Models trying to pin down a player’s odds of making the Hall of Fame have started to pop up in all sorts of corners of sports analytics. Teams want them. Fans too, and it wouldn’t be surprising if some players spend a night or two wondering what drives those final, mysterious decisions. Still, the reality is trickier than those outputs might suggest, statistics can hint at likely results, but when the doors close on those voting rooms, things get more complicated. 

Modern probability tools provide plenty of sophistication, yet, when it comes to induction, everything ultimately hinges on cut-and-dried thresholds and lots of subjectivity. Each method scratches the surface in different ways, but none quite reach the whole truth.

Foundations of Hall of Fame Probability Modeling

Most of the popular Hall of Fame projection tools seem to lean quite a bit on logistic regression (it’s the default, at this point). That approach munches through layers of player info, think WAR, awarded wins, whatever records, and spits out something not unlike a percentage chance, technically squeezing it between 0 and 1. Some folks branch out into machine learning, tossing in random forests or neural networks, just in case there’s a non-linear pattern hiding somewhere, which, occasionally, nudges up the prediction rates.

For example, Statitudes had Jaromir Jagr almost locked in as a future Hockey Hall of Famer. MLB? Candidates creep past the 0.5 mark more often as their trophy shelves fill, at least, that’s what the data trends toward. The usual suspects matter: longevity, steady productivity, and even which year it is. And then you’ve got the soft stuff, like nagging scandals or “intangibles.” These enter quietly, sometimes just a blip, but maybe it’s there all the same. The whole process is reminiscent of online slots, where statistical expectation plays a major role, but the mechanical system has its own inflexible outcomes.

Game Mechanics in Actual Selection

The real Hall of Fame voting, it doesn’t bend for probabilities. It’s cut-and-dry. Baseball’s BBWAA, for instance, expects at least 75% of votes for a player to get in. Voters can check off up to 10 names. Only the ones clearing that strict bar walk away with a plaque. It doesn’t matter if someone lands at 74.9%, the number might be there, but the rules stop you cold. There’s no wiggle room for those “in-between” probabilities (70%, 82%), which show up in tabular models but get ignored at the finish line. 

If you come up short, you’re out, even by a vote. Other leagues, like hockey or football, add layers, panels or committees, different cycles, but the punchline is always the same: you get in, or you don’t. That’s where the rub sits, a model says 0.8 is “overwhelmingly likely,” and meanwhile, a committee can just say, sorry, not tonight. Tension pops up at the edges, too, when a player’s just straddling that imaginary line. It’s all a bit rigid, and maybe that’s part of the drama.

Comparing Analytical Predictions and Selection Outcomes

Running the numbers with probability models gives fans and armchair analysts ammo for endless debates, so-and-so clocks in at 64%, someone else sits at 22%, and on it goes. But the selection process tosses in its own twists. A few players manage to get through after a analytical predictions and selection outcomes, suddenly, they don’t look so borderline. Others with high model marks stall out, stuck on the ballot for years. If you throw the numbers on a chart, you’ll see it: the models stretch across the full decimal spectrum, but the Hall only deals in absolutes, a yes at the league threshold, or a hard no. 

MLB’s bar at 75%? Higher than what most analysts would flag as enough for likely induction (50% pops up in research, but it’s pretty far from the actual cutoff). So, big-picture, the models can be pretty solid for rankings, but predicting the outcome year-to-year, it’s dicey. Especially when something off the field turns the tide for an entire ballot. And, come to think of it, the models themselves are only as sturdy as the history they’re built on, which gets messy whenever the rules, or the broader cultural standards, take a turn.

Dynamics, Limitations, and Evolving Standards

Making sense of Hall induction odds is a bit like playing catch with a moving target. Once the old-guard voters step aside for newer, maybe more stats-savvy folks, the benchmarks drift. The new era and small committee routes sometimes reach back and lift up overlooked players, but at the same time, they add new layers of uncertainty. Even if you train a perfect model on decades of voting, nobody can really promise that those same statistical signposts signal the future. 

Leadership, impact, off-field noise, they slip into consideration now and then, but they’re tough to quantify, let alone nail down. Researchers from Fangraphs and elsewhere have pointed out that what you don’t measure, the “omitted variables”, can skew predictions more than you’d expect. If the focus changes, or a brand-new position gets a champion, the models sometimes lag behind or guess wrong. So, the whole thing, if you step back, tends to look less like a straightforward roll of the dice and more like a living strategy board, shifting and reshaping as new generations put their stamp on the criteria.

Responsible Interpretation and Transparency

Trying to model Hall of Fame odds? It’s somewhat like considering different outcomes on slots or any game that leans into probability, you can point toward the likely outcomes, but there’s no such thing as a guarantee for what any single player will get. It’s wise not to lean too heavily on those model “certainties,” since quirks and blind spots are always hiding around the edges, and the committees running the show are anything but algorithmic. Sharing method details helps push the conversation forward, making arguments about fairness or bias a bit sharper, at least. 

At the same time, recognizing how much human unpredictability goes into the outcome is important, numbers bring clarity, sure, but they’re just one voice in a room full of unpredictable ones. Maybe the best move is to treat these models as conversation starters (and maybe useful guides), not as final word. That way, fans and candidates get insight without the sting of missing out just because the numbers seemed promising.

By the time Week 10 arrives, the NFL feels different. Early-season optimism gives way to the reality of hard-earned truths. 

Teams once dismissed as rebuilding projects start to look dangerous, while others that opened the year with swagger are fighting to stay relevant.

For bettors and fans alike, this is the week when perception finally meets performance.

At this point in the schedule, betting lines are no longer driven by preseason reputation; they’re shaped by evidence. Offensive consistency, defensive depth, and injury resilience now dictate how oddsmakers see the league. 

Week 10 is where the midpoint meets momentum, and the numbers begin to tell stories as compelling as the games themselves.

Fading Myths and Emerging Realities: Teams Rewriting the Storyline

Every NFL season writes its share of surprises, and by Week 10, those surprises become new realities. Teams that stumbled out of the gate are finding rhythm, while others are struggling to live up to the early hype.

The Bears’ Rookie Revolution

Not long ago, Chicago’s offense looked like a work in progress under rookie quarterback Caleb Williams. Fast-forward to Week 9 and a statement win over Cincinnati, which showed flashes of what the future might hold. Williams has settled into a groove, and suddenly, the Bears are favored heading into Week 10.

What’s changed isn’t just execution, it’s confidence. The public is warming up to Chicago’s evolving offense, and oddsmakers are reflecting that optimism with tighter lines and higher totals.

The Texans’ Cooling Hype

Houston opened the season as one of the NFL’s most talked-about stories. C.J. Stroud looked like a future MVP, and bettors bought in quickly. Yet recent weeks serve as a reminder that very few teams ascend in a straight line. 

A rough outing against the Broncos cooled some of the excitement, and their Week 10 meeting with Denver now feels like a referendum on whether the Texans belong in the AFC’s upper tier.

The Commanders’ Quarterback Shock

Washington’s season took a sharp turn when rookie Jayden Daniels suffered a severe arm injury. His spark had given the team life, but now veteran Marcus Mariota is being asked to stabilize an offense in transition. 

Unsurprisingly, the betting markets adjusted immediately, widening spreads and dropping totals for their Week 10 matchup against the Lions.

These shifting storylines are reflected across the betting board, where midseason recalibrations unfold in real time. 

The movement of lines for games like Lions–Commanders or Bears–Giants can be followed through FanDuel Sportsbook, which provides a clear picture of how confidence levels evolve as teams rewrite their identities midstream.

When Health Shapes the Market: The Injury Effect

By November, attrition becomes one of the league’s defining storylines. Every Sunday feels like a survival test, and for bettors, injury reports are as influential as depth charts.

Star players can swing both the emotional and statistical outlook of a matchup. Consider a few of Week 10’s headline injury situations:

• Tyreek Hill (Dolphins): A severe knee injury has his status in doubt, creating uncertainty in a pivotal matchup against Buffalo. If he’s ruled out, Miami’s total points projection could drop significantly, 
• Jayden Daniels (Commanders): His injury is already widening Washington’s spread, a clear indicator of how much value oddsmakers place on a franchise quarterback. 

Injury news, especially for skill-position players, dictates market movement as much as on-field performance.

Reading the Market: How Oddsmakers Adapt to Midseason Trends

The Week 10 board tells a broader story about how markets evolve as data accumulates. Early in the season, bettors chase storylines; by midseason, they’re reacting to patterns.

Three trends stand out as particularly influential this year:

• Road Favorites Are Thriving: Elite teams traveling away from home continue to outperform expectations. Their discipline and consistency make them reliable even in hostile environments, 
• Underdogs Refuse to Fold: Despite the dominance of top-tier squads, underdogs have been resilient against the spread, a sign that parity remains one of the league’s great equalizers, 
• Market Adjustments Tighten Gaps: Oddsmakers have refined their pricing after nine weeks of evidence. Inflated lines for overhyped teams like Dallas or Denver have given way to more measured assessments.

These evolving dynamics align closely with ongoing analytical work, such as key NFL props and predictions this week, which highlight how team efficiency metrics, player usage, and matchups are recalibrated as the season matures. 

Together, they show how fluid, yet logical, the betting landscape becomes by midseason.

The Global Spotlight: Berlin’s Game Adds a New Dimension

Week 10’s international game brings another layer of intrigue. The Falcons and Colts square off in Berlin’s Olympic Stadium, a venue steeped in history and energy. For players, it’s a logistical curveball; for oddsmakers, it’s a study in unpredictability.

Travel, time zones, and routine disruption can subtly impact performance. Teams arriving early may benefit from extra rest, while others struggle to adjust to European schedules. The neutral crowd also affects the atmosphere, neither home-field advantage nor total detachment, just a unique mix of global fandom.

These games often produce surprising outcomes, reminding everyone that context matters as much as raw talent. 

Week 10’s Berlin matchup is both spectacle and test, a rare blend of culture and competition that influences how sportsbooks shape their lines.

The Midseason Reality Check

By the time Week 10 wraps, the NFL will have drawn a new map of credibility. Contenders will look more defined, pretenders exposed, and the betting landscape more grounded in evidence rather than emotion.

The midpoint of the season isn’t about who can reinvent themselves overnight; it’s about which teams sustain growth while navigating adversity. For fans tracking the ebb and flow of odds and narratives, Week 10 offers something better than prediction: perspective.

Momentum, health, and consistency now carry more weight than hype. Whether it’s the Bears’ emergence, the Texans’ recalibration, or the unpredictability of Berlin, the NFL’s second half promises to keep rewriting what we thought we knew, one line, one trend, and one Sunday at a time.

*Content reflects information available as of 03/11/2025; subject to change

The Baseball Hall of Fame has announced the eight names who will be on the Contemporary Baseball Era ballot.  This Era focuses on players whose primary contributions occurred after 1980.

To gain induction, the candidate must receive 75% of the ballots cast among the 16-member committee.  That committee has yet to be announced.

The candidates are:

Barry Bonds, PIT 1986-92 & SF 1993-2007, Outfield.  Bonds is one of the greatest position players the game has ever seen.  The all-time leader in Home Runs (762) also boasts the single-season mark with 73.  The longtime Outfielder is also the all-time leader in bWAR (162.8), Walks (2,558), and MVPs (7), and he won two Batting Titles, 10 OBP Titles, seven Slugging Titles, and nine OPS Titles.  His trophy case also boasts 12 Silver Sluggers and eight Gold Gloves.  Bonds peaked on the regular ballot with 66% in his final year in 2022, and was on the Veterans ballot the year after, though did not receive enough support for his tally to be announced.  His issue, like many, is his suspected PED use, which has kept him out of Cooperstown.

Roger Clemens, BOS, 1984-96, TOR 1997-98, NYY 1999-2003 & 2007, & HOU 2004-06, Pitcher.  Clemens is the Pitching equivalent of Bonds regarding the Hall of Fame, as they joined the modern ballot together, left the modern vote together, and were also on the 2023 Senior Ballot, where, like Bonds, he did not receive enough votes for his tally to be revealed.  Clemens won an MVP, seven Cy Youngs, seven ERA Titles, five Strikeout Titles, and compiled a record of 354-184 with 4,672 Strikeouts.  There is no way anyone on this committee should vote for Bonds without Clemens or vice versa.

Carlos Delgado,  TOR 1993-2004, FLA 2004 & NYM 2006-09, First Base.  Delgado was a two-time All-Star who powered 473 Home Runs with 1,502 RBIs while also securing three Silver Sluggers.  While Delgado did not win an MVP, the Sporting News named him the 2003 Major League Player of the Year.  On the Modern ballot, Delgado lasted only one year (3.8% in 2015), but that ballot included 13 players who made the Hall, including Bonds, Clemens, Kent, Sheffield, Curt Schilling, Mark McGwire, and Sammy Sosa.

Jeff Kent, TOR 1992, NYM 1992-96, CLE 1996, SFG 1997-2002, HOU 2003-04 & LAD 2005-08, Second Base.  A five-time All-Star, Kent won the 2000 NL MVP and earned four Silver Sluggers.  Kent smacked 377 Home Runs with 2,461 Hits and 1,518 RBIs.  On the Modern ballot, Kent finished as high as 46.5% (his last time on the ballot), and this is his Senior ballot debut.

Don Mattingly, NYY, 1982-95, First Base.  Mattingly was one of the best hitters in the 1980s, batting over .300 for six consecutive seasons (1984-89) and winning the 1984 AL Batting Title.  A six-time All-Star and three-time Silver Slugger recipient, Mattingly also won nine Gold Gloves.  Injuries derailed him by 1990, and his Hall of Fame candidacy went off the track with it.  Mattingly still had 2,153 Hits and 222 Home Runs, and he later became a Coach and Manager, and won the 2020 NL Manager of the Year.  The highest he finished on the Modern ballot was his first attempt (28.2% in 2001), but in 2023, on his third Veteran’s ballot, he had 50% of the votes.

Dale Murphy, ATL 1976-87, PHI 1990-92 & COL 1993, Outfield.  Murphy won back-to-back National League MVPs (1982 & 1983), was a two-time Home Run champion, and went yard 398 times.  The seven-time All-Star won four Silver Sluggers, five Gold Gloves, but never made it to 30%.  He has, however, been in the Senior vote three times, and in 2023, he had 37.5% of the tally.

Gary Sheffield, MIL 1988-91, SDP 1992-93, FLA 1993-98, LAD 1998-2001, ATL 2002-03, NYY 2004-05, DET 2007-08, & NYM 2009 Outfield.  A member of the 500 Home Run club (509), Sheffield went to the All-Star game nine times, won five Silver Sluggers, and a Batting Title.  A World Series Champion with the Marlins, Sheffield finished with 63.9% in his final year on the ballot (2024), and is on his first Senior ballot.

Fernando Valenzuela, LAD 1980-90, CAL 1991, BAL 1993, PHI 1994, SDP, 1995-97 & STL 1998, Pitcher,  Fernandomania took over the sports world in 1981, when Valenzuela won the Rookie of the Year, the Cy Young, and led the Dodgers to a World Series win.  He was also a six-time All-Star and had a record of 173-153 with 2,074 Strikeouts.  Previously, he was on the ballot for only two years and had never been on a Senior Ballot.

The results will be announced on December 7 at 7:30 EST on the MLB Network. 

It is with great pleasure that we have brought back the Notinhalloffame MLB Regular Cup, and let us explain how this works:

For every regular-season game, we anointed the top five players with the most points, in descending order: 5-4-3-2-1. 

We know the following:

• The top players for the MLB NIHOF Cup are not always the best in the league, as injuries keep players out of games, and a premium on staying healthy can help pile up points. It also does not hurt to be a top player on an average or mediocre team, as they can amass Cup points more easily than elite players on loaded squads.
• In Baseball, it is more common than in Basketball and Hockey for a player to accrue points with a single Home Run in a game, which favors position players. Starting Pitchers have a hard time with approximately 30-35 Starts and throw fewer innings than previous generations. This is also true for closers not made for this process.
• Please remember that this is NOT necessarily who we think were the best players this year and does not reflect overall consistency. Treat this the way we did: as a fun process and more of a compilation of temporary statistical domination.
• As such, expect it to take time to see Pitchers on this list, or high-average hitters with limited power.

Here are the final standings (and note that we will be adding more of the results over the next few weeks):

1. Shohei Ohtani, Los Angeles Dodgers, Designated Hitter & Pitcher:  220 Cup Points in 158 Games, 1.39 Cup Points per Game.   7.7 bWAR, 146 Runs Scored, 164 Hits, 55 Home Runs, 102 Runs Batted In, 20 Stolen Bases, .282/.392/.622 Slash Line, 1.014 OPS & 179 OPS+.  14 Games, 1-1 Record, 2.87 ERA, 47.0 IP, 62 SO, 145 ERA+, 1.043 WHIP, 6.89 SO/BB.

Who other than a superstar who can accrue points with his bat and on the mound, win the Notinhalloffame Cup?

This is a trophy built for Shohei Ohtani, the only active player in the Majors who plays both ways. Although he threw for only 47 Innings, that is what put him over New York’s Aaron Judge.  Ohtani led the National League in Runs (146), Slugging (.622), OPS (1.014), OPS+ (1.014), and broke his single-season Home Run record with 55 dingers. 

The final week in the standings was a battle between Ohtani and Judge, and while his work as a hurler put him over the top, what Ohtani has done this year and since 2021 has been nothing short of immaculate.

Congratulations to Shohei Ohtani for winning the notinhalloffame.com MLB Cup. 

By the way, the title needs to be accepted in person here at our current home base in Seattle.

2. Aaron Judge, New York Yankees, Outfield:  217 Cup Points in 152 Games, 1.43 Cup Points per Game.  9.7 bWAR, 137 Runs Scored, 179 Hits, 53 Home Runs, 114 Runs Batted In, 12 Stolen Bases, .331/.457/.668 Slash Line, 1.114 OPS & 215 OPS+.

Aaron Judge had the Notinhalloffame Cup locked up, but after bouncing back and forth with Shohei Ohtani, Judge fell in the last two games. However, it is hard to beat a player (for this Cup) when you don’t pitch.  Wait, does that mean Judge is the de facto winner here?   Sadly, no.

Judge had a phenomenal year, where he maintained his power (53 Home Runs) while winning his first Batting Title (.331).  He did not just lead the AL in that stat; he swept the Slash Line, OPS, and OPS+ while also finishing first in Runs (137) and Walks (124).   

The Yankees made it to the playoffs, but could they have done so without Judge?  We doubt it.

3. Cal Raleigh, Seattle Mariners, Catcher:  183 Cup Points in 159 Games, 1.15 Cup Points per Game.  7.3 bWAR, 110 Runs Scored, 147 Hits, 60 Home Runs, 125 Runs Batted In, 14 Stolen Bases, .247/.359/.589 Slash Line, .948 OPS & 169 OPS+.

Is this the best year by a Catcher?  Offensively, yes, it looks like!

Raleigh shattered the Home Run record for a Catcher with 60 taters, and led the AL in that stat and RBIs (125).  “The Big Dumper” was an All-Star for the first time in 2025, and his output propelled the Mariners to a top seed in the 2025 playoffs. 

4. Pete Alonso, New York Mets, First Base: 179 Cup Points in 162 Games, 1.11 Cup Points per Game.  3.4 bWAR, 87 Runs Scored, 170 Hits, 38 Home Runs, 126 Runs Batted In, 1 Stolen Base, .272/.347/.524 Slash Line, .871 OPS & 144 OPS+.

Would you believe that Alonso was at the top of the standings (by far) when we first published our ranking in early May? 

This is arguably the first surprise on this list, as, with all due respect to Alonso, he does not seem like he should be this high, but again, we remind you that this is a point system based on individual games! 

Alonso had a great year, blasting away like always, but this time with a respectable Batting Average of .272 (his best), and a National League leading 41 Doubles. 

Regardless, the biggest news for Alonso is that he opted out of his contract and will likely not be a Met next year.

5. Jose Ramirez, Cleveland Guardians, Third Base:  166 Cup Points in 158 Games.  1.05 Cup Points per Game.  5.8 bWAR, 103 Runs Scored, 168 Hits, 30 Home Runs, 85 Runs Batted In, 44 Stolen Bases, .283/.360/.503 Slash Line, .863 OPS & 137 OPS+.

The story of the improbable Guardians' run to the postseason can not happen without their top gun, and potential Hall of Famer, Jose Ramirez, who added his seventh All-Star and fifth straight.  He was fourth in OPS+, sixth in OPS, and eighth in Slugging.

6. Juan Soto, New York Mets, Outfield: 164 Cup Points in 160 Games, 1.03 Cup Points per Game.  6.2 bWAR, 120 Runs Scored, 152 Hits, 43 Home Runs, 105 Runs Batted In, 38 Stolen Bases, .263/.396/.525 Slash Line, .921 OPS & 160 OPS+.

It is the New York Mets that are the first team to post two players, and it comes in the form of a player who had a slow start after signing a monster contract.

Juan Soto did not make the All-Star Game (making him the highest-ranked player on this list not to), but he finished the season as the National League leader in OBP (.396), Walks (127), and Stolen Bases (38), the last of which was a huge surprise considering his previous high was 12.  Soto also had a career-high 43 Home Runs.  The Mets may not have made the playoffs, but in year one, New York got value from the superstar.

7. Francisco Lindor, New York Mets, Shortstop: 163 Cup Points in 160 Games, 1.02 Cup Points per Game.   5.8 bWAR, 117 Runs Scored, 172 Hits, 31 Home Runs, 86 Runs Batted In, 31 Stolen Bases, .267/.346/.466 Slash Line, .811 OPS & 129 OPS+.

Yes.  The New York Mets, the team with the most epic choke job in the last twenty years, have three ranked players before any other squad has two.  How is this possible?  The short answer is to see how long it takes for the Mets to have five players here, and when a Pitcher finally shows up.

Lindor had his first All-Star since 2019 (fifth overall), and was the NL leader in Plate Appearances (732) and At Bats (644).  He also had his second 30-30 year, and was third in Runs Scored (117), fifth in Hits (172), and was eighth in Home Runs (31).

8. Manny Machado, San Diego Padres, Third Base: 162 Cup Points in 159 Games, 1.02 Cup Points per Game.   4.1 bWAR, 91 Runs Scored, 169 Hits, 27 Home Runs, 95 Runs Batted In, 14 Stolen Bases, .275/.335/.460 Slash Line, .795 OPS & 118 OPS+.

Machado continues his amazing career by adding a seventh All-Star and continuing to be the Padres' top offensive weapon.  Machado, who was ninth in Hits in the NL, also turned a National League-leading 34 Double Plays at Third Base. 

9 (TIE). Kyle Schwarber, Philadelphia Phillies, Designated Hitter: 161 Cup Points in 162 Games, 0.9938 Cup Points per Game.  4.7 bWAR, 111 Runs Scored, 145 Hits, 56 Home Runs, 132 Runs Batted In, 10 Stolen Bases, .240/.365/.928 Slash Line, .928 OPS & 150 OPS+.

This year’s All-Star Game MVP led the NL with 56 Home Runs and 132 RBIs, both of which were career highs.  He also had a career best in Hits (145), and was second in both Slugging and OPS, but his 197 Strikeouts cost him Cup Points. 

9 (TIE). Junior Caminero, Tampa Bay Rays, Third Base: 161 Cup Points in 154 Games, 1.0454 Cup Points per Game.  4.5 bWAR, 93 Runs, 159 Hits, 45 Home Runs, 110 Runs Batted In, 7 Stolen Bases, .264/.311/.535 Slash Line, .846 OPS & 131 OPS+.

This was the (expected) breakout year for the 22-year-old Dominican Third Baseman, who exploded with 45 Home Runs, a .846 OPS, and the best bat on a promising Rays roster.  We can’t wait to see what “La Maxima” has next!

11. Bobby Witt Jr., Kansas City Royals, Shortstop: 158 Cup Points in 157 Games, 1.0064 Cup Points per Game.  7.1 bWAR, 99 Runs, 184 Hits, 23 Home Runs, 88 Runs Batted In, 38 Stolen Bases, .295/.351/.501 Slash Line, .852 OPS & 136 OPS+.

Witt spent most of the year in the top ten, and having “only” 23 Home Runs might have cost him a Cup Point or two.  Nevertheless, this is Kansas City’s top gun, who led the American League in Hits (184) for the second straight year, and also topped the AL in Doubles (47).

12. Freddie Freeman, Los Angeles Dodgers, First Base: 155 Cup Points in 147 Games, 1.0544 Cup Points per Game.  3.5 bWAR, 81 Runs, 164 Hits, 24 Home Runs, 90 Runs Batted In, 6 Stolen Bases, .295/.367/.502 Slash Line, .869 OPS & 141 OPS+.

Freeman was an All-Star again this year, his ninth overall, and is now four-for-four in Los Angeles. 

13. Fernando Tatis Jr., San Diego Padres, Outfield: 149 Cup Points in 155 Games, .09613 Cup Points per Game.  5.9 bWAR, 111 Runs, 159 Hits, 25 Home Runs, 71 Runs Batted In, 31 Stolen Bases, .268/.368/.446 Slash Line, .814 OPS & 125 OPS+.

Tatis Jr. was an All-Star for the third time this year, and led the NL Rightfielders in Total Zone Runs (31) and Range Factor per Game (2.33).

14. James Wood, Washington Nationals, Outfield: 148 Cup Points in 157 Games, .09427 Cup Points per Game.  3.7 bWAR, 87 Runs, 153 Hits, 31 Home Runs, 94 Runs Batted In, 15 Stolen Bases, .256/.350/.475 Slash Line, .825 OPS & 132 OPS+.

While Wood struck out an NL-leading 221 times, he smacked 31 Home Runs and was the Nationals' top bat.  He was an All-Star for the first time.

15 (TIE). Eugenio Suarez, Arizona Diamondbacks & Seattle Mariners, Third Base: 145 Cup Points in 159 Games, .09120 Cup Points per Game.  3.6 bWAR, 91 Runs, 134 Hits, 49 Home Runs, 118 Runs Batted In, 4 Stolen Bases, .228/.298/.526 Slash Line, .824 OPS & 126 OPS+.

Suarez had a great year, where he was traded from Arizona to Seattle, and matched his career-best in taters with 49.  Suarez did have a better period in Arizona (.897 OPS) than in Seattle (.682 OPS).

15 (TIE). Riley Greene, Detroit Tigers, Outfield: 145 Cup Points in 157 Games, .09236 Cup Points per Game.  2.1 bWAR, 84 Runs, 155 Hits, 36 Home Runs, 111 Runs Batted In, 2 Stolen Bases, .258/.313/.493 Slash Line, .806 OPS & 120 OPS+.

Following James Wood, the American League leader in Strikeouts, Greene dodged the same in the NL (201).  Greene went to his second straight All-Star, and showed his best power numbers (36 HR & 111 RBI).

15 (TIE). Julio Rodriguez, Seattle Mariners, Outfield: 145 Cup Points in 160 Games, .09063 Cup Points per Game.  6.8 bWAR, 106 Runs, 174 Hits, 32 Home Runs, 95 Runs Batted In, 30 Stolen Bases, .267/.324/.474 Slash Line, .798 OPS & 128 OPS+.

Julio completed his fourth season and earned his third All-Star.  Rodriguez matched his career-best 32 Home Runs and was the American League leader in Plate Appearances (710) and At-Bats (652).

18 (TIE). Rafael Devers, Boston Red Sox & San Francisco Giants, Designated Hitter: 144 Cup Points in 163 Games, .08834 Cup Points per Game.  4.0 bWAR, 99 Runs, 153 Hits, 35 Home Runs, 109 Runs Batted In, 1 Stolen Base, .252/.372/.479 Slash Line, .851 OPS & 140 OPS+.

Devers had a great year, but, interestingly, the Red Sox soared when he left and the Giants declined when he arrived.  This was his fifth straight 35 Home Run year, and his .372 OBP was the best of his career.

18 (TIE). Vladimir Guerrero Jr., Toronto Blue Jays, First Base: 144 Cup Points in 156 Games, .09231 Cup Points per Game.  4.5 bWAR, 96 Runs, 172 Hits, 23 Home Runs, 84 Runs Batted In, 6 Stolen Bases, .252/.381/.467 Slash Line, .848 OPS & 133 OPS+.

Vladdy was an All-Star for the fifth straight time, and he brought the Blue Jays to their first American League Pennant since 1993.  Not bad considering it looked like Guerrero was going to become a free agent after this year.

20. Geraldo Perdomo, Arizona Diamondbacks, Shortstop: 143 Cup Points in 161 Games, .08888 Cup Points per Game.  7.0 bWAR, 98 Runs, 173 Hits, 20 Home Runs, 100 Runs Batted In, 27 Stolen Bases, .290/.389/.462 Slash Line, .851 OPS & 136 OPS+.

Perdomo quietly was the National League leader in bWAR in what was his breakout year.

Soon, we will release more updates that will show the complete list.