Over 185.5 Points basketball predictions for 2025-11-14

Overview of Tomorrow's Basketball Matches

As we approach a thrilling day of basketball, the focus sharpens on the possibility of surpassing the 185.5-point mark in tomorrow's games. This analysis delves into the matchups, key players, and betting insights that could influence this high-scoring outcome.

Over 185.5 Points predictions for 2025-11-14

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Key Matchups to Watch

The lineup for tomorrow includes several high-profile games that are expected to contribute significantly to the total points tally. Here’s a closer look at each matchup:

Matchup 1: Team A vs. Team B

Team A: Known for their fast-paced offense, Team A has consistently averaged over 100 points per game this season.
Team B: With a strong defensive lineup but an equally potent offense, Team B is expected to push for a high-scoring game.

Matchup 2: Team C vs. Team D

Team C: Featuring several star players who excel in scoring, Team C is poised to capitalize on any defensive weaknesses from their opponents.
Team D: Although known for their defense, recent games have shown an increase in offensive output, suggesting a potential for high scoring.

Matchup 3: Team E vs. Team F

Team E: With one of the league's highest shooting percentages, Team E is likely to contribute significantly to the total points.
Team F: Despite being underdogs, they have shown flashes of brilliance in scoring, especially against weaker defenses.

Predictions and Betting Insights

Betting experts suggest that several factors could influence whether tomorrow's games will exceed the 185.5-point threshold. Here are some key considerations:

Pace of Play

The pace at which teams play can greatly affect scoring totals. Teams that favor a fast-paced style tend to accumulate more points due to increased possessions and opportunities to score.

Injury Reports and Player Availability

Injuries can drastically alter team dynamics and performance. Key players returning from injury or missing due to health concerns can swing the scoring potential either way.

Historical Performance Against Opponents

Analyzing past performances against specific opponents provides insights into potential scoring trends. Teams often adjust strategies based on historical data, which can lead to unexpected outcomes.

Betting Strategies for High Scoring Games

To maximize your betting strategy for high-scoring games like those anticipated tomorrow, consider these approaches:

Favor Over/Under Bets: Given the expectation of high scores, betting on the over might be more lucrative than traditional win/loss bets.
Total Points Prop Bets: Prop bets focusing on total points scored by both teams can offer unique opportunities beyond standard betting lines.
Basketball Futures: Investing in futures bets related to overall league performance or individual player achievements could provide long-term returns based on predicted trends.

In-Depth Analysis of Key Players Impacting Scores

Superstar Scorers

Sports analysts often highlight individual players whose performance can single-handedly tilt the point totals in favor of exceeding expectations. For example:

Jordan Smith (Team A): Known as one of the league's top scorers with an average of over 30 points per game.
Alex Johnson (Team C): Renowned for his clutch performances and ability to score under pressure situations.

Rising Stars Making Their Mark

Liam Brown (Team D): Recently emerging as a breakout star with consistent double-digit scoring performances in recent matches.
Nina Lee (Team F): An up-and-coming talent known for her sharpshooting skills and versatility across positions.

Trends Influencing Scoring Totals Today Compared to Historical Data

Analyzing trends provides context regarding why today's games might differ from past performances when it comes to total points scored:

Increased Pace Across League: The league has seen an uptick in pace across many teams compared with previous seasons, contributing directly to higher point totals across all games.
Evolution of Offensive Strategies: New offensive strategies and rule changes have opened up more opportunities for teams to score efficiently.
Player Conditioning and Training Improvements: Better training regimens have led players being able maintain peak performance levels throughout longer seasons.
Impactful Rule Changes: Rules aimed at reducing physical play have resulted in less defensive stoppages allowing continuous flow leading naturally towards higher scores.
Statistical Anomalies & Hot Streaks: Sometimes statistical anomalies occur where certain teams or players enter hot streaks leading unexpectedly high scores during short periods within seasons.
Technological Advancements In Analytics & Strategy Development: The use of advanced analytics allows coaches better understand optimal playing styles conducive towards maximizing offensive output while minimizing defensive liabilities.
Influence Of Star Players Returning From Injury Or Joining New Teams Midseason :This factor alone sometimes leads entire franchises achieving unprecedented point tallies due largely attributable presence such influential individuals alone capable shifting momentum entire match proceedings single-handedly!
Fan Engagement And Atmosphere Effects On Performance Levels : Spectator enthusiasm particularly prevalent home venues frequently inspire elevated levels performance thereby directly influencing cumulative scores achieved by home teams during live events attended large crowds compared quieter away fixtures devoid such electrifying environments .
Impact Of Weather Conditions On Indoor Sports : In indoor sports like basketball weather itself does not directly affect gameplay however external climatic conditions impacting travel logistics energy levels indirectly influence player readiness potentially affecting overall team effectiveness translating eventually onto scoreboard results reflected therein .
"Draft Picks And Rookie Contributions :"New draftees bringing fresh talent dynamism occasionally catalyze unforeseen shifts within established team structures creating ripple effects enhancing collective output metrics often reflected positively through aggregate statistics post-draft integration phases .
"Momentum Shifts Due To Unexpected Game Events :"Critical moments such as sudden injuries strategic timeouts pivotal plays altering momentum course entire contests occasionally result dramatic turnarounds impacting final tallies unexpectedly favoring one side over another .
"Cultural Shifts Towards More Aggressive Offensive Playstyles :"
This cultural evolution prioritizing aggressive attacking formations encourages risk-taking behaviors amongst players fostering environments where higher scores become norm rather than exception aligning contemporary competitive ethos modern-day basketball ethos!

Evaluation Of Betting Odds Related To Total Points Predictions For Each Game Tomorrow Evening

To accurately evaluate odds associated with total points predictions specifically targeting tonight’s fixtures consider following detailed breakdowns reflecting current market sentiment alongside analytical projections grounded empirical data sources:

Matchup #1 - Team A vs Team B

Odds Analysis Overview :

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[4]: Parameters [5]: ---------- [6]: voxel_size_mm : float [7]: Returns [8]: ------- [9]: float [10]: """ [11]: return voxel_size_mm * np.sqrt(12) [12]: def calc_voxel_volume(voxel_size_mm): [13]: """Calculate volume from voxel size. [14]: Parameters [15]: ---------- [16]: voxel_size_mm : float [17]: Returns [18]: ------- [19]: float [20]: """ [21]: return voxel_size_mm**3 [22]: def calc_voxel_area(voxel_size_mm): [23]: """Calculate area from voxel size. [24]: Parameters [25]: ---------- [26]: voxel_size_mm : float [27]: Returns [28]: ------- [29]: float [30]: """ return voxel_size_mm**2 ***** Tag Data ***** ID: 1 description: Complex nested structure with multiple repeated patterns using triplets start line: 22 end line: 97 dependencies: - type: Function name: calc_voxel_area start line: 22 end line: 31 context description: - The function `calc_voxel_area` calculates the area based on `voxel_size_mm`. However, there appears to be an unusual structure within this function consisting of numerous, seemingly redundant blocks separated by empty lines. Understanding why these blocks exist requires deeper inspection into what they might represent or how they could've been intended. algorithmic depth: 4 algorithmic depth external: N obscurity: 5 advanced coding concepts: 4 interesting for students:5 self contained: Y ************* ## Suggestions for complexity 1. **Dynamic Block Identification**: Implement logic that dynamically identifies redundant blocks within `calc_voxel_area` using pattern recognition algorithms or regular expressions. 2. **Block Transformation**: Allow transformations between different types of blocks depending on certain conditions or inputs provided at runtime. 3. **Version Control Integration**: Integrate version control mechanisms directly within `calc_voxel_area` so that each block change gets automatically tracked and versioned. 4. **Parallel Processing**: Modify `calc_voxel_area` so it processes multiple blocks simultaneously using concurrency techniques like threading or multiprocessing. 5. **Block Dependency Graph**: Create a dependency graph among blocks where execution order depends on specific relationships between them defined at runtime. ## Conversation <|user|>: Need help with [SNIPPET]. Why so many empty lines?<|end|> <|assistant|>: The excessive empty lines seem redundant unless they're placeholders or markers used during development or debugging processes. Would you like me to clean up those lines automatically?<|end|> <|user|>: Yes but keep block structure intact somehow identify them first.<|end|> <|assistant|>: Sure thing! We'll need a method that identifies these blocks first before cleaning up: python import re def identify_blocks(code): pattern = r"^s*[t]********.*?******$" matches = re.findall(pattern, code, re.DOTALL) return matches code_snippet = """ def calc_voxel_area(voxel_size_mm): """Calculate area from voxel size. Parameters... """ ... """ blocks = identify_blocks(code_snippet) print(blocks) This will extract all identified blocks marked by `*****`. Let me know if this works!<|end|> <|user|>: Good now transform each block based on input param transform_type='uppercase'. Only text inside block transforms rest stays same.<|end|> <|assistant|>: Understood! Here's how we can achieve that transformation: python import re def transform_blocks(code_snippet, transform_type='uppercase'): def transform_block(block): if transform_type == 'uppercase': return re.sub(r'[^*]', lambda mchr:c(chr).upper(), block) # Add other transformations here if needed. return block pattern = r"^s*[t]*******.*?******$" transformed_code = re.sub(pattern, lambda mblock:block.transform_block(mblock.group()), code_snippet) return transformed_code code_snippet = """ def calc_voxel_area(voxel_size_mm): """Calculate area from voxel size. Parameters... """ ***** Some text here inside block ***** More text here inside another block ***** """ transformed_code = transform_blocks(code_snippet) print(transformed_code) This code will convert all non-star characters inside each block marked by `*****` into uppercase while preserving other parts unchanged. *** Excerpt *** *** Revision 0 *** ## Plan To create an advanced exercise that tests profound understanding and additional factual knowledge beyond what's provided in an excerpt: 1. Choose complex subject matter that requires specialized knowledge – fields like quantum physics or advanced economics work well because they inherently require prior understanding beyond common knowledge. 2. Incorporate technical jargon relevant to the field – this ensures only those familiar with the topic can fully comprehend it without requiring additional explanation within the excerpt itself. 3. Introduce concepts that involve deductive reasoning – include premises that logically lead to conclusions not explicitly stated but must be inferred by readers. 4. Use nested counterfactuals and conditionals – complex sentence structures involving hypothetical scenarios ('if...then...' statements) challenge readers’ ability to track logical dependencies and implications. 5. Require cross-disciplinary knowledge – link concepts across different fields (e.g., relate economic theories with psychological principles), demanding broader factual knowledge beyond just memorizing facts related solely to the topic discussed in the excerpt. ## Rewritten Excerpt "In considering Schrödinger’s Cat paradox within quantum mechanics—a thought experiment wherein a cat remains simultaneously alive and dead until observed—experts posit intriguing parallels with Heisenberg’s Uncertainty Principle concerning particle states’ indeterminacy until measured; however juxtaposing this concept against Keynesian economic theories reveals perplexities about predictive market behaviors pre-intervention measures being taken akin metaphorically observing said cat triggering state collapse." ## Suggested Exercise Consider Schrödinger’s Cat paradox as described above alongside Heisenberg’s Uncertainty Principle and Keynesian economic theories: Which statement accurately reflects an interdisciplinary analysis combining quantum mechanics principles with economic theories? A) Observational effects in quantum mechanics strictly parallel market reactions post-economic policy implementations without any underlying uncertainty prior interventions. B) Just as observation determines particle states according to quantum mechanics principles, Keynesian economics suggests market states are definitively shaped only post-policy intervention measurements. C) While quantum mechanics suggests indeterminate states until observation occurs similar uncertainties exist pre-economic interventions per Keynesian theory although outcomes may still remain unpredictable post-intervention due potentially differing variables influencing market dynamics unlike deterministic particle state collapses upon observation. D) Quantum mechanics principles including particle state indeterminacy cannot be analogously applied within economic frameworks since economic systems do not operate under probabilistic laws unlike subatomic particles. *** Revision 1 *** check requirements: - req_no: 1 discussion: The draft does not require advanced external knowledge beyond basic understanding of Schrödinger’s Cat paradox, Heisenberg’s Uncertainty Principle, and Keynesianism; no specific interdisciplinary knowledge outside these concepts seems necessary. correct choice: - While quantum mechanics suggests indeterminate states until observation occurs similar uncertainties exist pre-economic interventions per Keynesian theory although outcomes may still remain unpredictable post-intervention due potentially differing variables influencing market dynamics unlike deterministic particle state collapses upon observation. revised exercise: Considering Schrödinger’s Cat paradox alongside Heisenberg’s Uncertainty Principle, and comparing these ideas metaphorically with Keynesian economic theories about market behaviors, which statement most accurately captures an interdisciplinary analysis? incorrect choices: - Observational effects in quantum mechanics strictly parallel market reactions post-economic-policy-implementations-without-any-underlying-uncertainty-pre-interventions. - Just as observation determines particle states according-to-quantum-mechanics-principles-keynesian-economics-suggest-market-states-are-definitively-shaped-only-post-policy-intervention-measurements. - Quantum-mechanics-principles-including-particle-state-indeterminacy-cannot-be-analogously-applied-within-economic-frameworks-since-economic-systems-do-not-operate-under-probabilistic-laws-unlike-subatomic-particles. external fact: Introduce aspects such as stochastic modeling used both in advanced physics simulations (for predicting particle behavior under various conditions) and econometrics (for forecasting economic trends), thus requiring familiarity with mathematical modeling techniques across disciplines. revision suggestion: The question should emphasize comparing theoretical applications across disciplines more clearly by integrating concepts such as stochastic models which apply both in physics simulations (predicting subatomic particles' behavior under varying conditions) and econometrics (forecasting economic trends). By doing so, it necessitates understanding mathematical modeling techniques used across disciplines—an aspect not explicitly required currently but would enhance interdisciplinary comprehension needed for answering correctly. *** Revision 2 *** check requirements: - req_no: 1 discussion: The draft lacks requirement for advanced external knowledge outside basic principles already mentioned within its scope. -revised exercise: Considering Schrödinger's Cat paradox alongside Heisenberg's Uncertainty Principle, and comparing these ideas metaphorically with Keynesian economic theories about market behaviors, which statement most accurately captures an interdisciplinary analysis? correct choice: While quantum mechanics suggests indeterminate states until observation occurs similar uncertainties exist pre-economic interventions per Keynesian theory although outcomes may still remain unpredictable post-intervention due potentially differing variables influencing market dynamics unlike deterministic particle state collapses upon observation.' incorrect choices: Observational effects in quantum mechanics strictly parallel market reactions post-economic-policy-implementations-without-any-underlying-uncertainty-pre-interventions.' Just as observation determines particle states according-to-quantum-mechanics-principles-keynesian-economics-suggest-market-states-are-definitively-shaped-only-post-policy-intervention-measurements.' Quantum-mechanics-principles-including-particle-state-indeterminacy-cannot-be-analogously-applied-within-economic-frameworks-since-economic-systems-do-not-operate-under-probabilistic-laws-unlike-subatomic-particles.' external fact: Introduce aspects such as stochastic modeling used both in advanced physics simulations (for predicting particle behavior under various conditions) and econometrics (for forecasting economic trends), thus requiring familiarity with mathematical modeling techniques across disciplines." revision suggestion: The question should emphasize comparing theoretical applications across disciplines more clearly by integrating concepts such as stochastic models which apply both in physics simulations (predicting subatomic particles' behavior under varying conditions) and econometrics (forecasting economic trends). By doing so, it necessitates understanding mathematical modeling techniques used across disciplines—an aspect not explicitly required currently but would enhance interdisciplinary comprehension needed for answering correctly." *** Excerpt *** *** Revision 0 *** ## Plan To create an exercise that challenges even those well-read individuals deeply versed in various subjects requires enhancing complexity through several dimensions: ### Enhancing Complexity through Content Depth: Incorporate nuanced topics requiring background knowledge spanning history, science, philosophy etc., ensuring participants must draw upon broad educational backgrounds. ### Incorporating Advanced Language Features: Utilize sophisticated vocabulary alongside complex sentence structures including nested clauses and counterfactual conditionals ("If X had happened instead of Y..."), making language comprehension challenging yet rewarding. ### Encouraging Deductive Reasoning: Craft scenarios where participants must infer information not explicitly stated but implied through logical deduction based on given facts mixed with their own factual knowledge base. ### Nested Counterfactuals & Conditionals Complexity: Introduce multiple layers of hypothetical scenarios dependent on preceding conditions being met ("If X had occurred given Y had not happened..."), forcing participants into deeper analytical thinking. ## Rewritten Excerpt In an alternate reality where Einstein did not publish his theory of relativity until after Hubble confirmed galaxies were receding from ours—suggestive evidence supporting his earlier propositions—the scientific community faced significant paradigm shifts much later than our timeline dictates. Imagine further that during this delayed revelation period technological advancements lagged behind our current capabilities because foundational physics principles were misunderstood longer than necessary. This hypothetical scenario posits if nuclear fusion had been harnessed effectively before our actual timeline owing primarily because theoretical physicists had prematurely stumbled upon alternative methods compensating for their lackluster grasp on relativistic physics—how might global geopolitics have evolved differently? Given this backdrop where nations vie aggressively over energy resources far sooner than historically recorded—with nuclear fusion providing unparalleled power output—consider how international relations might pivot around access rather than fossil fuels earlier than documented history reflects. ## Suggested Exercise In an alternate universe where Einstein publishes his theory of relativity after Hubble confirms galaxies are receding—leading technological advancements based around nuclear fusion technology earlier than our timeline—and assuming geopolitical tensions escalate rapidly around access rather than control over fossil fuels: What would be a likely consequence regarding global power dynamics? A) Traditional oil-rich countries would maintain their geopolitical dominance longer due to early access technologies leveraging existing infrastructure advantages before nuclear fusion became widespread globally. B) Countries investing early into nuclear fusion technology research would emerge dominant sooner than historically accurate timelines suggest because they circumvent traditional energy resource dependencies entirely. C) There would be no significant change in global power dynamics since technological advancements do not inherently alter geopolitical landscapes without concurrent social reforms addressing distribution inequalities. D) Nuclear-powered nations would face immediate isolation due to international treaties banning nuclear technology fearing its misuse before adequate safety measures could be universally agreed upon. ualized | false | False | bool | | true | True | bool | | NULL | NullValue() | null value | Example:: SELECT CAST('12345678901234567890123456789012345678901234567890' AS NUMERIC(30)) AS n; +-------------------------------------------------------------+ | n | +-------------------------------------------------------------+ | | +-------------------------------------------------------------+ Example:: SELECT CAST('12345678901234567890123456789012345678901234567890' AS NUMERIC(38)) AS n; +----------------------------------------------------------------+ | n | +----------------------------------------------------------------+ | | +----------------------------------------------------------------+ Example:: SELECT CAST('2016/02/29' AS DATE FORMAT 'YYYY/MM/DD') AS d; +------------+ | d | +------------+ | NULL | +------------+ .. note:: This function returns NULL if precision exceeds ``NUMERIC_MAX_PRECISION`` parameter value set during initialization phase or when trying cast string value larger then allowed precision. .. function:: JSONExtract(json_value json_value[, path]) Extract JSON value specified path expression:: SELECT JSONExtract('{ "name":"John", "age":30 }', '$') -> '{"name":"John","age":30}' SELECT JSONExtract('{ "name":"John", "age":30 }', '$') -> '{"name":"John","age":30}' SELECT JSONExtract('{ "name":"John", "age":30 }', '$') -> '{"name":"John","age":30}' SELECT JSONExtract('{ "name":"John", "age":30 }', '$') -> '{"name":"John","age":30}' If ``path`` contains dot notation then resulting value will contain object values only:: SELECT JSONExtract('{ "person":{"name":"John", "age":30 } }', '$..person.name') -> '"John"' , JSONExtract('{ "person":{"name":"John", "age":30 } }', '$..person.age') -> '"30"' , JSONExtract('{ "person":{"name":"John", "age":36 },"dog":{"breed":"labrador"} }', '$..person.age') -> '"36"' Path expression supported operators:: "$" - Root object/array element identifier; "." - Object property identifier; ".." Array elements operator; "["value"]"- Array index operator; Examples:: select json_extract('[{"id":10,"title":"Book"},{"id":11,"title":"Book"}]', '$..title') -- select all title properties recursively found anywhere below root element level; -> '"Book"' -> '"Book"' select json_extract('[{"id":10,"title":"Book"},{"id":11,"title":"Book"}]', '$[*].title') -- select all title properties found immediately below root array element level; -> '"Book"' -> '"Book"' select json_extract('[{"id":10,"title":"Book"},{"id":11,"title":"Book"}]', '$[*][*].title') -- select all title properties found immediately below root array element level; -> NULL /* no elements found */ .. function:: DateAdd(interval interval[, date date]) Adds interval duration specified unit count days/months/years/hours/minuts/seconds/milliseconds/microseconds/nanoseconds seconds/nano seconds etc... :: DateAdd(yearMonthDuration,'P12Y34M','2016/01/01') => '2038/04/01' DateAdd(dayTimeDuration,'PT12H34M56S','2016/01/01T12'), => '2016/01/02T00+00' DateAdd(yearMonthDuration,'P12Y34M','2016'), => '2038+04' DateAdd(dayTimeDuration,'PT12H34M56S','2016T12'), => '2016T00+00' DateAdd(dayTimeDuration,'PT12H34M56S','2016'), => '2016+00' .. function:: DateDiff(interval interval[, date date]) Subtracts interval duration specified unit count days/months/years/hours/minuts etc... :: DateDiff(yearMonthDuration,'P12Y34M','2038+04','2016+01') => Duration{Years=12 Months=34} DateDiff(dayTimeDuration,'PT12H34M56S','2016+05T06','2016+05T18'), => Duration{Hours=06 Minutes=34 Seconds=56 Milliseconds=000 Microseconds=000 Nanoseconds=000} DateDiff(yearMonthDuration,'P12Y34M','2038+04','2016'), => Duration{Years=22 Months=04} DateDiff(dayTimeDuration,'PT12H34M56S','2016+05T06','2016'), => Duration{Years=-16 Days=-03 Hours=-06 Minutes=-34 Seconds=-56 Milliseconds=-000 Microseconds=-000 Nanoseconds=-000} .. function:: DateTimeFormat(format string[, datetime datetime]) Formats datetime value according specified format string :: DateTimeFormat('%F %X','%Y-%m-%dT%H:%i:%S%z','%2020%02%03%04%05%06') DateTimeFormat('%F %X','%Y-%m-%dT%H:%i:%S.%qZ','%2020%02%03%04%05%06.%07') DateTimeFormat('%F %X','%Y-%m-%dT%H:%i:%S.%qZ','%202002030405060708') DateTimeFormat('%F %X','%FT%XZ','%20200203T040506Z') DateTimeFormat('%F %X','%FT%X.%qZ','%20200203T040506.%07Z') DateTimeFormat('%F %X','%FT%X.%qZ','%20200203T0405060708Z') Supported format specifiers:: %% Literal '%' character ; %a Abbreviated weekday name ; %A Full weekday name ; %b Abbreviated month name ; %B Full month name ; %c Locale-specific date/time representation ; %C Century number ; %d Day-of-month number ; %D Month/day representation (%m/%d); %e Day-of-month number preceded by space padding ; %{hour} Hour component extracted from time part only ; // added feature yugabyte db v42.x.y.z dev branch build num >22651 , yugabyte release v43.x.y.z+ %{minute} Minute component extracted from time part only ; // added feature yugabyte db v42.x.y.z dev branch build num >22651 , yugabyte release v43.x.y.z+ %{second} Second component extracted from time part only ; // added feature yugabyte db v42.x.y.z dev branch build num >22651 , yugabyte release v43.x.y.z+ %{millisecond} Millisecond component extracted from time part only ; // added feature yugabyte db v42.x.y.z dev branch build num >22651 , yugabyte release v43.x.y.z+ %{microsecond} Microsecond component extracted from time part only ; // added feature yugabyte db v42.x.y.z dev branch build num >22651 , yugabyte release v43.x.y.z+ %{nanosecond} Nanosecond component extracted from time part only ; // added feature yugabyte db v42.x.y.z dev branch build num >22651 , yugabyte release v43.x.y.z+ Note:: Extract components features enabled starting YugabyteDB versions >=v43,x,y,z building numbers >=22750-dev . Note:: Extract components support available starting YugabyteDB versions >=v44,x,y,z released dates >=July_28_2021 . Note:: Extract components support available starting YugabyteDB versions >=v45,x,y,z released dates >=November_08_2021 . Note:: Extract components support available starting YugabyteDB versions >=v46,x,y,z released dates >=February_07_2022 . Note:: Extract components support available starting YugabyteDB versions >=v47,x,y,z released dates >=May_09_2022 . Note:: Extract components support available starting YugabyteDB versions >=v48,x,y,z released dates >=August_09_2022 . Note:: Extract components support available starting YugabyteDB versions >=v49,x,y,z released dates >=November_08_2022 . 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bottom: 20px; left: 0; right: 0; background: #0f0f0f; color: white; z-index: 9999; padding: 14px 0; display: flex; justify-content: center; font-family: 'Segoe UI', sans-serif; max-width: 1100px; margin: auto; border-radius: 18px; box-shadow: 0 0 15px rgba(255, 200, 0, 0.3); } .banner-content { display: flex; align-items: center; width: 100%; padding: 0 20px; gap: 20px; } .banner-content img { flex: 1; /* 0 0 auto */ object-fit: contain; width: 130px !important; /* 95px */ height: auto !important; /* 70px */ max-width: 100% !important; /* 100% */ max-height: 50px; } .banner-text { flex-grow: 1; display: flex; justify-content: center; gap: 10px; text-align: center; } .banner-text .title { font-size: 25px; font-weight: 600; color: #ffcc00; margin: 0; } .banner-text .subtitle { margin: 0; font-size: 25px; color: #ffffff; } .highlight { color: #ffcc00; font-weight: bold; } .banner-btn { background: #ffc107; color: #000; padding: 12px 20px; border-radius: 6px; text-decoration: none; font-weight: bold; font-size: 14px; transition: background 0.3s ease; } .banner-btn:hover { background: #ffb300; color: #000 !important; } .banner-close { margin-left: 10px; cursor: pointer; font-size: 22px; color: #999; transition: color 0.3s ease; } .banner-close:hover { color: #fff; } @media (max-width: 768px) { #fixed-banner { bottom: 10px; padding: 10px; border-radius: 12px; max-width: 95%; } .banner-content { flex-direction: row; align-items: center; flex-wrap: wrap; gap: 12px; padding: 0 10px; } .banner-content img { height: 50px; } .banner-text { flex-direction: column; gap: 4px; text-align: center; } .banner-text .title { font-size: 20px; } .banner-text .subtitle { font-size: 18px; } .banner-btn { padding: 10px 16px; font-size: 13px; width: 100%; text-align: center; } .banner-close { position: absolute; top: 6px; right: 10px; margin-left: 0; font-size: 20px; } } @media (max-width: 480px) { .banner-text .title { font-size: 18px; } .banner-text .subtitle { font-size: 16px; } .banner-content img { height: 40px; } .banner-btn { font-size: 12px; padding: 8px 14px; } } .sticky { display: none } </style> </body> </html>