Looking at this match-up we have an underperforming Bengals team with simply too much talent to be 1-4 to start this season. Joe burrow has been putting up insane passing numbers but his defense has not been playing well at all. From a statistical veiwpoint lets look at some team numbers and individual numbers to give you an idea of what we can expect in this Week 6 Prime time match-up.

Cincinatti has a top 5 scoring offense but a bottom five scoring defense. Bengals are scoring 28 a game while giving up 29. The Bengals are putting up 359 yards of offense and allowing 365 yards defensively. Joe Burrow has an average passer rating this season of 110.98, a completion percentage of 72% and a QB EPA of +6.52, which is top 5 in the NFL in all three categories. This is ridiculous for a team that is 1-4. It is obvious that Cincinatti's problems lies on the defensive side of the ball as the Bengals are a top 5 passing offense averaging 267 YPG through the air. Cincinatti cannot run or stop the run only averaging only 96 YPG on the ground (bottom 5) while giving up 151 YPG rushing to opponents (bottom 5). 

For Daniel Jones and the Football Giants they are looking to get to .500 in a super competitive NFC East and have actually been playing decent football despite their record. They are putting up an average of 17.8 ppg and allowing a hair under 21 ppg. Offense is getting 321 ypg and defense is allowing 316 ypg which is below the league average so defensively the Giants are playing decent. Daniel Jones has an average passer rating of 88.9 and a completion percentage of 64%. Additionally his Qb EPA is positive at 0.08 which for the last three weeks has stayed consistent. The Giants have been consistently above league averages in EPA in all of their games with the exception of week 1 vs the Vikings. So what we have in NY is a scrappy team that can't light up the scoreboard offensively but are giving you the type of consistensy that allows us to know what we are going to get. The pass defense for the Giants is only allowing 200 ypg and 316 ypg in total defense. Not eye popping numbers but will allow them to hang around and keep games close. What I like to see is consistentcy, no matter good or bad, and what the Giants are is an average team that hits their averages. You know what you are getting. The Bengals are wildly inconsistent and we never know which version of the Bengals we are going to get. With the exception of Joe Burrow, the rest of Cincinatti is a complete wild card. I look to see the numbers for Joe Burrow to stay within his averages but I also have concerns for a team that cannot move the ball on the ground. One-dimensional teams are easier to scheme against and in the National Football League you need to run and stop the run to play big time football and the Bengals haven't shown us all year that they are able to do that. I look to see the Giants to run effectively and shorten this game and if they can move the ball on the ground and move the chains then they can shorten this game and make it a scrppy close game that gives them a chance to even their record. Bengals are aware that one more loss early in this season will effectively destroy any chance for the playoffs and they need to be able to establish some sort of run game and commit to balancing the way they move the ball. It has to start tonight. 

The play for me in this game is the UNDER 46.5 for the game. With the offensive injuries that the Giants have, Malik Nabors and Devin Singletary both listed as OUT, I look to see Daniel Jones having to use his legs to extend drives. Cincinatti has Zack Moss listed as questionable and if he can't go then it is another blow to the Bengals run game. For me the play is UNDER 46.5 and a close game spread wise, but not willing to take or lay the 3.5 so I will pass here ATS. Should be a good Prime Time Match-up. Enjoy.

Title: What Is Quantum Logic™

Published by: Jim Zepton Top 1% SuperContest Finisher | Founder, VIP Elite Sports

The Problem: Sportsbooks Don’t Set Lines to Be Right—They Set Them to Be Bet

Most bettors think they’re playing against Vegas. They’re not. They’re playing against each other—inside a market designed to exploit emotion, bias, and recency. That’s not a market. That’s a trap.

The Solution: Quantum Logic™

Quantum Logic™ is a proprietary decision engine built to detect inefficiencies in sports markets before they correct. It’s not a model. It’s a multidimensional framework that simulates, adjusts, and deploys capital based on signal—not sentiment.

What Powers It

• Monte Carlo Simulation Architecture > 10,000+ matchup simulations per position to map volatility and outcome clusters

• Market Spread Delta Detection > Identifies where the posted line diverges from our corrected model line

• Cluster Injury Analytics > Adjusts for non-linear impact of injuries across position groups and tempo

• Regression-Corrected Team Ratings > Strips out noise from recent results and recalibrates true team strength

• Variance Mitigation Protocols > Exposure-weighted allocation to reduce drawdown and maximize compounding

What It’s Not

• Not a pick service

• Not a trend-chasing algorithm

• Not “gut feel” with a spreadsheet

Quantum Logic™ is a capital deployment system—built to extract alpha from mispriced markets with institutional discipline.

Why It Works

Because sportsbooks can’t adjust fast enough. Because the public overreacts. Because volatility is predictable—if you know where to look.

Quantum Logic™ doesn’t chase winners. It prices inefficiency, then deploys capital with surgical precision.

Real-World Results

• Week 9–18 (2024 NFL): 26–17–2

• ROI: +14.75%

• Outperformed S&P 500 by 3x

• Zero leverage. Zero drawdown. Zero guesswork.

Related Pages

• Steelers vs. Browns: 5.2-Point Spread Inefficiency

• Why Sports > Stocks: The ROI Ledger

• 25% ROI Guarantee – How It Works

I know its early in the season but tonight we have the Vancouver Canucks coming to Amalie Arena to take on the Tampa Bay Lightning. This will be Tampa's home opener  in what should be a very strong Lightning campaign. This season should be one that gets the Lightning deep into a playoff run as Tampa ran into serious hockey fatigue playing basically four seasons from 2021-2023 with how much post-season play they were involved in. After last season that wasn't a disappointment they come into this season looking for a deep playoff run and perhaps another Stanley Cup. Given the emotional state of the Tampa area recently hit and devastated by Hurricane Milton look for the energy levels to be astronomic for this home opener and look to see a big win by the home team. This should be a great night on the ice.

Play on

Tampa Bay -1.5 on the puck line at +185

We have a good match-up tonight that will give everyone a chance to see two evenly matched teams to play each other in what should be a decent game. On one side we have the rookie QB Bo Nix and the Denver Broncos who have actually been a pretty decent team so far this season. The defense of the Broncos under Sean Payton has been the bright spot and it has given his young quarterback a chance to manage games while the defense keeps things close. The Saints have been a trainwreck. The reality is that they are a bad team and they beat two other bad teams to start the season, whipping both Carolina and a very bad Dallas team. Since then they have been beaten 4 straight and this looks like another game they will struggle in as well. The injuries for the Saints are epic. Alvin Kamara, Ceaser Ruiz, Rasheed Shahid, Derek Carr all no gos tonight and one thing I see about twice a season is a team playing three games within 11 days. You had a monday night game two weeks ago with the Saints playing the Chiefs in Arrowhead Stadium, then they play six days later and get ran out of the building by Tampa Bay, and now on a short week have to turn around and face a top 5 defense in the Denver Broncos who are going to bring a ton of pressure against another rookie quarterback in Spencer Rattler. Even if this Saints team was healthy and at full strength the fatigue of three games in 11 days is usually too much to overcome. I do beleive Spencer Rattler is servicable in this spot and will be able to do some things here but over the course of the game that fatigue is going to set in and be too much for any team to over come. Look for the Broncos to pour it on in the second half and put this game out of reach.

Go ahead and play DENVER -3.5

Take Care,

Jim

In this Prime Time Matchup of two powerhouse teams tonight, we have on one side of the ball, the Baltimore Ravens (4-2) having reeled off 4 straight games and looking like early front-runners for Super Bowl contenders. With a virtually unstoppable run game with Lamar Jackson and Derrick Henry running the league over averaging 205 yards a game on the ground and if that isnt enough they pass for an average of 251 thought the air. Baltimore really has no weaknesses here and this is a spot where they should be able to move the chains with the balance of offense the Ravens have. You have got to put a man on Mark Andrews, Zay Flowers, Isaiah Likely and Rashod Bateman which makes it insanely hard to play run defense. This is a nightmare situation for any defensive coordinator. Lamar Jackson is AVERAGING a 113.6 passer rating and has a QB EPA of 6.76. Ridiculous. 

On the flip side you have a Tampa Bay team that has zero issues moving the ball and putting up alot of points and yards and they have been gaining alot of yards rushing lately with the emergence of rookie running back Bucky Irving. While Tampa doesnt have the run game of the Ravens they are still running for a respectable 136 ypg on the ground so they can play physical football with anyone, but in this matchup the Bucs will try to establish a passing offense that has been putting up video game numbers. Baker Mayfield has an AVERAGE passer rating of 109.3 and is completing 71.4% of his passes. He has Mike Evans and Chris Godwin and also has Bucky Irving catching passes out of the backfield. 

With both teams playing such efficient football and having high-powered offenses this game should easily sail OVER the total of 50 and we might even close to that by halftime. These are two of the best teams in the National Football League and there is a possibility we could be watching a Super Bowl Preview. Look for points a plenty here guys and have no doubt when you pull the trigger on the OVER 50. Easy Money!!!

As for the outright winner I would say whoever has the ball last. 

Enjoy this Week 7 Treat on Monday Night

Take Care,

Jim

Got an early season NBA match-up between the Bucks and the Sixers that on paper should have been a powerhouse Eastern Conference match-up but afte looking at the injuries from the 76ers this is going to wind up being a laugher in favor of the team from Milwaukee. The Sixers go tonight without Joel Embiid AND Paul George and recently these games have been won by MIlwaukee with Embiid in the game. These two no-go's tonight are the difference maker in the decision for me as Embiid-led Sixers teams at home have proven over the last few years to almost unstoppable. 

Embiid averaged 34.7 points and 11.0 rebounds in 33.6 minutes per game last season, although he was limited to 39 contests after undergoing in-season left knee surgery.

George, who signed a four-year, $212 million deal with Philadelphia in the offseason, averaged 22.6 points for the Los Angeles Clippers in 2023-24.

Offense wasn't the issue for the Bucks last season. They averaged the fourth-most points in the NBA at 119.0, but were just 21st in defense, allowing 116.4 points per game being led by Giannis Antetokoumpo. Antetokounmpo averaged 30.4 points and 11.5 rebounds last season, while Lillard chipped in 24.3 points and 7.0 assists during his first season in Milwaukee. Milwaukee has some injury issues of their own but none to the extent of the Sixers. THe bright spot for Philly is that they will have Tyrese Maxey who is awesome to watch play the game. Maxey was named the NBA's Most Improved Player last season, and was an All-Star for the first time after averaging 25.9 points and 6.2 assists. But depth over the course of 4 quarters will be an issue for the Sixers and Milwaukee has won each of the last four meetings between the teams, including all three last season, and has either won or tied the season series going back to the 2012-13 campaign

The line in this game is Bucks -3.5 and I'm gonna call it 

Bucks 121 Sixers 110

Jim

Tonight we get super lucky as the last few weeks in college football the Thursday night match-ups have been pretty bogus, but tonight we get the Syracuse Orangemen (5-1) taking on #19 Pitt (6-0) in what is shaping up to be a monster football game with college football playoff implications. The Panthers are one of 9 remaining undefeated FBS teams and is seeking their first 7-0 start since Dan Marino was their quarterback in 1982. Pitt has a 13% chance to make the college football playoffs and that percentage jumps to 17% with a win over the Orange.

Syracuse is looking to start the season 6-1 for the second time in the last three seasons and QB Kyle McCord has passed for 300+ yards in every game this season. He is second in FBS with 360 passing YPG and has tossed 19 TD's which is tied for fifth in college football. This is truly Pitt's first test of the season as they have faced lower-tier competition so far and have faced no ranked opponents. Pitt brings the 12th ranked passing attack averaging 305 YPG through the air and also has some balance as they average 176 YPG on the ground but my concern here is the level of competition they have fattened those numbers against. Syracuse has gotten their 5-1 record by beating two top 25 teams this year, and in addition to McCord's passing numbers, are getting 104 YPG on the ground. There should be no shortage of points scored in this game, and with two high-powered offenses on display this has all the makings of an instant classic. The betting line for this game is Pitt -6 and the total is set at 62.5. Given the level of competition that Pitt has faced this year they should be coming into this game with a 6-0 record and there have been some close games in that stretch that should not have been close. I am taking the Orange in this spot to get the outright win and put themselves in the conversation of the upcoming college football playoffs. This is gonna be a barn burner guys. Gimme the 'Cuse head up.

Syracuse 38 Pittsburgh 35

Jim

Since the start of the 2024 NBA season I have spent every night watching at least 2 NBA games. During the days I have Hockey and the NBA playing constantly on my TV's and I get plenty of time in front of these players to see exactly how they play as a unit and also certain match-ups that give a certain team an advantage against another. Tonight we have a match-up between the Knicks and the Hawks that should go according to numeric script. First off, the Atlanta Hawks is a team I have seen play three games this season and the one thing that stays absolutely consistent is every game is this Atlanta team plays no form of defense. In the 8 games Atlanta has played this season all but one game sailed OVER the total and they actually had 7 straight go OVER until Boston came in and completely shut ATL down. The funny thing about watching Atlanta is that they have no problems offensively and when they get the players back that are out due to injury this Atlanta Hawks team will be a problem for most NBA teams. They have Tre Young that leads the league in time he possesses the basketball and he can drive, shoot from deep and also distrubute the ball efficiently. Atlanta gets a lot of offensive rebounds and also has alot of young talent on the floor with last years #1 draft pick but at the end of the day when you play in the NBA if you cant stop the other team from scoring you lose. The Hawks will try to outscore you and they can put up points but they put no effort into defense and it is obvious from the jump that these games are headed for an easy OVER cover. The problem Atlanta will have tonight is Karl Anthony-Towns. KAT is the best shooting big-man in the NBA. It isn't even close. He can hit three's and post-up. He can bang inside or bring you past the arc and score at will. There arent too many teams that have a defender that can slow down KAT and Atlanta has absolutely no one to defend this guy. I look to see New York run the offense through Towns and establish alot of screen rolls with Towns and Brunson. This should be an master class in old school NBA basketball with the way the Knicks can use Atlanta's over pursuit of the ball defensively to get guys open, and with the triple threat New York poses offensively with KAT, Brunson and Hart it should be a game very similar to the one last played Monday between the Celtics and the Hawks. Atlanta has no perimeter defense and no big man to slow Karl Anthony Towns. This one will be over by halftime. Hawks have only covered ONE point spread all year and had 7 straight OVER's cash before last games UNDER. I look for ATL to regress to the mean here. They get blown out and the game sails OVER. The line right now is New York -7 225. The Play is Knicks and OVER.

Jim

The NFL will have the majority of everyones attention today but there is a game in the NBA tonight that should be a game with playoff-like intensity and gives us a chance to see two powerhouses go at it and decide it on the court. I know it's early in this season but some games are must watch TV. The NFL Sunday Night game is Detroit vs Houston and that should be on everyones TV but if you can splitscreen or have two TV's in your man cave then the Mavs and Nuggets should be on the other screen. What we have are two teams designed to do the exact same thing offensively and defensively. These teams are mirror images of each other. In Dallas you have the thre-headed-snake of Doncic, Irving, and Thompson that are the offensive production of the Mavs, along with Derrick Lively and Gafford inside to bang and grab rebounds and cause problems in the paint for opposing teams, The Mavs are putting up 113.4 ppg and can attack you from anywhere on the court. The bench production allows little drop off  when the starters are getting a rest. So plenty of fire power in Dallas. On the other side of the court you have Denver who is averaging 120.8 ppg and have a myriad of offensive firepower for the Mavs to try and slow down. The main problem for any team trying to slow down the Nuggets is Nikola Jokic. Dude is averaging a triple-double this year. Again. Averaging 28.9 ppg and leading the league in rebounds AND assists with 13.2 boards per game and 11.3 dimes. Dude is a nightmare matchup for the entire NBA. If you play fantasy basketball the Joker is a mandatory start every night getting fantasy players a ridiculous 65.6 points per contest on average. Add in MIchael Porter Jr. Aaron Gordon, and Jamal Murray and you have arguably one of the best starting fives in basketball. The advantages here are very few and far between as these two clubs are mirror images of one another. One thing I always remember about games played in Denver is the altitude. Two teams have huge altitude edges, Utah and Denver. Conditioning becomes an issue with teams coming to Denver to play at a mile above sea level and the Nuggets are a top 3 pace team in the NBA which over the course of 4 quarters will over fatigue the opposition. I look to see Dallas try to slow the pace and set things up in the half court and run the offense through Luka Doncic and Kyrie Irving. The Nuggets play excellent perimeter defense and should slow the production down that Klay Thopmson gives the Mavs and remember that Klay Thompson himself is a terrific perimeter defender and should be on Kyrie and on switchouts will be defending Jamal Murray so look for the production to drop from both teams guard play. On the inside is where the Mavs have the advantage, even against Jokic. They can throw bodies at the Joker and with Derrick Lively and Gafford they will be able to stop Jokic from dominating the glass and having his way in the paint. This game should come down to the mid-range game of guys like Aaron Gordon who are guys that fly a bit under the radar with all the star power both teams have. This game is going to be a chess match as it is a possible playoff preview. I look to see reduced pace from both teams and a focus on motion switchouts to get Jokic on smaller defenders and avoiding the size down low that Dallas has. Jokic is going to get his but he will have to do it from outside. If Dallas can run a bunch of bodies at Jokic and force him to shoot lower percentage shots Dallas might be able to pull the outright upset in this one but my focus for a betting play is definitely on the UNDER. I think with the focus being on the premeir defenders stopping the offense from either team this is going to be a low scoring defensive game that resembles a game being played in mid-May instead of early November. Look for alot of missed shots and a low scoring game . The line now is Denver -5, O/U 232.5. Im passing on a spread winner here and am going to absolutely HAMMER the UNDER 232.5 

PLAY IS Dallas Mavericks/Denver Nuggets UNDER 232.5

Enjoy the Week 10 NFL games today and hopefully you can catch this awesome NBA game during commercial breaks.

Take care guys,

Jim

Steelers vs. Browns: How Quantum Logic™ Detected a 5.2-Point Spread Inefficiency

Published by Jim Zepton  
Top 1% SuperContest Finisher | Founder, VIP Elite Sports

—

The Market Missed. We Didn’t.

In Week 14 of the 2024 NFL season, the public saw a low-total slugfest. We saw a volatility window.

While sportsbooks posted a total of 37.5, our Quantum Logic™ simulations flagged a 5.2-point delta, projecting a corrected model line of 32.3. That inefficiency wasn’t guesswork—it was signal.

—

What Drove the Edge?

- Pass Rush Mismatch Index: Pittsburgh’s front seven ranked #2 in pressure rate vs Cleveland’s backup offensive line  
- Weather-Adjusted Pace Metrics: 18% slower-than-average tempo projected due to wind shear and field conditions  
- Quarterback Volatility Score: Rookie QB variance for Cleveland triggered a 1.7-point downward adjustment in scoring probability

—

Capital Deployment Strategy

We executed a structured UNDER position at 37.5, using variance mitigation protocols and exposure-weighted allocation. This wasn’t a bet—it was a capital deployment decision based on multidimensional inefficiency.

Final Score: Steelers 17, Browns 13  
Result: ? UNDER cashes by 7.5 points  
Alpha Extracted: +1.0 unit ROI

—

Why It Matters

This wasn’t luck. It was repeatable edge.  
Quantum Logic™ doesn’t chase narratives—it prices them before the market corrects.

—

Related Case Studies

- How We Beat the Super Bowl Total by 6.5 Points  
- What Is Quantum Logic™  
- Why Sports > Stocks: The ROI Ledger
 

Hey Guys,

The way I wake up every day is by throwing in a ridiculous dip of Apple Skoal snuff and grabbing a cup of Colombian coffee. The first thing I do after is crank up the laptop and update my NBA numbers on all my spreadsheets. I have a sheet in particular that gives me a probability analytic. Sometimes when I handicap sports, and this is one of my favorite data sets to mine, I use a basic probability sports model to give me a percentage of probability in upcoming match-ups. Once certain teams bling on that basic spreadsheet I move the selected criteria to another sheet. Then I calculate the probability of those teams either covering a spread or going OVER or UNDER the listed totals. I usually find one or two teams or totals that jump off the page and give me the highest probability of making a solid bet. Today there are quite a few that give us an edge in tonight's NBA. 

This is based strictly on the probability of a certain thing happening guys. No stats are used in this particular model. 

If you flip a coin you only have two possible results. Heads. Tails. If you flip a fair coin 99 times and it lands on heads 99 straight times, the probability of the 100th flip is still 50/50 because there are only two possibilities. I get that, but using simple coin flipping probability, when it comes to events that have another variable, which is a point spread or a total in a game the coin flip has to have an edge. Here are tonight's games that have a probability edge in either covering or going over or under.

Dallas +7.5

Dallas has not covered the point spread in 5 straight games while the Lakers have covered 3 straight. Dallas is at home getting 7.5 points. The numeric probability of Dallas covering is 98.4% while the probability of the Lakers not covering is 93.8%

Phoenix/Charlotte OVER 222.5

Phoenix is 6-0-1 UNDER their last 7 games

Charlotte is 7-0 UNDER their last 7 games

The numeric probability of these two teams going OVER the total is at a very comfortable 99.6% for EACH team giving us an almost 100% chance of the game going OVER. Think about Jim Carrey in Dumb and Dumber. There is a chance it goes under, but our probability is super stacked in our favor here guys. This is my best bet of the day based on probability. Highest EDGE bet of the day for me. 

Miami/Golden State UNDER 218.5

Miami has gone OVER in their last 4 games

Golden State has gone OVER three straight

We are getting super close to !00% probability edge here guys. One factor I will throw in is the fact that Miami is on the road and they played a double overtime game last night and are in a state of flux with the Jimmy Butler-being-a-cunt debacle,this is a good spot for teams to go UNDER.. 

This last probability play has two factors but also gives us a high probability edge. One thing that I look for is a term called regression to the mean, RTTM. This is when teams are heading in a certain direction and meet the probability threshold, but are statistically going to regress or progress to the mean. Here is a situation where we have a regression to the mean. 

Minnesota/New Orleans OVER 220.5

Minnesota had gone OVER 5 straight games before going UNDER last night vs the LA Clippers (our free play winner last night BTW) 

While I called last nights match-up to go UNDER and called it correctly, the regression point now is for Minnesota to go back OVER tonight. Here's why.

New Orleans had gone OVER the total 6 straight before they met the threshold and finally went UNDER. Now these teams are heading into a match-up against each other and now we get our probability and the regression. They will go back to being a solid OVER play.

I hope you took 5 minutes out of your day to read this article guys and hopefully the numbers are on our side tonight.

Take care,

J

Hey Guys,

This game comes down to health and the Utah Jazz are decimated with injuries. The Charlotte Hornets are basically intact, and they have been playing cohesive basketball as a unit lately. Utah has most of their starters listed as OUT tonight and over the course of a 4-quarter basketball game the lack of depth for the Jazz will be simply too much for them to overcome versus a healthy Charlotte team playing with extended rest due to a couple of their recent games being cancelled due to the LA wildfires. Taking you through the injuries and players listed as OUT or QUESTIONABLE here for the Jazz.

• Keyonte George PG - QUESTIONABLE (hip) 15.6 ppg
• Collin Sexton SG - OUT 18.2 ppg
• Lauri Markkanen SF - OUT 20.1 ppg
• John Collins PF - OUT 17.9 ppg
• Jordan Clarkson SG - OUT 16.0 ppg
• Johnny Juzang SF - OUT 7.3 ppg

Guys, 4 of the players listed above are starters and the two bench guys are regular rotational guys for the Jazz. With Charlotte being pretty much 100% healthy I will ride with the healthier team that has been playing good basketball lately against the West. Lamelo Ball, Miles Bridges, and Mark Williams have been lights out and they have been getting good production off the bench. The depth off the bench produces very little drop-off once the starters rest and this will be hard for Utah to overcome with the majority of their current starters being bench guys themselves. I always consider the altitude in games played in Utah and Denver and stamina being an issue but this game will most likely be a laugher with the Hornets getting a double-digit win. Easy cover here guys as the spread is only Charlotte -5 in most books. Grab this one early as the money is likely to come in heavy on the Hornets.

The play here is Charlotte -5

Take Care Y'all

Jim

One way or the other, history will be made at the conclusion of Super Bowl LIX. Either the Chiefs will be the first team to win three Super Bowls in a row, or the Eagles will become the first team to win a Super Bowl "rematch" after losing the first game. 

As far as matchups are concerned, it really doesn't get any better than this, and that's what makes this game so hard to try to predict. On paper, this game has the makings of another Super Bowl classic, similar to the first Chiefs-Eagles Super Bowl. That game literally came down to one or two plays (and calls) determining the outcome. 

Along with the experience of having won Super Bowls, the Chiefs have another advantage over the Eagles in that they know exactly who they are, especially on offense. The Chiefs know that Patrick Mahomes will run the show when they have the ball. Conversely, will the Eagles focus on getting Saquon Barkley going early, or will they instead try to get Jalen Hurts off to a good start? Philadelphia's offense is so good that it actually creates an issue as far as that is concerned. 

Last year, the 49ers got their stud running back, Christian McCaffrey, involved early, and it nearly resulted in victory. But the 49ers unwisely went away from him at critical moments in overtime, and that contributed to their second Super Bowl loss to Kansas City. The Eagles need to make sure that they don't make that mistake with Barkley. 

Speaking of the running game, that's where the biggest disparity is between these otherwise evenly matched teams. The Eagles possess the NFL's best running back in Barkley, who is the first 2,000-yard rusher to get to a Super Bowl. Barkley's presence has opened things up for Hurts and the passing game. It has also enabled the Eagles to routinely win time of possession while keeping opposing offensives off the field. This has to be the case again on Feb. 9 if the Eagles are going to win. 

Philadelphia is also going to need a big game from Hurts, who scored four total touchdowns in the Eagles' NFC title game win over the Commanders. Hurts specifically had success throwing downfield to A.J. Brown, who consistently won his one-on-one matchup with Marshon Lattimore. Brown was single covered because the Eagles have too many weapons to focus too much on one player. 

Every defense that plays the Eagles' offense basically has to pick their poison. Do they stop Hurts and the passing game, or do they try to neutralize Barkley while putting the game on Hurts' shoulders? If I'm Chiefs defensive coordinator Steve Spagnuolo, I'm focused on neutralizing Barkley while forcing Hurts to beat me. 

If that's how Spagnuolo decides to play it, it doesn't mean that it'll work. Barkley, as we all know, has the unique ability to turn seemingly nothing into a big play. He can also make plays both between the tackles as well as on the outside, so the odds of Barkley being a non-factor in this game is virtually none. 

If the Chiefs are able to make things somewhat difficult for Barkley (especially early), this is where Hurts' performance is so critical. Hurts can't warm up to the competition; he needs to go into the Super Bowl with the expectation of being aggressive right off the bat. You don't beat the Chiefs with safe check downs, you beat them with boldness and big plays. 

This is also where Hurts' mobility is key, just as it was when the two teams faced off in the big game two years ago. It's no secret that Hurts has been playing through a knee injury that has likely led to him running less than he normally would. Barkley has taken some of that burden off of him, but Hurts will still have to make more than a few plays with his legs if the Eagles are going to pull off the upset. 

Defensively, the Eagles absolutely have the players to contain Mahomes and the Chiefs' offense. The Eagles don't allow many points (they were second in the NFL in fewest points allowed during the regular season) and they thrive off of getting turnovers. Philadelphia enters the Super Bowl with a +10 turnover ratio during the postseason, while the Chiefs are -1.  

You can say that the Eagles' defense hasn't faced a quarterback like Mahomes this season. But they did just defeat Jordan Love in the wild-card round, Super Bowl champion and likely future Hall of Famer Matthew Stafford in the divisional round and likely Offensive Rookie of the Year Jayden Daniels in the NFC title game. Yes, Mahomes presents a different challenge, but it's safe to say that the Eagles' defense is more prepared to face the Chiefs' offense than the Chiefs' offense is to face them. 

Specifically, the Eagles' pass rush has the ability to pressure Mahomes, which we all know is the blueprint for how to stop him. Just as Spagnuolo is likely coming up with ways to try to contain Barkley, you can assume that Eagles defensive coordinator Vic Fangio is devising ways to pressure Mahomes similarly to how the Buccaneers did when they beat the Chiefs in Super Bowl LV. 

Kansas City's line was in shambles then, so it'll be harder to pressure Mahomes in this game. But as noted earlier, the Eagles have the pass rushers (specifically Josh Sweat, Nolan Smith and Jalen Carter) to win more than their share of matchups against the Chiefs' talented offensive line. The Eagles' defense also features one of the game's best linebackers in Zack Baun and an opportunistic secondary, led by C.J. Gardner-Johnson, who could find himself on the receiving end of an errant Mahomes pass on Feb. 9. 

There have been several notable upsets in Super Bowls past. Each time, the team that pulled off the upset had a clutch quarterback, a physical, productive running game and an aggressive defense that put pressure on the quarterback, thus leading to turnovers.

Get the winning Side and Total in this match-up and be the one bragging Monday Morning that you won big at the SuperBowl this year. $200 is a small price to pay for this valuable information. 

• Been up since 4am this morning going through the numbers on some games and have been using AI to help me do deep dives on teams a lot faster. Now I get it that AI doesn't play baseball but I'm using it strictly to help me find edges on 14 or 15 games and I don't have time to go through it with a magnifying glass. This is 2025 not 1991 and AI is here whether we like it or not. 

  One of the games that has been heavily researched this morning comes in the form of Cubs/Brewers. Statistics are regarded and disregarded by me as a human based on 40 years of watching sports and 30 years of being a sports handicapper. My brain works a certain way. I'm enjoying the way the AI finds things that I can expand on and like I said some gems in the form of betting information thanks to my artificial friend. 

   

  • Shota Imanaga's Dominance – Since the 2024 season, Imanaga's team has an incredible 13-0 record when facing National League teams with a slugging percentage of .390 or worse. That’s a 100% win rate!

  • Peralta’s Home Strength – Freddy Peralta has been nearly untouchable at home, boasting an ERA of just 0.69 in home games this season. In those starts, he’s allowed only one earned run across 13 innings.

  • Imanaga’s Road Success – Imanaga is undefeated in away games this season, holding an ERA of 0.53. He’s given up only one earned run across 17 innings.

  • Shota Imanaga's Dominance: Since the 2024 season, whenever Imanaga's team faces a National League opponent with a batting average of .245 or worse, his team has gone 12-0. That’s an impressive undefeated streak in those conditions!  

  • Imanaga vs. Low-Power Teams: When pitching against teams averaging fewer than 2.75 extra-base hits per game, Imanaga's team boasts an astounding 15-1 record. His ability to neutralize weaker-hitting offenses gives his team a significant edge.  

  • Peralta's Strikeout Power: Freddy Peralta has struck out 41 batters in just 39.3 innings this season, averaging more than one strikeout per inning. His ability to get batters swinging and missing makes him a tough challenge.  

  • CategoryPeraltaImanaga

    Record3-23-1

    ERA2.522.77

    Innings Pitched39.139.0

    Strikeouts4130

    WHIP1.071.13

    K/99.46.9

    BB/93.203.00

    Opponent AVG.196.214

    Quality Starts22

    Recent Outing6 innings, 2 earned runs5 scoreless innings

    Team Record in Starts4-34-3

    Pitch ArsenalFastball, Changeup, Curveball, SliderFour-seam Fastball, Splitter, Slider

  • Chicago Cubs Bullpen Overview

    The Cubs’ bullpen has been a bit of a mixed bag this season. They showcase flashes of solid relief work from standouts like Ryan Pressly, who has posted a 2.08 ERA in his outings and offers promising underlying metrics such as controlled home run rates (around 1.9%) and a respectable strikeout-to-walk ratio. However, this strength is offset by seams of inconsistency. Other relievers have struggled significantly—players like Jordan Wicks have seen ERA numbers as high as 13.50, and additional arms are sidelined by injuries (for example, Justin Steele and others on the injured list). Recent reports even cite an overall bullpen ERA hovering around 4.81, underscoring that while there are bright spots, the overall picture remains unstable and highly dependent on the few reliable voices in the rotation of relievers .

    Milwaukee Brewers Bullpen Overview and Sabermetric Breakdown

    In contrast, the Brewers’ bullpen presents a more cohesive and consistent picture—a factor that could prove vital over the course of a long season.

    Key Traditional Metrics

    • ERA and WHIP: The core group of Brewers relievers are posting ERAs typically in the mid-3 range with WHIP figures clustering around 1.18 to 1.33. For instance, according to projections:

      • Jared Koenig has an ERA of 3.71 with a WHIP of 1.25 over about 63 innings.

      • Joel Payamps is delivering a 3.54 ERA with a 1.18 WHIP in roughly 61 innings.

      • Bryan Hudson stands out with a 3.36 ERA and a WHIP near 1.19 over 59 innings.

      The consistency across these numbers reflects a bullpen that is not only durable—with most pitchers averaging 55–65 innings of work—but also one that effectively limits baserunners and damage in crucial late-game situations.

    Advanced Sabermetric Insights

    Delving into deeper metrics reveals why the Brewers’ bullpen might be considered superior:

    • Expected ERA (xERA) & Fielding-Independent Pitching (FIP): These metrics suggest that beyond the traditional ERA, the Brewers are doing a solid job of preventing big innings. Lower xERA numbers imply that, even if some relievers face a statistical anomaly on a given night, the underlying performance levels are healthy. In many cases, the advanced numbers (with xERA and FIP projections in the low-to-mid 3’s for key arms) indicate effective run prevention without an over-reliance on luck or defensive support.

    • Strikeout-to-Walk Ratios and Home Run Rates: The Brewers’ relievers also tend to generate quality strikeouts while keeping drawn walks in check. Their cumulative HR percentages are kept low, reducing the likelihood of sudden, costly runs. For example, in the aggregated sabermetric profiles, the best portions of their bullpen display controlled HR and balanced strikeout-to-walk ratios—a recipe for stability in high-leverage situations.

    • Usage and Longevity: With a well-distributed workload among several arms, the Brewers mitigate the risk of overuse and maintain consistency throughout their bullpen. This distribution is crucial, especially when injuries or a heavy schedule come into play. Advanced metrics underscore that such balance—not having one or two workhorses carrying the load—often translates to a lower variances in performance game-to-game.

    In summary, while both bullpens have their stories, the detailed sabermetric data shows that the Brewers’ bullpen is more consistent and efficient, especially in a relief role where every inning pitched can be critical. Their blend of stable traditional numbers (ERA and WHIP) along with favorable advanced metrics (xERA, FIP, and controlled HR rates) sets a foundation that could provide a decisive edge in late-game situations

  • In conclusion with the lightning quick research ability of my imaginary artificial friend, I have to conclude that with these two hillbillies on the mound that the game will be a low scoring affair. So, the play here is most definitely the UNDER for the first five innings which right now is set at a flat 4 at -120 odds. You may want to try alternate spreads and see if you can get the game UNDER 3.5 for geeked juice odds. At 3.5 you are looking at + money instead of -120. ENjoy the huge slate today and check the website daily for free information and videos. 

Going through the data this morning I identified a play in MLB that is backed up statistically and gives us a high probability of cashing. I actually had this game on my radar since Thursday when I was reviewing the weekend match-ups and now that I can access today's data for all the games this was the one that jumped off the page again. These two pitchers are terrible. They have bad numbers to begin with but when you search the advanced sabermetric data you see that the underlying numbers reveal a bigger story.  My goal here at VIP is to provide edge for my clients. To give them the highest probability of success. This matchup today between the Blue Jays and the Mariners check the boxes in so many spots it is hard not to ride with this play. This will be my VIP Elite Play of the Week and this will be a max unit play for me. 

Below is a detailed summary that ties together multiple strands of the provided data and sabermetric insights to back up the idea that these starting pitchers create a high probability of the game going over eight total runs.

Advanced Pitching Metrics Signal Elevated Run Production

High Expected Run Allowance:  When you examine the advanced metrics for pitchers like Bowden Francis and Logan Evans, you see numbers that suggest they’re giving up more than what their basic ERA might imply. For instance, Bowden Francis posts an ERA of about 6.17 while his Fielding Independent Pitching (FIP) and similar predictors (dERA, DICE, SIERA) hover around 6.79. In sabermetrics, when a pitcher’s FIP exceeds his ERA this markedly, it signals that he might have benefited from above-average defense or some favorable variance—and that his underlying performance actually points to higher run allowance. This discrepancy is a red flag; it indicates that the pitcher's true run?allowance potential is higher, thereby increasing the likelihood that a game they start will see more runs scored than expected.

Comparative Metrics Across Game Conditions:  A closer look across different conditions (like night games versus daytime or home versus away) reinforces this outlook. For instance, during night games the metrics for these pitchers become even more inflated—Bowden Francis’s night game numbers show xERA and dERA rising to figures near 7.80–8.74. This type of shift suggests that the conditions further amplify the run?allowing tendencies, hinting that the environment and matchup context are ripe for higher scoring affairs. Such trends indicate that not only are these pitchers individually prone to allow more runs based on their sabermetric profiles, but the game conditions they face can push totals well over the eight-run threshold.

Betting Records and Historical Over Trends

Consistent Over/Under Production:  The betting records in the data set tell a complementary story. When the total line is set in the range of eight to 8.5 runs, both the overall and specific situational betting outcomes reveal a noticeable tilt toward the “over” side. For example, team betting records linked to these pitchers show that in certain categories—whether measured by overall game performance or by specific conditions such as road games—the unit returns when betting the over have been either positive or, in some cases, very balanced in a way that hints at an undervalued market inefficiency. In simple terms, the historical lines indicate that when these pitchers take the mound, teams have frequently exceeded the 8-run mark. Even when accounting for losses, the “over” has been present on multiple occasions, suggesting that the effect isn’t a fluke but part of a larger, recurring pattern.

Integration of Sabermetrics with Market Trends:  What strengthens the case is the convergence of statistical insight with market behavior. The sabermetric data (e.g., the elevated FIP relative to ERA) indicates a natural regression where a pitcher who might be “lucky” in preventing runs eventually gives up more as his underlying skills are exposed over time. Meanwhile, the recorded betting trends confirm that the market—perhaps influenced by superficial metrics—has consistently underpriced this regression effect. When you combine the two, it paints a clear picture: the matchups tend to produce more runs than the public odds might hint, thereby providing a betting edge on the over for totals set around eight runs.

Contextual Considerations

Although individual pitcher performance is a major factor, it’s also valuable to consider the broader matchup context. The data set often includes records against specific types of opponents or in settings where offense is particularly potent. For example, when these pitchers face teams with strong offensive profiles or under conditions that amplify scoring, the likelihood of hitting an “over” becomes even more pronounced.

This detailed alignment of advanced metrics, historical over/under results, and contextual matchup factors builds a strong case: the underlying sabermetric evidence and historical trends suggest that these pitchers’ outings are highly correlated with high-scoring games—making it a data-backed proposition that the game is more likely to go over the eight-run total.

Below is a summary of overall “combined average” of key sabermetric metrics for the two pitchers. For some splits only one pitcher’s data is available, so those rows reflect the available values. In the rows where both pitchers have data (All Games, League, and Over the Last Month), the values are the simple averages of the two. All values are rounded to two decimals for clarity.

How These Averages Were Derived

1. All Games & League Games:  Both pitchers have complete data. For example, the All Games ERA is calculated as: • Francis: 6.17  • Evans: 7.20  • Combined average: (6.17 + 7.20) / 2 ≈ 6.69. The same averaging method was applied for xERA, ERC, FIP, dERA, DICE, SIERA, and HR%.

2. Home Games:  For Evans the home splits are available (ERA?=?3.60, xERA?=?2.51, ERC?=?2.06, FIP?=?6.30, dERA?=?6.61, DICE?=?6.30, SIERA?=?6.39, HR%?=?5.30%). In this instance Francis’s home game data wasn’t provided, so the table reflects Evans’s values directly.

3. Away Games:  Francis’s away splits are available (ERA?=?5.74, xERA?=?5.59, ERC?=?5.58, FIP?=?5.08, dERA?=?4.87, DICE?=?5.08, SIERA?=?5.06, HR%?=?4.50%), while Evans’s away data isn’t separately broken out. Thus, the away row reflects Francis’s numbers.

4. Night Games:  Only Francis’s night game data is available (ERA?=?5.95, xERA?=?7.80, ERC?=?7.42, FIP?=?8.74, dERA?=?8.48, DICE?=?8.74, SIERA?=?8.74, HR%?=?10.80%), so that row shows his numbers.

5. Over the Last Month:  Here both pitchers have values, even though Evans’s “last month” numbers mirror his All/League results. The averages are computed using: • Francis: ERA?=?7.61, xERA?=?7.76, ERC?=?7.56, FIP?=?7.54, dERA?=?7.11, DICE?=?7.54, SIERA?=?7.52, HR%?=?8.80% • Evans: ERA?=?7.20, xERA?=?6.05, ERC?=?6.25, FIP?=?4.30, dERA?=?4.22, DICE?=?4.30, SIERA?=?4.28, HR%?=?2.20% For example, the combined ERA over the last month is (7.61 + 7.20) / 2 ≈ 7.41.

Final Thoughts

This overall summary table helps visualize where the combined pitching tendencies lean under different conditions—especially noting that Francis’s night outings are associated with significantly worse underlying numbers (and a higher HR%) that could drive the game totals well above the eight-run mark. Similarly, while Evans shows a very contained home performance, his overall league numbers still reflect the potential for higher scoring when averaged against Francis’s data. 

The VIP Elite Play of the Week will obviously be TOR/SEA OVER 8 at -110 odds. Hopefully the numbers provide you with a basis for a safe bet and feel free to hammer the shit out of this play. 

Doing the numbers on Arizona vs San Fran I started out with the pitching matchup and saw it was Kelly vs. Verlander. Now Verlander of 2025 is not Verlander of 2014 and although he still can produce, he is 42 and has lost the magic he had a decade ago. The first simulation I ran was describing the batting metrics of both teams against "average pitchers" which goes through a database and determines average pitcher stats against the advanced metrics of both teams' bats. In the first simulation the clear-cut advantage belonged to the Arizona Diamondbacks. I ran another simulation with the same batting metrics cross referenced with the starting pitchers of Arizona and San Fran. The simulation took into account the career numbers for Verlander and placed him in the category of an elite suppressor, giving the Giants the advantage. Then I ran the simulation with the pitching splits for both starters in recent games and added criteria like over the last month, this season, and other relevant splits like division games and home and away scenarios. The data received produced a different classification for Verlander and placed him a few notches down into the category of average. His recent outings have been just that. Average. The additional cross referencing returned the advantage to Arizona. 

Below is a step-by-step breakdown:

. OPS+ and Overall Production

Arizona’s hitters include several key players with elite OPS+ numbers—values that measure production relative to the league average (with 100 being average). For instance, players like:

• Pavin Smith (OPS+ around 178),

• Ketel Marte (OPS+ around 163), and

• Corbin Carroll (OPS+ near 156)

illustrate that multiple batters in the Arizona group are producing 50% or more above league average. In contrast, San Francisco’s core hitters tend to cluster in the 120?130 OPS+ range (e.g., Mike Yastrzemski at 133, Jung Hoo Lee at 123, and Matt Chapman around 126) with several supporting players posting below-average numbers. Against an average pitcher, Arizona’s hitters have a built-in edge; for every 100 runs expected from a league-average lineup, Arizona’s top batters could add an extra 50–70% in production.

2. wOBA and Run-Creation

Beyond OPS+, metrics like weighted On?Base Average (wOBA) and weighted Runs Created Plus (wRC+) are designed to account for both opportunity and the value of each plate appearance. Arizona’s advanced stats show higher wOBA values for its elite hitters—meaning that every plate appearance is more effective in producing runs. Elevated wRC+ numbers further confirm that Arizona’s hitters turn their chances into runs at rates significantly above the norm. In a matchup against an average pitching attack, those advantages mean that Arizona’s lineup is more likely to generate extra-base hits and capitalize on scoring opportunities.

3. Consistency and Depth

While San Francisco does have a couple of solid contributors, the overall depth of Arizona’s lineup—with multiple players consistently performing well above average—suggests that against average pitching, Arizona will have more opportunities to exploit favorable matchups. The combination of high OPS+ and superior run-creation metrics means that even if one player has an off day, the collective strength of the group helps maintain an edge.

Conclusion

In summary, when facing average pitching, the advanced metrics suggest that Arizona’s hitters are built to produce significantly more than league norms. Their high OPS+ values and strong wOBA/wRC+ numbers translate to an increased likelihood of run production. This elevated offensive efficiency provides a clear advantage over San Francisco’s group when matched up against a pitcher delivering average performance.

Let's take the advanced offensive profiles for each team—originally measured against average pitching—and overlay adjustments based on the expected suppression (or lack thereof) from the opposing starting pitchers. In this matchup, Arizona’s lineup (which shows higher advanced numbers against average pitching) will be facing San Francisco’s ace, Justin Verlander, while San Francisco’s hitters will contend with Arizona’s starter, Merrill Kelly. Here’s how we can break it down:

1. Baseline Versus Average Pitching

Before adjustment, the advanced stats indicate that Arizona’s hitters have a significant edge against average pitching—for example, with many key players posting OPS+ numbers in the 156–178 range. In contrast, San Francisco’s core hitters generally register OPS+ in the low 120s to mid?130s. In other words, if both teams were facing “average” pitchers, Arizona’s offensive production would be expected to outpace that of San Francisco.

2. Incorporating Pitcher Quality

Justin Verlander (SF’s starter): Verlander’s current performance leans on elite command and suppression. When an elite pitcher is in the battle, a lineup—even one that is generally potent—often suffers a drop in production relative to its average. You might estimate that an elite arm like Verlander’s could depress available advanced metrics by roughly 15–20%.

Merrill Kelly (Arizona’s starter): Kelly’s numbers this season (for example, an ERA around 4.09 with modest strikeout rates) suggest he’s closer to an “average—or slightly below average” pitcher. Against such a pitcher, a lineup typically performs near or even a few percentage points above its baseline due to less effective suppression. We might estimate a boost or minimal reduction in the range of 0–5%.

3. Adjusting the Effective Offensive Advantage

Let’s use a simplified example based on a hypothetical advanced metric like wRC+:

Team’s Baseline (vs. Avg Pitching)

Adjustment Factor

Effective wRC+

Arizona’s Hitters: ~150

× 0.85 (15%–20% suppression by Verlander)

~128

San Francisco’s Hitters: ~130

× 1.05 (minimal drop, maybe a slight boost vs. Kelly)

~137

Under these assumptions, although Arizona’s hitters would normally be expected to excel against an average pitcher, facing Verlander reduces their effective production. Meanwhile, SF’s hitters see less suppression from Kelly (or even a slight relative boost), which brings their effective offensive metric up to or above parity. In this simplified model, San Francisco’s adjusted numbers edge ahead even though against average pitching Arizona would have the advantage.

4. Implications for Strategy and Wagering

• For Arizona’s hitters: While they’re typically more advanced against average pitching, going up against a proven suppressor like Verlander means betting models—whether for totals or hitter-specific prop bets—should reduce expectations. This might lead to more favorable odds on under bets for Arizona’s scoring in the context of Verlander’s involvement.

• For San Francisco’s hitters: Although they might seem less potent on paper, facing a pitcher like Kelly (who doesn’t offer the same level of suppression) may enable them to perform closer to, or even slightly above, their standard line. This adjustment might present wagering edges on over/positive production props for SF’s hitters.

Final Thoughts

By adjusting the advanced hitting statistics with the quality of the starting pitchers, the initial advantage seen with Arizona’s lineup against average pitching becomes significantly eroded when they face Justin Verlander. Meanwhile, San Francisco’s hitters—when matched up against Merrill Kelly—can perform at a higher effective level than the average model would predict. This matchup suggests that wagering strategies should focus on the suppression effects: consider under bets for Arizona’s scoring (or Arizona’s total output) and be open to value in SF hitter props, given that Kelly’s numbers may not suppress production as much.

Let’s break down how we can reframe the matchup by adjusting the “suppression effect” using recent splits for Justin Verlander, then cross-referencing those numbers with our earlier advanced batting data.

1. Establishing the Baseline

In our earlier analysis versus average pitching, we assumed that Arizona’s hitters—who boast elite figures (with OPS+ values in the 156–178 range and high run?creation metrics)—would get a big boost. On average, we might think of Arizona’s offensive metric as around 160 when facing an average pitcher, while San Francisco’s hitters are more in the 130 range.

In the initial model, when we imagined Verlander as an elite suppressor, we applied a heavy adjustment factor. For example, using a 15% suppression effect (multiplying by 0.85) would reduce Arizona’s effective metric from 160 to about 136. That would nearly neutralize their advantage.

2. Adjusting for Verlander’s Recent Splits

However, when we look at the recent splits for Justin Verlander, the data tell a different story:

• His 2025 numbers show an ERA around 4.7 with a WHIP of roughly 1.31, and his recent starts have produced mixed results (a couple of losses with moderate run support, modest strikeout rates, and betting trends that aren’t overwhelmingly positive).

• These splits suggest Verlander is performing more at an average level rather than providing elite suppression.

If we adjust our suppression factor accordingly—say, using only a 5% effect (a factor of about 0.95) instead of 0.85—the effective impact on Arizona’s hitters would be much less. That is:

Effective Arizona metric versus Verlander = 160 × 0.95 ≈ 152

In contrast, San Francisco’s hitters face Merrill Kelly, whose recent splits indicate a near-average (or slightly below average) pitcher. In our earlier model we even assumed Kelly might have a negligible or slight boosting effect on his hitters (for example, a factor around 1.05). That yields:

Effective SF metric versus Kelly = 130 × 1.05 ≈ 136.5

3. Cross?Referencing with the Batting Data

To put these numbers in perspective, here’s a simple table summarizing the adjustments:

Team’s Baseline (vs. Avg Pitching)

Adjustment Factor

Effective Metric

Arizona’s Hitters (Baseline ~160)

0.95 (vs. Verlander’s average)

~152

SF’s Hitters (Baseline ~130)

1.05 (vs. Kelly’s minimal suppression)

~136.5

Originally, if Verlander had been elite, Arizona’s advantage could have been wiped out. Instead, with his recent splits showing he’s about average, Arizona’s hitters get a healthy effective boost—about 15 points above their SF counterparts. This suggests that when Verlander is on the mound, Arizona’s advanced hitting traits can more fully express themselves.

4. Projecting the Possible Edge

What does this translate into for the matchup?

• For Arizona’s offense: With an effective offensive metric of around 152, Arizona’s bats are projected to produce significantly above league average—even when corrected for pitcher quality. This suggests they’re likely to generate extra-base hits and maintain a higher run production in this game.

• For wagering implications: Such a projected edge could translate into value for bets on Arizona’s offensive production, such as over bets on run totals or hitter-specific production props. In contrast, SF’s hitters—dented by facing Kelly—get an effective metric around 136.5, a noticeable gap favoring Arizona.

Thus, by adjusting the suppression effect on Arizona’s hitters from 15% to just 5% (in light of Verlander’s recent average-level performance), we project that Arizona holds a clear offensive edge. This cross-referenced approach—using both advanced batting data and the latest pitcher splits—shifts the narrative: rather than Verlander negating Arizona’s edge, his current form suggests that Arizona’s hitters should perform well above expectations.

1. Establishing the Baseline

• Offensive Metrics vs. Average Pitching: Under average conditions, our data show that Arizona’s hitters post elite numbers (with OPS+ ranging roughly from 156–178) and an effective baseline offensive metric of about 160. In contrast, San Francisco’s hitters generally operate around an effective level of 130.

2. The Initial Suppression Hypothesis

• We initially assumed that San Francisco’s starter, Justin Verlander, would impose a significant suppression effect—roughly a 15% reduction on offensive production. Under that scenario, Arizona’s effective metric would drop from 160 to around 136, nearly erasing their edge.

3. Adjusting Using Recent Splits

• Recent Data on Verlander: Reviewing Verlander’s latest splits shows an ERA near 4.7 and a WHIP around 1.31. These figures indicate he’s performing at an average level—not the elite suppressor we once expected.

• Revised Suppression Factor: Based on these splits, our model now applies only a 5% suppression effect—multiplying Arizona’s baseline metric by 0.95. This adjustment brings Arizona’s effective offensive metric to approximately 152 rather than 136.

4. Cross-Referencing with Merrill Kelly’s Data

• Facing Merrill Kelly: On the other side, San Francisco’s hitters contend with Merrill Kelly, whose numbers suggest minimal suppression (or even a slight boost, roughly a factor of 1.05). This adjustment pushes SF’s effective metric to about 136.5.

• Resulting Offensive Gap: With the revised adjustments, Arizona’s effective offensive metric sits around 152 compared to SF’s 136.5—a clear 15-point advantage.

5. Wagering Strategies & Takeaways

• Actionable Betting Insights:

  • The preserved 15-point edge in Arizona’s favor indicates that their hitters should be able to generate significantly above-average production—even against a pitcher like Verlander playing at an average level.

  • For wagering purposes, this suggests that bets on over/under run totals and specific hitter production props in Arizona’s favor are particularly compelling.

• Final Thought: By recalibrating our model to account for Verlander’s recent average-level performance, the offensive advantage for Arizona remains robust. This integration of advanced metrics and freshly adjusted splits provides a powerful, actionable framework for positioning our bets wisely.

The play tonight is the Arizona Diamondbacks on the money line at -113

This morning I was reviewing the matchups for the games today and saw an absolute gem of a pitching matchup tonight between Max Fried and Brian Woo in the block of late games. There were a few matchups that caught my eye, but staying on task here and using the logic behind the play we cashed yesterday, I want to further expand on the effect of Suppression Rates vs. OPS+.

Tonight's matchup offers two of the best starting pitchers in baseball, along with some of the best hitters the game has across the board. To test the theory of suppression vs. OPS+ that produces an above average unit profitability in MLB gambling, I am going to provide an in-depth look at suppression and adjusted OPS+ numbers using the top pitching vs. the top hitting teams in MLB. While yesterday provided an opportunity to reduce an aging pitcher's past performance against public perception, tonight's match-up gives us a real-time view of the effect of suppression and why I factor this into my daily handicapping arsenal. I made a video yesterday explaining this effect and will also provide another video later today on YouTube explaining the effect of suppression pertinent to tonight's matchup.

Max Fried

Traditional Metrics & Current Output:  Fried’s current sample is nothing short of elite. Posting a 6–0 record with a season ERA of just 1.05 over roughly 51.7 innings, he’s been exceptionally efficient. His quality-start percentage (QS%) of 75% and an overall WHIP of 0.910 signal that he’s not only limiting baserunners but doing so at an extraordinary rate. In his split for away games—even though the sample is small—he posted an ERA around 0.44, highlighting that his dominant numbers aren’t just home-field artifacts.

Advanced Metrics & Underlying Skill Indicators:  When we break his performance down using fielding-independent metrics, Fried’s numbers still shine—even if they suggest a modest regression relative to his raw ERA. His FIP (Fielding Independent Pitching), dERA, and SIERA all sit around 2.91. In sabermetric terms, while his actual ERA is unusually low, his FIP indicates that much of his success has come from factors within his control (like strikeouts, walks, and home run prevention) while perhaps benefiting from above-average defense or a bit of luck on fly balls. His extremely low home run rate (HR% at 1.4%) further suggests he’s efficiently limiting the most damaging batted-ball outcomes. His xERA of 1.84 and ERC of 1.75 also reinforce that the expected rate of run prevention is dramatically below league average, supporting the idea that even if regression occurs, Fried should continue to be well under a three-run “projected” ERA. Finally, the team betting records—where his starts have helped his team achieve an 8–0 money line mark—reflect the market’s confidence in his ability to control games.

Projection:  Even if regression nudges his ERA closer to his FIP, Fried is projected to remain an elite asset. One might expect his future outings to settle in the low-to-mid 2.00s ERA range, still well below the league average. His combination of excellent command, low walk rates (~5.3%), and minimal home-run giving make him one of those pitchers who, on a sustained basis, should continue to deliver high-leverage, low-run games.

Bryan Woo

Traditional Metrics & Current Output:  Woo’s numbers, while solid, present a slightly different picture. He’s sporting a 4–1 record with a 3.25 ERA over approximately 44.3 innings. His WHIP of 0.925 is almost as tight as Fried’s, and his strikeout rate is roughly comparable—indicating that his ability to miss bats is on par. Notably, his home game performance is particularly impressive; posting an ERA of 1.38 over a couple of starts at home suggests that venue factors and defensive support can sometimes help him shine.

Advanced Metrics & What They Reveal:  Diving deeper, Woo’s advanced metrics hint that his peripheral numbers are better than his raw ERA might indicate. His xERA (2.27) and ERC (1.87) are substantially lower than his 3.25 ERA, while his FIP of 2.90 aligns very closely with what we see in Fried’s profile. These advanced numbers imply that Woo’s underlying performance—through effective strikeouts, a low rate of walks (around 4.6%), and a decent HR% (2.3%)—is not fully reflected in his earned runs. In sabermetric terms, this gap often signals an expectation of regression; the factors within his control suggest that, over time and with consistent defensive support, his ERA could gravitate closer to the 2.90 range. His consistency at the plate (as evidenced by his relatively low OBP allowed) and solid ratios across his plate discipline metrics give us reason to project that his current ERA is a bit of an outlier.

Projection:  For Woo, the advanced metrics support a projection where he should improve his run prevention to match his FIP. In other words, if his defense remains stable and he continues to pitch with his current command and sequencing, we’d expect his ERA to dip by a point or so over a larger sample size—likely aligning him near the 2.9 mark. In betting terms, while his team records aren’t as overwhelmingly positive as Fried’s, the underlying tools indicate that Woo is a reliable starter who could be poised for a breakout or, more accurately, a regression to his more efficient underlying numbers.

Comparative Summary & Further Considerations

• Rate Efficiency: Both pitchers show similar command in terms of strikeout and walk rates, but Fried’s extremely low ERA (and low HR%) currently sets him apart. Even though both pitchers have FIP values hovering around 2.90, Fried’s current performance (and associated market valuations, as reflected in team betting records) suggests he’s been particularly adept at converting his underlying skills into game outcomes, albeit with a bit of “extra” defense or luck.

• Projection Reconciliation:

  • Max Fried: Expect his current dominance—if slightly tempered over time by regression—to remain among the top-tier performances in the rotation. The advanced metrics project him at roughly a low-to-mid 2.00s ERA level when accounting for regression, though he’s already trending far below that mark.

  • Bryan Woo: The gap between his actual ERA and his expected numbers suggests he’s due for improvement. A consolidation of his underlying performance should bring him closer to that 2.90 mark, making him a very effective starter once sample sizes stabilize.

• Additional Insights:  A further deep dive would look at pitch sequencing, batted-ball profiles (such as ground-ball/fly-ball ratios), and park effects. Moreover, contextual factors like the quality of defensive support behind each pitcher can explain some of the variances between raw and advanced numbers. Future analyses might also compare their performance against different opponent lineups to further isolate their intrinsic value.

Both pitchers exhibit high-level underlying skills. Fried currently converts his tools into nearly historic numbers, even if some of that might normalize over a longer season. Woo, likewise, has the makings of an elite starter—the sabermetrics point to a pitcher whose true talent is just waiting to be fully reflected in the box score.

Let's break down what OPS+ numbers tell us about each team’s offensive lineup. OPS+ is a normalized version of a player’s on-base plus slugging percentage that adjusts for both league average and ballpark effects—with a value of 100 representing exactly league-average production. Numbers above 100 indicate better-than-average offensive performance (for example, an OPS+ of 150 means the hitter is producing 50% more than an average hitter when adjusted for context), and numbers below 100 indicate production that lags behind league norms .

New York Yankees

Looking at the Yankees’ projected starters:

• Aaron Judge (OPS+ 255): His explosive 255 OPS+ is an elite figure in baseball. It indicates that Judge is generating offensive value at a rate that’s 155% above league average. This isn’t just the product of power; his ability to combine high slugging with excellent plate discipline makes him a cornerstone for run production each game.

• Paul Goldschmidt (OPS+ 154): With an OPS+ of 154, Goldschmidt is producing 54% above the league average. His numbers suggest that he’s a consistent run creator, combining both power and on-base skills to be a significant offensive catalyst.

• Jasson Dominguez (OPS+ 123): Ticking in at 123 means Dominguez is about 23% above average. This level indicates good power and plate discipline—especially promising for a developing talent—providing solid run production in his spot of the order.

• Austin Wells and Anthony Volpe (OPS+ 108 each): An OPS+ of 108 means these young players are roughly 8% above average. They offer incremental value on either side of the order by generating modest extra production relative to the baseline.

• Jazz Chisholm (OPS+ 101): Nearly exactly average at 101, Chisholm’s numbers suggest that—while he might not be doing anything spectacular from an OPS perspective—he’s a stable, reliable contributor.

• Oswaldo Cabrera (OPS+ 80) and Cody Bellinger (OPS+ 90): These figures are below the league average (20% and 10% below, respectively), signaling potential issues in either their ability to get on base or to hit for power. While they may be filling positional needs or providing defensive value, their offensive production likely won’t boost the overall lineup as much.