadScript('https://cdn.jsdelivr.net/npm/chartjs-plugin-datalabels@2.2.0', function() { initChart(); }); } else { initChart(); } } // Initialize when DOM is ready if (document.readyState === 'loading') { document.addEventListener('DOMContentLoaded', startLoading); } else { startLoading(); } })();

You can definitely see the 99-yard pick-6 here going into halftime — though, weirdly, it produced only a 16% swing in win probability. And we’ve got the Vols’ big plays in the 2nd quarter making things interesting (ahem, “interesting”) there for a bit.

But otherwise, these numbers were surprisingly cheery for the Tide. That Vols’ second quarter gave them only a few plays on their half of the win probability chart, but otherwise Alabama was living in the >70% probability area the whole game. It even put us near 100% going into the 4th quarter!

You can see some weirdness here and there in the chart, when individual plays might have puzzling effects on the win probability. I’m still learning about how this type of data responds to events (and I remain at least a little skeptical and hesitant to write these up). But I double checked this against the ESPN model and theirs is even more optimistic on the Tide this whole game. What a bunch of Gumps!

Anyway, Roll Tide, congrats on a huge rivalry win, and enjoy your cigar hangover. (Maybe go outside and get some extra oxygen today to make up for it). All of the charts from this game are here.