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Settings →Every AI pick tracked. Every result shown. No hiding, no deleting, no excuses. Browse today's plays, verify our record, and see exactly where the edge comes from.
6
Today's Picks
54.9%
Win Rate
1184
Total Picks
Record
624-513-47
W-L-P
Win Rate
54.9%
Units
+101.3
ROI
+8.9%
Streak
1L
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136-115 · +11.4u · +4.5%
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18-6 · +13.5u · +56.4%
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Arizona Diamondbacks @ Cincinnati Reds - 1:41 PM ET
Arizona Diamondbacks ML(-107)

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Methodology
GODDS uses a proprietary AI algorithm that analyzes real-time odds from the top offshore sportsbooks, combined with historical data, injury reports, matchup dynamics, and situational variables to calculate true win probabilities for every game.
When the model identifies a meaningful discrepancy between its calculated probability and the implied odds on the board, a pick is generated. Each pick includes a confidence rating (1-5 stars), the recommended sportsbook offering the best line, and a detailed analysis explaining the edge.
Most importantly, every pick is tracked and verified. Our win-loss record, unit profit, and ROI update automatically — nothing is hidden or retroactively changed. Transparency is the foundation of trust.
The Process
Data Collection
We ingest real-time odds from the top offshore sportsbooks, injury feeds, weather data, and historical performance metrics for every matchup.
AI Analysis
Our algorithm evaluates true win probabilities, expected margins, and closing line value. It compares its projections against posted odds to find market inefficiencies.
Pick Generation
When the model identifies value — where the true probability meaningfully exceeds the implied odds — a pick is generated with a confidence rating from 1 to 5 stars.
Result Tracking
Every pick is tracked from the moment it publishes. Win, loss, or push — nothing is hidden, deleted, or edited. Our record updates automatically after each game settles.
Pick Types
Straight-up winner predictions. Our algorithm weighs win probability, closing line value, and implied odds to find mispriced favorites and live underdogs.
Example: Lakers ML -150 → Algorithm sees 65% true probability vs. implied 60%
Point spread selections driven by margin-of-victory modeling. We compare our projected margin against the posted line to find value on either side.
Example: Chiefs -3.5 → Model projects 6.2-point margin
Over/under predictions based on pace, offensive efficiency, and defensive metrics. Weather, altitude, and rest days factor into outdoor sports models.
Example: Under 217.5 → Both teams bottom-5 in pace this month
Our highest-confidence plays. These require alignment across multiple model signals — value, edge size, and historical pattern strength all must converge.
Example: 5-star confidence → All signals aligned
Positive expected value (+EV) picks where the true probability exceeds what the odds imply. Not always the likeliest winner, but profitable over volume.
Example: Underdog at +180 → True probability 40% vs. implied 36%
Longer-range predictions on championships, awards, and season totals. Updated weekly as new data reshapes projections.
Example: Celtics to win East +320 → Pre-season value window
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Chicago Cubs @ San Francisco Giants · 10:06 PM ET
San Francisco Giants ML(+100)
The sharp money moved the line from +113 to -103, but the Giants' home record (13-19) was a clear weakness. Chicago's early scoring and bullpen dominance exposed San Francisco's lack of depth. The market overcorrected for a team that simply wasn't good enough at home.
New York Knicks @ San Antonio Spurs · 8:40 PM ET
New York Knicks spread +5.5(-115)
The Knicks' head-to-head dominance continued with a fourth win in five meetings. San Antonio's offense stalled against New York's defense, failing to reach 95 points. The +5.5 spread was never in doubt as the Knicks led wire to wire.
Philadelphia Phillies @ Milwaukee Brewers · 7:11 PM ET
Milwaukee Brewers ML(-162)
The Brewers were the better team with sharper line movement, but Aaron Nola and the Phillies offense caught fire. Milwaukee's bullpen blew a lead, and the Phillies scored 6 runs in two innings to flip the game. Process was sound, result was not.
Atlanta Braves @ New York Mets · 4:10 PM ET
Atlanta Braves ML(+102)
The Braves' elite pitching and road record overwhelmed a mediocre Mets lineup, validating the +102 value at Bovada. The gap in team quality was too wide for the odds to ignore.
San Diego Padres @ Baltimore Orioles · 4:06 PM ET
Baltimore Orioles ML(-125)
The Orioles' pitching collapsed, allowing 9 runs to a Padres team that had lost 4 of 5 and was missing two starters. Sharp money pushed the line but couldn't predict a bullpen implosion. The pick missed because we overvalued the line movement and undervalued San Diego's lineup.
Miami Marlins @ Pittsburgh Pirates · 4:06 PM ET
Miami Marlins ML(+114)
The Marlins were the hotter team with a 10-game win streak, and the Pirates had lost 8 of 10. The +114 price was inflated due to market bias, and Miami dominated from the start, covering easily.
Seattle Mariners @ Washington Nationals · 4:05 PM ET
Seattle Mariners ML(-103)
The Mariners' superior pitching and the Nationals' terrible home record were the decisive factors. Seattle's offense exploded for 10 runs, and their staff held Washington to just 2. The pre-game edge in ERA and home/road splits translated directly to the field.
New York Yankees @ Toronto Blue Jays · 3:08 PM ET
New York Yankees ML(-122)
The Yankees' pitching held Toronto to one run, while their offense generated enough support. The run differential and ERA advantage we highlighted pre-game played out exactly as expected.
St. Louis Cardinals @ Minnesota Twins · 2:11 PM ET
St. Louis Cardinals ML(-104)
The Cardinals led 6-2 but their bullpen collapsed, allowing 7 runs after the fourth inning. Minnesota's offense rallied late, overcoming St. Louis's pitching advantage. The pick was sound based on form and pitching, but baseball's unpredictability won out.
Philadelphia Phillies @ Milwaukee Brewers · 7:41 PM ET
Milwaukee Brewers ML(-233)
The Brewers' pitching dominance and home field advantage were the deciding factors. Milwaukee's staff held the Phillies scoreless, and their offense provided enough support. The line movement toward Milwaukee confirmed sharp action, and the final score validated the confidence level.
Los Angeles Dodgers @ Chicago White Sox · 7:41 PM ET
Los Angeles Dodgers ML(-147)
The Dodgers had clear statistical advantages in runs scored, runs allowed, and ERA, but the White Sox outplayed them in every phase. This was a classic case of a good team having a bad game, which happens often in baseball. The pick was sound based on the data, but the execution failed.
New York Yankees @ Toronto Blue Jays · 7:37 PM ET
New York Yankees ML(+107)
The Yankees lost because their bullpen blew a lead in the 7th inning, allowing 4 runs. Sharp money had moved toward Toronto before the game, signaling value on the Blue Jays that we missed. The statistical edge on paper didn't account for bullpen fatigue and market movement.
Atlanta Braves @ New York Mets · 7:15 PM ET
Atlanta Braves ML(+114)
The Braves were the better team with superior ERA, but their pitching staff allowed 7 runs and the Mets' bats showed up. Value was there at +114, but execution failed.
Detroit Tigers @ Cleveland Guardians · 7:11 PM ET
Cleveland Guardians ML(-105)
The Guardians' pitching dominance over the Tigers continued, holding them to two runs. Detroit's poor road record and Cleveland's head-to-head success made this a sharp play at -105.
Texas Rangers @ Boston Red Sox · 7:11 PM ET
Texas Rangers ML(+118)
The Rangers' pitching fell apart, allowing 10 runs despite a superior season ERA. Boston's home offense dominated, and Texas couldn't generate any offense. The sharp money was wrong this time.
San Diego Padres @ Baltimore Orioles · 7:06 PM ET
Baltimore Orioles ML(-137)
The Orioles' home offense outscored the Padres' struggling lineup by 4 runs. San Diego's losing streak continued, and Baltimore's pitching held them to 3 runs. The pre-game edge in runs per game at home was the key indicator.
Seattle Mariners @ Washington Nationals · 6:46 PM ET
Seattle Mariners ML(-135)
The Mariners' superior pitching (3.54 ERA vs 4.66) and the Nationals' injury-riddled rotation created a massive edge. Seattle's offense capitalized against Washington's depleted staff, leading to a blowout win.
Miami Marlins @ Pittsburgh Pirates · 6:41 PM ET
Pittsburgh Pirates ML(-140)
The Pirates lost because Mitch Keller gave up 5 runs in the first two innings, putting the team in a hole they couldn't climb out of. Miami's offense, which had been inconsistent, capitalized on early mistakes and held on for the win.
Atlanta Braves @ Chicago White Sox · 7:41 PM ET
Atlanta Braves ML(-114)
The Braves lost despite strong underlying metrics because baseball is volatile over one game. Chicago's pitching stepped up and Atlanta's offense had an off night. The pick was still correct based on the data; variance happens.
Seattle Mariners @ Baltimore Orioles · 7:06 PM ET
Seattle Mariners ML(-111)
The Mariners' pitching advantage was supposed to be the difference, but their starter struggled early and the bullpen couldn't hold. Baltimore's offense exploded for 7 runs, outpacing their typical production. Sometimes the numbers don't translate to the field, and this was one of those nights.
Philosophy
The sports betting industry is plagued by fake records, deleted losses, and retroactive line changes. Handicapping services routinely claim 70-80% win rates that crumble under scrutiny. At GODDS, we built our pick tracking system to be tamper-proof from day one.
Every pick is timestamped when it publishes, with the exact line and odds recorded. Results are automatically graded when games settle — no manual intervention, no after-the-fact editing. If we go on a losing streak, you'll see it right here on this page.
We track units gained/lost rather than dollar amounts because unit-based tracking is the industry standard for evaluating betting performance. It normalizes results across different bankroll sizes and eliminates the incentive to cherry-pick bet sizes.
We also track closing line value (CLV) — whether we beat the final line at game time. Research consistently shows that CLV is the strongest predictor of long-term profitability, even more predictive than short-term win rates.
FAQ
GODDS combines the analytical power of artificial intelligence with the transparency that the sports betting industry desperately needs. Our algorithm processes thousands of data points per game — from real-time odds across the top offshore sportsbooks to injury impacts, rest advantages, and historical trends.
But what truly sets GODDS apart is accountability. Every pick is publicly recorded, every result is automatically graded, and our full performance history is available for anyone to audit. We don't sell picks — we prove them.
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