Our projections are powered by EV Analytics’ proprietary NBA projection model, trusted by professional bettors and betting syndicates for years. This model blends both quantitative and qualitative inputs to deliver highly accurate, actionable forecasts.
On the quantitative side, our model digests a wide array of advanced stats, including player and team production metrics, historical game logs, pace-of-play numbers, opponent defensive ratings, and situational performance splits. These hard numbers form the statistical backbone of every projection.
But data alone isn’t enough.
We’ve also assembled a team of expert analysts, each hired for their deep domain knowledge and real-world expertise in basketball. These professionals supplement the numbers with critical qualitative insights—like late-breaking injury updates, offical lineups, coaching comments, player usage shifts, rotation changes, minute restriction limits, and insider information not always visible in the data. Their judgment ensures the model stays responsive to real-world developments and the nuanced factors that can impact player performance.
The result:
A robust, real-time projection system that combines cutting-edge analytics with human expertise—consistently outperforming betting markets and making EV Analytics a trusted name in sports analytics.
We’re actively building a comprehensive results table. In the meantime, our main focus is on providing you with powerful data tools to support your own decisions—not selling you static picks. Projections update dynamically throughout the day, reflecting breaking news and odds changes. Because both projections and betting odds fluctuate so frequently, it’s not practical to post “results” for every adjustment.
While we could just sell profitable picks, it’s nearly impossible to scale fairly—odds shift quickly, and not everyone gets the same prices. Instead, we deliver constantly improving models, trusted by pros, and backed by consistent testing and real-world results.
EV Analytics’ reputation is built on transparency and delivering value. Our own team uses these tools to generate profit, and we regularly hear success stories from a growing number of users. Still, remember: projections are not “guaranteed answers.” Sports betting always involves swings and randomness—even the best models have ups and downs. Use our projections as a guide, not a promise, and always bet responsibly.
Projections update constantly throughout the day—whenever relevant new info comes in: injuries, lineup changes, and more. There’s no fixed update schedule; instead, our team relies on internal alerts and monitoring to make real-time adjustments. Some variables, like game totals or point spreads, don’t directly change projections but can influence the process. For example, if a big line move suggests a star player might sit out, projections for related players will adjust accordingly. The result: the most current and accurate player projections possible.
The most accurate projections are available just before game time, after all news and updates are in. However, sportsbook odds are also sharpest at this point. For the best value, check our projections as soon as odds are released—early odds are usually less efficient and offer more potential value. Be sure to check back for updates if injuries or breaking news occur.
The implied projection is a proprietary stat we pioneered at EV Analytics in 2018. Its purpose is to provide a new way to compare a player prop's odds with a player projection. This value is developed internally using our own formulas and models. By comparing the sportsbook's implied projection and our model's projection, users can more effectively spot market inefficiencies. Because evaluating a betting market's price can be difficult, we wanted to simplify the process and give users an apples-to-apples comparison. We believe the implied projection helps users save time when shopping for the best price and improves their overall handicapping process.
The implied projection is calculated using a proprietary formula that converts the sportsbook’s odds and line into the average (mean) stat outcome required for a break-even bet. We take the line and the prices for both sides (Over/Under), determine which side offers the most value, and use probability math to estimate the average performance needed to make that bet profitable at the posted odds. This makes it easier to compare the market to our model’s projection and spot value.
Example: A player who has a prop total line of 7.5 Rebounds (-100/-100), but the implied projection is 8.23. Shouldn’t it be 7.5?
Great observation! It might seem suspicious at first, but here’s why:
A line of 7.5 means the sportsbook expects the player to go over 50% of the time and under 50% of the time.
It does not mean the player averages 7.5 rebounds.
Real NBA box scores don’t cluster around the betting line. Minutes, fouls, blowouts, and randomness create lopsided distributions.
Example rebound log over 26 games (dummy but realistic):
8, 5, 12, 9, 7, 6, 7, 7, 10, 9, 7, 6, 11, 7, 9, 7, 9, 7, 14, 8, 9, 7, 5, 8, 13, 7
Average (mean) = 8.23
Median = 7.5 (middle of 7 and 8)
Player goes over 7.5 in 13 of 26 games (50%)
This shows that a player can average 8.23 yet still land on each side of 7.5 equally often.
To make 7.5 (-100/-100) fair long-term, the player may need a true average closer to 8.23, not 7.5.
Line = median (50/50 break-even point)
Implied projection = mean required to justify the odds
Because NBA stats are skewed, the implied projection often differs from the posted total
This difference is completely normal in the NBA.
Note: We use -100/-100 in this example because it represents a true 50/50 market without any sportsbook hold or juice. Sportsbooks never offer -100/-100 in practice — it’s simply the cleanest way to illustrate the math behind implied projections. (This also helps set up the next FAQ, where we explain how hold/juice affects pricing and probabilities.)
Example: Two Players both have a prop total line of 7.5 Rebounds (-137/-137). One has an implied projection of 7.58, while the other’s is 8.92. How could that be?
Great observation! It might look strange at first, but here’s why this is completely normal:
1. The odds convert to the same break-even probability.
Both the Over and Under at -137 require you to win more than 57.81% of the time to break even. This part is identical for both players.
2. We first identify which side offers the best value.
For each player, our model compares the line and odds to our projection and range of likely outcomes. Sometimes the Over provides the better edge; sometimes it’s the Under—even when the odds are the same. We always select a side as the reference point, even if neither side has value.
3. The implied projection depends on the side we’re solving for.
Once the side is chosen, we simply ask: “What average (projection) would this player need for this side, at this price, to break even long-term?” That answer becomes the Implied Projection.
Chet Holmgren — the Over is the better value.
His implied projection of 8.92 represents the average rebounds he’d need for the Over 7.5 at -137 to be profitable long-term — meaning he would need to go Over 7.5 at least 57.81% of the time, which is the break-even win rate for -137 odds.
Russell Westbrook — the Under is the better value.
His implied projection of 7.58 represents the average rebounds he’d need for the Under 7.5 at -137 to break even — meaning he would need to stay Under 7.5 at least 57.81% of the time.
Same line. Same odds.
But we are solving two different break-even questions based on which side applies:
“What average makes the Over hit at least 57.81% of the time?” (Holmgren)
“What average makes the Under hit at least 57.81% of the time?” (Westbrook)
Because each player would need a different long-term average to reach that 57.81% threshold on their respective sides, the implied projections naturally differ.
On our player prop pages, we display Expected Value (EV) visually using a simple Plus mark system (0 to 5 Plus marks). The more Plus marks, the better the potential value in that bet, according to our model. You can sort by Expected Value to quickly spot the most interesting opportunities.
We provide this information as a tool, not as an instruction to bet. We don’t suggest specific amounts or guarantee outcomes. If everyone bet the same "high-value" props, sportsbooks would quickly adjust lines and limit accounts. The Plus mark system gives you a nuanced way to interpret the data and spot value for yourself.
A positive EV suggests that, over many similar bets, you’d likely come out ahead—but it’s not a guarantee on any single bet. Always weigh all information and bet responsibly.
The EVA % Difference (EV Analytics Projection Percentage Difference) shows how much higher or lower our projection is compared to the implied projection from the sportsbook, expressed as a percentage.
How is it calculated?
If our projection is 24 Points and the implied projection is 20 Points, the EVA Perc Difference is +20%.
If our projection is 0.60 Blocks and the implied projection is 0.50 Blocks, that’s also +20%.
But here’s why it’s not the full story:
A bigger percentage difference doesn’t always mean a better bet. The percentage difference depends on the scale of the stat (Points vs. Blocks), so it can look inflated or minimized depending on the market.
Different player props and betting markets have different ranges and distributions. Projections are not linear—so a 20% difference isn’t always equally meaningful in every market.
Summary:
While it’s not a standalone indicator of betting value, EVA % Difference is a great starting point for identifying props worth a closer look. Used together with Expected Value (EV), it helps you understand both the degree of disagreement with the market and whether the price actually offers a positive long-term edge.
Great question! Our goal at EV Analytics is to empower users with powerful data tools—not simply give out a list of the most “profitable” bets or tell you exactly which market to bet.
Here’s why we don’t show a predicted win probability or a single “fair price”:
We want to provide insight, not picks.
The Expected Value (EV) column already points users toward value by quantifying each bet from 1 to 5 Plus marks. While this helps identify strong betting opportunities, it doesn’t explicitly tell you which specific bet is “the best” or most profitable.
Preventing herd behavior & protecting the edge.
If we highlighted or sorted by “most profitable” bets or widely displayed our model’s win probability/fair price for every market, everyone would flock to the same bets at the same time. This would move lines almost instantly, eroding the value for all users—and often only a few would actually get those odds before they change.
Promoting a sustainable betting ecosystem.
By suggesting a wide range of Plus EV bets and providing clear rankings (1 to 5 Plus marks), we help more users find value and avoid attracting unwanted attention from sportsbooks. Relying on a single list of the “best” or most profitable bets is the fastest way to get limited or restricted.
Encouraging responsible decision-making.
We don’t tell you exactly what to bet or how much to wager. Our tools are designed to empower your handicapping process, not replace it. If several markets have the same Plus mark, it’s up to you to evaluate which fits your preferences and risk tolerance.
Summary:
We believe in giving you the tools and transparency to make smarter decisions—not spoon-feeding the “top pick” or posting a fair price for every bet. This approach protects both your advantage and your accounts, and helps maintain long-term value for all our users.
Historically, yes—our projections and data tools have helped users, including professionals, beat the market over the long run. However, making money in sports betting takes more than just good data. It requires patience, smart bankroll management, sharp timing, and emotional discipline. Sports betting is a marathon, not a sprint, and small edges add up over time. If you’re after a quick windfall, this isn’t the place; but if you treat it as a long-term process, these tools can give you a real edge.
At EV Analytics, we put our own money behind our projections. Our team regularly places real wagers using the same model and tools we provide to subscribers. We don’t just “sell picks”—we rely on this system ourselves.
But here’s the reality of modern sports betting: if you’re consistently profitable—especially in player props—sportsbooks will limit or restrict your accounts. That “glass ceiling” makes it impossible to scale up. Rather than letting a winning model sit idle or go to waste, we believe in sharing our edge with others who want to bet smartly, using actionable data and market-tested projections.
By sharing these tools, we’re building a long-term, transparent business—one that helps more bettors, including ourselves, stay ahead of the curve. We stake our reputation and our bankroll on what we offer, every day.
Our propsheet is still in Beta—we’re actively developing and adding new features based on your feedback. More data can help, but too many columns can slow down the site and make it harder to use. We aim to balance valuable data with a fast, clean user experience. Rest assured, we’ll keep improving and add more reference info as the platform evolves!
We’re always happy to help. Reach out to our support team at support@evanalytics.com or send in your feedback anytime!
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