Moneyline betting represents one of the most fundamental forms of sports wagering, offering a straightforward proposition: selecting the outright winner of a contest. Unlike spread betting, the margin of victory is irrelevant; the chosen team or individual simply needs to win the event. Odds for moneyline bets are typically presented in the American format, where a negative number (e.g., -150) indicates the favorite and the amount a bettor must wager to win $100. Conversely, a positive number (e.g., +130) signifies the underdog and the potential profit from a $100 stake. The team assigned negative odds is designated the “favorite,” implying a higher statistical probability of winning, though this comes with a correspondingly lower payout relative to the stake.
This report aims to quantify the historical win percentage of these moneyline favorites, as designated by the general sports betting market (often colloquially referred to as “Vegas sportsbooks”), across four major North American professional sports leagues: Major League Baseball (MLB), the National Basketball Association (NBA), the National Football League (NFL), and the National Hockey League (NHL). Furthermore, this analysis will endeavor to provide a combined favorite win percentage across these leagues. Throughout this examination, a commitment to the highest possible accuracy based on available data will be maintained, with all methodological assumptions explicitly detailed.
It is important to establish at the outset that the concept of sportsbook “accuracy” in selecting favorites is not solely a measure of predictive prowess. Sportsbooks operate under a business model designed to balance wagers on either side of a contest, thereby minimizing their risk, and to generate revenue through a commission known as the “vigorish” or “vig.” As one source notes, “The Las Vegas odds makers are not trying to pick winners. They are trying to predict outcomes… to give all bettors a 50/50 chance of winning… balancing the book”. Consequently, the win percentages observed are as much a reflection of market dynamics and risk management as they are of pure predictive skill.
The odds set by sportsbooks inherently carry an “implied probability” for each potential outcome of an event. For instance, moneyline odds of -200 suggest an implied win probability of 66.7% for the favorite. A central component of this report involves comparing such implied likelihoods (particularly for favorites) against their actual historical win rates. This distinction is crucial: sportsbook odds function as a market price for a given outcome, reflecting supply, demand, and the sportsbook’s margin, rather than serving as a pure, unbiased probabilistic forecast. The “accuracy” figures presented herein refer to the actual frequency with which the market-designated favorite wins the contest.
Furthermore, the “vig” is an omnipresent factor in sportsbook operations. This commission, typically a few percentage points, is embedded within the odds structure and ensures that sportsbooks achieve a positive return over a large volume of bets, irrespective of their “accuracy” on any individual game. A practical consequence of the vig is that the sum of implied probabilities for all possible outcomes of an event will invariably exceed 100%. This operational reality means that the favorite win percentages analyzed in this report are derived from market-set odds that already account for this built-in sportsbook advantage. The accuracy of sportsbooks, therefore, must be understood within the context of a system engineered for their sustained profitability.
In the National Football League, moneyline favorites have historically demonstrated a consistent ability to win outright. Analysis of extensive data from Bet Labs, as cited by BetMGM, covering six full seasons since the broader legalization of online sports betting in the United States (following the 2018 Supreme Court decision), indicates that NFL moneyline favorites with closing lines of -115 or shorter achieved a win-loss-tie record of 1013-508-7. This translates to a 66.6% win percentage. This figure provides a robust benchmark for understanding sportsbook efficacy in identifying likely NFL game winners.
The data exhibits some year-to-year variation, though the overall trend remains stable. For example, during the 2023 season, favorites at -115 or shorter recorded 181 wins against 85 losses, equating to a 68% win rate. In the preceding 2022 season, similarly defined favorites posted a record of 175-88-2, for a 66.5% win rate. These slight fluctuations are expected in sports outcomes but do not detract from the longer-term average.
There is a well-documented relationship between the point spread assigned to an NFL game and the subsequent moneyline win probability of the favorite. As the point spread increases (i.e., the favorite is expected to win by a larger margin), their historical win rate on the moneyline also tends to rise. For instance, NFL favorites with point spreads of 10 points or more have historically won over 80% of their games. More specifically, a team favored by 7 points has demonstrated a win rate of approximately 76.8%. This illustrates that sportsbook “accuracy” is not uniform across all games but is dynamically related to the perceived disparity in team strength.
The primary data for this NFL analysis originates from Bet Labs and encompasses the 2018 through 2023 seasons. A critical aspect of this dataset is its reliance on “closing lines”—the final odds offered just before a game commences. These closing lines are widely regarded in the sports betting industry as the most efficient and accurate reflection of true probabilities. This enhanced accuracy stems from the market having had ample time to process all available information, including injury updates, weather conditions, and, crucially, the influence of wagers from sophisticated or “sharp” bettors. The use of closing lines therefore lends substantial credibility to the 66.6% win percentage, suggesting it is a strong measure of market-settled favorite win probability. This implies that the predictive capacity of sportsbook lines tends to refine as game time approaches.
Several assumptions underpin this NFL analysis. Firstly, it is assumed that the data aggregated by Bet Labs, which covers major sportsbooks, is representative of the broader “Vegas sportsbook” market. Secondly, the filter applied to the data—considering only favorites with odds of -115 or shorter—is assumed to capture a significant and representative majority of all moneyline favorites. While this filter excludes very slight favorites (e.g., those at -105 or -110), its impact on the overall percentage is likely minor, though it signifies that the data does not encompass every instance of a designated favorite. This could mean the 66.6% figure is marginally different (potentially slightly higher, as stronger favorites are more consistently included) than if all designated favorites were counted. Finally, this report focuses on “accuracy” as the actual win rate, distinct from betting profitability. Indeed, the same source indicating the 66.5% win rate for favorites in 2022 also noted that systematically betting on every favorite would have resulted in a negative 3% return on investment (ROI). This underscores a vital point: a high win rate for sportsbook-designated favorites does not inherently translate to profitability for bettors, primarily due to the compressed payouts offered on such wagers.
For the National Basketball Association, an extensive dataset covering over 28,000 games provides a strong foundation for assessing the historical win percentage of moneyline favorites. A weighted average calculation based on this data, which accounts for the number of games played at each specific point spread, indicates that NBA moneyline favorites have won approximately 66.43% of the time. The timeframe for these 28,000+ games is not explicitly detailed in the source material, but the sheer volume of data suggests a robust historical sample.
Similar to the NFL, the NBA data reveals a clear positive correlation between the magnitude of the point spread (favoring one team) and the actual win percentage of that favorite. As the point spread increases (represented by a more negative line for the favorite), the favorite’s win percentage (Fav Win %) also systematically increases. This trend is evident across the spectrum of spreads, ranging from a 49.05% win rate for a team favored by a mere -1 point, up to a 95.33% win rate for a team heavily favored by -15.5 points. This demonstrates that sportsbook odds effectively scale with the perceived difference in team quality. Supporting the general reliability of such market data, an academic study analyzing betting markets from 2006-2016, including the NBA, found no evidence that the probabilities implied by betting market data were biased or inaccurate in reflecting game outcomes, thus affirming the efficiency of these markets.
The primary data for this NBA analysis is sourced from BoydsBets, which compiled results from “over 28,000 NBA games.” The assumptions made for the NBA data include, firstly, that this large sample of over 28,000 games provides a statistically reliable and representative overview of NBA moneyline favorite performance across various market conditions. Secondly, it is assumed that the weighted average calculation, as performed in the analysis of the source data , is an accurate and appropriate method for deriving an overall favorite win rate from the provided point-spread-specific win percentages. Lastly, the term “Vegas sportsbooks” is considered to be well-represented by the aggregated data presented in the source.
The NBA’s favorite win rate of approximately 66.43% is strikingly similar to the NFL’s 66.6%. This congruence suggests a comparable level of general predictability for favorites by sportsbooks across these two prominent leagues, despite their inherent differences in game structure (e.g., continuous play vs. discrete downs), scoring frequency, season length (82 NBA games vs. 17 NFL games per team in the regular season), and the relative impact of individual star players. The ability of sportsbooks to establish lines where favorites win roughly two-thirds of the time appears consistent.
The substantial sample size of “over 28,000 NBA games” lends considerable statistical weight to the calculated 66.43% average. In statistical analysis, larger datasets tend to reduce the margin of error and increase confidence in the stability of the findings. Assuming the data collection and subsequent calculations are methodologically sound, the 66.43% figure for the NBA likely represents a very stable historical average for favorite performance.
Further nuance can be added by considering the concept of “favorite-longshot bias.” An analysis of Pinnacle’s NBA moneyline market, a sportsbook known for its sharp lines, suggested that a “weak favourite-longshot bias” might be present. This bias typically refers to a market tendency where favorites might be slightly underpriced (their odds are not as short as their “true” probability of winning would dictate) and, conversely, longshots are overpriced. If such a bias is prevalent more broadly, it could mean that the actual win rate of favorites is marginally higher than what perfectly efficient, unbiased odds would imply. Alternatively, it indicates that sportsbooks are highly adept at setting lines such that favorites win at a rate that sustains public betting interest while ensuring their own profitability. This adds a layer of complexity to the interpretation of “accuracy”—whether it’s accuracy against a theoretical true probability or accuracy in achieving a market equilibrium that may incorporate such subtle pricing characteristics.
In Major League Baseball, the historical win percentage for moneyline favorites appears to be somewhat lower than in the NFL or NBA, reflecting the sport’s unique characteristics and inherent variability. General historical observations from Covers.com suggest that MLB moneyline favorites typically win about 58% to 62% of their games, with the acknowledgment that this figure can fluctuate seasonally.
More specific data, derived from Oddsshark.com and covering an unspecified but consistent “five-year span” across multiple leagues, indicates an underdog win percentage of 41.6% in MLB. By simple deduction (100% – 41.6%), this implies a favorite win percentage of 58.4%. This figure aligns with the lower end of the broader 58-62% range and provides a more precise estimate for a recent multi-year period.
A crucial distinction in MLB betting is the performance of heavy favorites versus all favorites. Data spanning 20 years indicates that while betting on MLB favorites with odds of -155 or higher can yield a win percentage exceeding 60%, such a strategy has historically resulted in a significantly negative Return on Investment (ROI), amounting to a loss of over 300 units (assuming one unit per game). This starkly illustrates that a high win probability for strong favorites does not equate to profitability for bettors, due to the prohibitively short odds offered.
Contextualizing these figures, an academic study using data from 2006-2016 observed that the highest annual team winning percentage in MLB is typically around 61%. This is considerably lower than the peak team performances seen in a league like the NFL (around 87%), a difference attributed in part to MLB’s much longer 162-game regular season and the greater day-to-day variance in baseball outcomes. The high frequency of one-run games in MLB (noted in one source as 28% of all games) further contributes to this unpredictability. These factors help explain why the overall win rate for moneyline favorites in MLB is more modest compared to some other sports.
The data sources for MLB include general historical ranges, specific five-year span data, and 20-year data for heavy favorites. The academic context is provided by data from 2006-2016. Assumptions for the MLB data include: the 58-62% range is a reliable general historical estimate; the 58.4% figure derived from S40 is a reasonable point estimate for a recent five-year period; and “Vegas sportsbooks” are adequately represented by these diverse sources.
The observed MLB favorite win rate, hovering around 58-60%, is notably lower than the approximate 66% rates seen in the NFL and NBA. This suggests a greater degree of inherent unpredictability in baseball. Factors contributing to this could include the significant impact of starting pitchers (whose day-to-day form can vary), the sheer length of the season which can dilute the dominance of even strong teams over any given game, and the higher statistical variance in individual game outcomes.
The data concerning heavy MLB favorites (those at -155 or greater) winning over 60% of the time yet leading to substantial financial losses for bettors is particularly revealing. It demonstrates that sportsbooks are “accurate” in identifying these probable winners, but the odds are structured so unfavorably that bettors consistently lose money in the long run by backing them. This implies that the market for strong MLB favorites is especially efficient at pricing in the sportsbook’s advantage, making it difficult for bettors to find value.
Despite the different sources and timeframes, there is a notable consistency in the figures for MLB. The general historical range of 58-62%, the derived 58.4% from a recent five-year span, and the contextual information that even top-tier MLB teams rarely exceed a 61% win rate over a season all converge. This consistency across various data points strengthens the confidence in this approximate 58-60% range as a stable and reliable estimate for the historical “accuracy” of sportsbooks in picking MLB moneyline favorites.
For the National Hockey League, moneyline favorites generally win more often than not, though with nuances similar to MLB regarding overall predictability. According to general historical data from Covers.com, NHL moneyline favorites are typically observed to win in the range of 60% to 70% of the time.
More granular and recent data provides further insight. Analysis from DailyFaceoff.com for the 2024-25 NHL season (data current as of January 3, 2025) reveals a distinction between home and away favorites: home moneyline favorites were winning at a rate of 61.2%, while away moneyline favorites secured victories 56.6% of the time. Averaging these specific figures yields an overall favorite win rate of approximately 58.9% for that period of the season.
Complementing this, data from Oddsshark.com, which covers a “five-year span” (specific years not detailed but consistent across leagues in that source), indicates an underdog win percentage of 41.4% in the NHL. This implies a corresponding moneyline favorite win percentage of 58.6% (100% – 41.4%). This figure is slightly below the general 60-70% range but aligns closely with the average derived from the 2024-25 season-to-date statistics.
The 2024-25 season data from DailyFaceoff.com also presented a comparison between actual win percentages and the implied odds set by sportsbooks. For home favorites, the implied odds suggested a 62.4% chance of winning, while their actual win rate was 61.2%. For away favorites, the implied odds were 59.9%, compared to an actual win rate of 56.6%. In both instances, the actual win percentages were slightly lower than the implied probabilities from the odds. This difference reflects the sportsbook’s inherent margin (the vig); the market price slightly overestimates the favorite’s raw probability to ensure sportsbook profitability. The sportsbooks are “accurate” in setting lines that yield this margin.
Data sources for NHL analysis include general historical observations, specific 2024-25 season data, and “five-year span” aggregated data. Key assumptions include: the 60-70% range is a reasonable general historical estimate; the 2024-25 data is accurate for that specific period but may not be universally representative of all historical trends due to its limited timeframe; and the 58.6% derived from S40 offers a reliable point estimate for a recent multi-year period.
A notable aspect of the NHL data, particularly from the 2024-25 season, is the discernible difference in win rates between home favorites (61.2%) and away favorites (56.6%). This nearly 5 percentage point gap underscores the significant impact of home-ice advantage in the NHL, a factor that sportsbooks clearly incorporate into their lines, yet one where favorites still demonstrably perform better in their home arenas. This level of detailed home/away favorite win rate breakdown was not as readily available for all other sports within the provided research materials, making this a distinct observation for the NHL.
When comparing the NHL’s overall favorite win rate (approximately 58.6% from S40, or an average of ~58.9% from S12’s 2024-25 data) to other leagues, it positions hockey similarly to MLB (58.4%) and notably below the NFL and NBA (both around 66%). This suggests that NHL outcomes may share some of the higher variance characteristics seen in baseball. Factors contributing to this could include the pivotal role of goaltender performance (akin to pitchers in MLB), the frequency with which games are decided in overtime or by shootout (introducing additional elements of chance), and a potentially higher degree of parity across the league compared to sports with more dominant favorites.
Recapping the findings for individual leagues provides a clear picture of how sportsbook-designated moneyline favorites perform across the major North American professional sports landscape. The NFL leads with a favorite win percentage of 66.6% , closely followed by the NBA at approximately 66.43%. MLB and the NHL exhibit lower, and remarkably similar, favorite win rates, with MLB at 58.4% and the NHL at 58.6% based on consistent five-year span data.
The following table summarizes these key figures:
Table 1: Summary of Moneyline Favorite Win Percentages by League
| League | Favorite Win % | Primary Data Source(s) & Snippet ID(s) | Timeframe of Data | Key Notes/Assumptions |
|---|---|---|---|---|
| NFL | 66.6% | Bet Labs via BetMGM | 2018-2023 seasons | Based on closing lines; favorites of -115 or shorter. |
| NBA | ~66.43% | BoydsBets | Over 28,000 games (timeframe unspecified) | Weighted average based on point spread data. |
| MLB | 58.4% | Oddsshark | “Five-year span” (recent, unspecified years) | Derived from underdog win percentage (41.6%). Consistent timeframe with other leagues from this source. |
| NHL | 58.6% | Oddsshark | “Five-year span” (recent, unspecified years) | Derived from underdog win percentage (41.4%). Consistent timeframe with other leagues from this source. |
These inter-league variations are significant. The higher favorite win rates in the NFL and NBA might be attributed to factors such as a potentially greater influence of elite talent, or perhaps more predictable game dynamics compared to MLB and NHL. The NFL’s shorter season could also allow for more focused predictive modeling by sportsbooks. Conversely, the lower rates in MLB and NHL could stem from greater game-to-game variance, the profound impact of individual performances in key positions (pitchers in MLB, goaltenders in NHL), longer seasons that can lead to more upsets, and potentially higher parity within these leagues.
To derive a combined moneyline favorite win percentage across these four leagues, the data from Oddsshark is particularly valuable as it provides underdog win percentages (and thus, derivable favorite win percentages) over a consistent “five-year span” for all specified sports. Using this source:
A simple arithmetic mean of these four percentages yields a combined favorite win percentage: 4(58.4%+58.6%+65.8%+67.9%)=4250.7%≈62.675% Rounded to one decimal place, the combined moneyline favorite win percentage is approximately 62.7%.
Several assumptions underpin this combined figure. Primarily, it relies on the Oddsshark data from the “five-year span” being representative and comparable across all four leagues. Secondly, a simple arithmetic mean is used for the combined figure because the source material does not provide the number of games played per league within that five-year dataset, which would be necessary for a weighted average based solely on that source. Finally, it’s assumed that “Vegas sportsbooks” are adequately represented by the data aggregated by Oddsshark.
The reliability of using the S40 data for this combined figure is bolstered by its internal consistency when compared to other sources for specific leagues. For instance, the NFL favorite win rate derived from S40 (65.8%) is very close to the 66.6% figure from Bet Labs data. Similarly, the NBA favorite win rate from S40 (67.9%) is proximate to the 66.43% calculated from the extensive BoydsBets dataset. These relatively small differences (0.8% for NFL, 1.47% for NBA) suggest that Oddsshark’s methodology for collecting and analyzing data yields results comparable to other reputable sources, at least for the NFL and NBA. This lends credibility to its figures for MLB and NHL as well, making it a suitable foundation for the combined average.
However, it is crucial to emphasize that this combined figure of approximately 62.7% is an average that masks significant underlying variation. The nearly 8 to 10 percentage point difference in favorite win rates between MLB/NHL (around 58.5%) and NFL/NBA (around 66-68%) is substantial. While a combined figure provides a general overview, league-specific percentages are far more pertinent for understanding the distinct dynamics of each sport.
Furthermore, the utility of such a combined figure has inherent limitations. Aggregating “accuracy” across sports with vastly different characteristics—such as the number of games in a season (MLB’s 162 vs. NFL’s 17), typical betting volumes, and the inherent levels of predictability—is a simplification. A simple average does not account for the varying number of games played in each league over the five-year span covered by the S40 data, which would influence a true weighted combined accuracy. Therefore, while the 62.7% figure addresses the query for a combined number, it should be interpreted with caution and viewed more as a general market indicator than a precise tool for specific betting strategies. The league-specific data offers more actionable and nuanced understanding.
The reported win percentages of moneyline favorites, while indicative of a certain level of predictive success by sportsbooks, are shaped by a complex interplay of market forces and operational objectives that extend beyond mere forecasting. Sportsbooks, at their core, are not solely focused on predicting winners with the absolute maximum accuracy. Their primary aim is to establish a balanced market for each contest, attracting sufficient wagering on all potential outcomes to mitigate their own risk, and to secure a profit through the systemic inclusion of a commission, the vigorish (vig), in the odds offered. As noted, “The Las Vegas odds makers are not trying to pick winners. They are trying to predict outcomes so that they can return the odds for all bettors to 50/50 and ‘balance their book'”. The “accuracy” figures detailed in this report are, therefore, a consequential outcome of this sophisticated market-making function.
The vigorish is a fundamental component of this model. It is the charge, or commission, that sportsbooks embed within the betting odds, ensuring their long-term profitability across a multitude of events. This is why the implied probabilities derived from sportsbook odds for all outcomes of a single event will consistently sum to a figure greater than 100%. The favorite win percentages presented in this analysis are based on these vig-included market odds, meaning they reflect outcomes priced within a system designed for sportsbook revenue.
Betting markets for major sports, particularly as game time approaches, tend towards a high degree of efficiency. The “closing line”—the final set of odds available just before an event begins—is generally considered by market analysts and seasoned bettors to be the most accurate reflection of the true probabilities of the outcomes. This is because the closing line has incorporated the maximum amount of available information, including late-breaking news (e.g., injuries, weather changes) and, critically, the collective judgment of the betting public, especially the impact of substantial wagers from knowledgeable or “sharp” bettors whose actions can shift the lines. One source states, “The closing line is the final odds available right before a game starts. Usually these are the most accurate…”. This principle suggests that sportsbook accuracy, and by extension the reliability of favorite win rates as indicators, is likely at its peak at the closing line. Data explicitly based on closing lines, such as the NFL figures from Bet Labs, is therefore of particular analytical value. The very existence and study of Closing Line Value (CLV)—which measures whether a bettor secured better odds than the final closing line—underscores the market’s self-correcting nature. If sportsbooks were consistently “inaccurate” in a way that created systematically profitable opportunities (e.g., consistently underpricing favorites), sophisticated bettors would exploit these inefficiencies, thereby pushing the lines towards a more efficient, or “accurate,” state. The observed favorite win rates thus reflect a market equilibrium shaped by this dynamic process.
It is also important to acknowledge certain limitations in the available data used for this report. There are variations in the timeframes covered by different data sources, ranging from specific recent seasons to multi-year spans or general historical observations. The term “Vegas sportsbooks” has been interpreted as representing the general regulated sports betting market; however, individual sportsbooks may offer slightly different lines, and their specific historical performance metrics could vary. Furthermore, while sample sizes are often substantial, they can differ, and some data points are specific to certain conditions (e.g., the data for heavy MLB favorites or for NFL favorites meeting a particular odds threshold).
Crucially, a high win percentage for favorites, as set by sportsbooks, does not automatically translate into profitable betting strategies for the general public. The odds offered for favorites are characteristically short, meaning bettors must risk a larger sum to win a smaller one (e.g., betting $200 to win $100 on a -200 favorite). Consequently, a high frequency of wins is required merely to break even, let alone achieve a profit. For example, in MLB, heavy favorites with odds of -155 or greater have historically won over 60% of the time, yet systematically betting on them over a 20-year period would have resulted in an ROI of over -300 units. Similarly, while NHL moneyline favorites are said to win around 60-70% of the time, it’s explicitly noted that “winning percentages don’t guarantee profitability”. This creates a challenging environment for bettors who simply back favorites, as they need to achieve an even higher win rate than the sportsbook’s “accuracy” implies, or be adept at identifying mispriced favorites that offer positive expected value.
The “accuracy” of sportsbooks, therefore, is relative to the market price they establish, a price that includes their operational margin and is designed to balance action, rather than being a pure reflection of “true” underlying probability devoid of these commercial considerations. The favorite win percentages quantify how often the market-favored outcome occurs at these established prices. This might differ, subtly or significantly, from predictions generated by purely academic or statistical models that are not encumbered by the need to create a balanced and profitable betting market.
This analysis has quantified the historical win percentages of moneyline favorites across four major North American professional sports leagues—MLB, NBA, NFL, and NHL—as designated by the broader sports betting market. The findings indicate that NFL favorites have won approximately 66.6% of the time, and NBA favorites have won about 66.43% of the time. MLB and NHL favorites exhibit lower, yet similar, win rates, around 58.4% and 58.6% respectively. Combining these figures, based on consistent multi-year data from a single source, yields an approximate overall moneyline favorite win percentage of 62.7%. This general trend confirms that favorites, as identified by sportsbooks, do indeed win more often than they lose, but the degree of this success varies notably by league.
The “accuracy” figures presented throughout this report reflect the capacity of sportsbooks to set betting lines where the designated favorite prevails in a majority of instances. This capability is consistent with their role as market makers who aim to balance risk while ensuring profitability through the vigorish. It is crucial to understand that these percentages are not solely the product of pure predictive modeling but are also shaped by sportsbook objectives and dynamic market forces, including the influence of sophisticated bettors and the inherent efficiency of closing lines. The relatively high accuracy in identifying favorites, coupled with the systemic ability to maintain profitability, points to the sophisticated modeling, risk management, and market understanding employed by modern sportsbooks.
For bettors, the implications are nuanced. While favorites win more than half the time, often significantly so, this does not directly translate to straightforward betting profitability. The structure of moneyline odds for favorites—requiring a larger stake for a smaller potential return—means that a win rate considerably higher than the sportsbook’s “accuracy” in picking winners is often necessary to overcome the house edge. Therefore, concepts such as identifying value in betting lines (i.e., discrepancies between offered odds and true probability) and achieving positive Closing Line Value (CLV) are more critical for long-term betting success than simply relying on the favorite’s general tendency to win.
The sports betting landscape is not static. The findings of this report represent a snapshot of historical market behavior. Factors such as evolving player strategies (for instance, the increased emphasis on three-point shooting in the NBA), the growing adoption of advanced data analytics by professional teams, and potential rule changes within leagues can all contribute to shifts in competitive balance. These evolutionary trends could, over time, influence the predictability of games and, consequently, the observed win percentages of moneyline favorites. Ongoing analysis of market data will remain essential to track such developments.
Ultimately, the value of this analysis lies not just in the specific percentages, but in fostering a deeper understanding of the sports betting market’s mechanics. The “accuracy” of sportsbooks is a feature of a dynamic equilibrium where lines are set, bettors react, and outcomes occur—all within a framework designed for the sportsbook’s sustained operation. A comprehensive grasp of these factors, rather than a simple reliance on favorite win rates, is paramount for anyone seeking to navigate this complex environment.