A lot of names have been mentioned as possible second basemen or third basemen for the Boston Red Sox in 2026. Some are already on the roster (Marcelo Mayer); some could be added by trade (Ketel Marte, Brendan Donovan); some could be picked up as free agents (Bo Bichette, Alex Bregman).
There are other names on the current Red Sox roster that have played significant time at second and/or third base, but are not mentioned in articles about who will get regular playing time in the Red Sox infield. And I have issues with this. Specifically, I have issues every time I read that Marcelo Mayer is presumed to be the player who will round out the infield after they acquire a second or third baseman. Because when I look at what Romy Gonzalez did in 2025, I see a guy who is no longer a platoon player, he’s a guy that deserves to play every day. In addition to that, his elite hard-hit rate makes him a breakout candidate, and I’m saying that despite the fact that he was already the second-best hitter on the Red Sox in 2025. His defense is not bad, it’s good enough, and his baserunning is a plus. He’s proven at the major league level, in ways that Marcelo Mayer isn’t. He can be relied on to produce good results in ways that Marcelo Mayer can’t yet.
The thing that will allow him to break out? If he just stops hitting the ball into the ground so much. Of all the guys I’m comparing in this article, he does that the most. His average launch angle is the lowest. The result is that he’s one of the best in baseball at hitting doubles and triples, but his rate of home runs is a little below average.
He could also stand to chase less, and correspondingly increase his walk rate while decreasing his strikeout rate.
If you care about home runs, stikeouts, and walks, any of the 5 potential acquisitions (Bichette, Marte, Donovan, Bregman, Paredes) will be an improvement over Romy Gonzalez. But if you care about overall results at the plate, only Ketel Marte is looking like an improvement over Gonzalez. And when you factor in fielding and baserunning, there are some even bigger advantages for Gonzalez over most of these 5.
I’d hoped to discuss more specifics about comparisons of individual players, but I am finding it hard to find time to write this article. So I’ll just show you the tables I created to make these comparisons easy.
Here are the comparisons I’ve created for these players. The players are ordered left to right by most plate appearances in 2025.
Red means the number is above MLB average; blue means it’s below MLB average. White is MLB average. I set the deepest red to 2.8 standard deviations better than the mean (usually above, but sometimes below), and the deepest blue to 2.8 standard deviations worse than the mean. For hitting and baserunning, a table showing the numerical values of these standard deviations follows.
These same statistics expressed as standard deviations better (red) or worse (blue) than MLB average is below. In some cases, the data was more log-normal than normal, so I used standard deviations of the logarithm of the stat. These are labeled as such.
Here are the numbers supporting my previously mentioned statement that Romy Gonzalez can unlock a lot more power if he learns to elevate the ball. He hits it into the ground too much.
I hated the trade of Willson Contreras to my team, the Boston Red Sox, for RHP Hunter Dobbins, RHP Yhoiker Fajardo and RHP Blake Aita. The Red Sox got a good player who doesn’t improve the team, while giving a player who was a personal favorite.
Hunter Dobbins was my favorite pitcher on the Sox, not for how he pitched, but for the things he said. For the competitive fire. For the anti-Yankees fervor. He seemed promising as a #5 starter.
When I say that Willson Contreras doesn’t improve the Red Sox, that hinges on something that I get the feeling that nobody agrees with me on: that Romy Gonzalez has evolved into one of the top bats on the team, whose elite hard-hit rate could turn him into one of the top bats in the game if he could learn to elevate the ball a bit (he hits it into the ground too much). If you go by multi-year track record, people are right about Gonzalez and Contreras; but if you go just by 2025, as I do in my comments to follow, they’ve got Romy all wrong.
I’ve stated elsewhere, when you analyze it carefully, you see that Contreras is no better than Romy Gonzalez at first base. He’s a good player that the Red Sox didn’t need.
A key part of that statement is “at first base”. Romy’s best position defensively has always been first base, where he rates as average by all the different rating systems (he’s a below average fielder everywhere else). Contreras is effectively the same as Romy at 1B in Total Zone, Defensive Runs Saved, and Deserved Runs prevented. Only Statcast’s Fielding Run Value has him significantly higher, where he is a substantially above-average 4.
At the plate? They’re very similar in wOBA, Expected wOBA, and OBP. Contreras gets more walks and home runs, but not a ton more. Romy gets more singles, doubles, triples, and strikes out slightly less. They both chase too much.
Playing in Fenway, Contreras will probably see his doubles numbers catch up to Romy’s, but their home run numbers may get closer too. But Romy is just a slight adjustment away from unlocking a ton more power, as I mentioned above, with his elite hard-hit rate, but tendency to hit the ball into the ground.
Baserunning? Romy is clearly the better one here.
Positional versatility? Slight advantage to Contreras because it’s great to have an emergency backup catcher, but Romy is strong in this category too.
I figured, put Romy at first until Casas is ready, then work things out from there. Get one other infielder, preferably a third baseman, or a Ketel Marte. That would have been best. Anthony, Gonzalez, and Casas could all be giving the Red Sox power in spades if they can all be healthy.
Now instead, Romy plays second base where he’s worse defensively (I hope he gets better), and Casas is kind of blocked. Contreras may be a power hitter, but the Red Sox may not end up with any more power production for his acquisition.
By now, we have a lot of examples to look at to see how a hitter’s results change when leaving the Japanese baseball leagues to join Major League Baseball. So when I saw some fans getting excited about the prospects of their team signing position players Kazuma Okamoto or Munetaka Murakami this offseason, I decided to try to figure out how these two are likely to do in the MLB.
I found a nice page on Wikipedia that listed all the players who made that very switch. Nineteen of them were position players. I then ruled out any players that had less than 600 plate appearances in Major League Baseball, as that small of a sample size doesn’t inspire confidence that we’re getting an accurate measure of their ability in the MLB. That took 4 players out. I also ruled out all players who were too young when they came over for us to expect that their recent past performance would be at the same level as their near future performance. That ruled out just one player – Shohei Ohtani, who was only 23.7 years old when he played his first game in the majors. That’s almost 4 years younger than the next youngest, Ichiro Suzuki, who was 27.4. That left the 14 players you see in the following table:
These 14 players are listed in descending order of their OPS over their last 3 years playing in Japan just before coming to MLB. The three columns on the right are the ones we’re most interested in. It has their 3-year OPS in Japan, their first-3 (or first-4 or first-5) year OPS in MLB, and what the change in OPS was.
As you can see, in all but one case, the OPS comes down. And not just by a little bit – a .200 point drop is typical in this list. If you look closely, you’ll notice that the players who started with a higher OPS in Japan experienced the biggest drops.
Now let’s look at this data visually to see if we can spot any more trends. I’ve plotted each player’s OPS’s on the vertical axis, and their age at the time they started playing in MLB on the horizontal axis.
I can’t say I see an age-related trend here, except that perhaps the youngest have a slightly smaller drop than the older players. What does show is that trend we mentioned above, that the highest drops come from players with the highest OPS’s in Japan. As a rule of thumb, I’d say this:
If the player’s Japan OPS over the previous 3 years was over 1.000, expect a .200 to .275 point drop.
If it was in the .900’s, expect a .150 to .275 point drop.
If it was under .850, expect a .50 to .100 point drop.
This would be a good time to address some of the outlying data points.
Regarding So Taguchi, the only player whose OPS rose (if only by a paltry .010) upon coming to MLB. There are two things about his time in MLB that did not happen for any other player coming from the Japan leagues. The first is the unusual amount of time he spent in the minors his first two years. Going by plate appearances, he spent 96% of his first year in the minors, and 83% of his second year. Every other player to come over spend most or all of their time in the majors. Perhaps they saw some things they could improve with his plate approach? The other thing is how he was used. He was used almost exclusively as a late-innings replacement, and as such, he got a lot of favorable platoon matchups, much more than a full-time player would. This would have boosted his OPS – indeed, it was higher in the majors than in the minors!
Because the way they used Taguchi was so out of the norm, we can’t rely on his data point to inform us about typically-used players who cross over. So we’ll toss that out.
On the other end of things, there is Yoshi Tsutsugo and his .302 point drop, the biggest one in the chart. Is that a good data point? Notice it is based on only 640 major league plate appearances. That’s just above our cutoff amount. Did we pick a cutoff that was too low?
This may be a good time to point out that we may have a bit of survivorship bias happening here. There were four players we omitted from our data because their total plate appearnaces in the majors was below our 600-PA lower limit – in all cases, well below. Three of those four players had OPS drops of more than .300 points. But are those drops so large because the sample sizes are so small? Or were the sample sizes so small because the drops in OPS were so large? We can’t know for sure. And we can’t know if those large drops in OPS would have stayed that large with more plate appearances. All we can say is there might be a survivorship bias occuring here.
And that makes me inclined to keep the Yoshi Tsutsugo data point. It could be our lone representative of all the players whose play was so poor in MLB that they didn’t even play all that much in the end.
Okay, so so far, we’re taking So Taguchi out and that’s it.
Now it’s time to ask, where would Murakami and Okamoto land on this table and chart?
One thing about Murakami: he’ll be more than a year younger than anyone on this chart was on the day of their first MLB game. That could be a relevant difference. So it would be good now to bring back that data point we eliminated before, the player who was even younger when he started, Shohei Ohtani (you may have heard of him).
Here’s the new table with the three of them added:
Here’s the new plot with those three added and So Taguchi removed:
As you can see, I’ve added Murakami and Okamoto, with their OPS’s from their last 3 years in Japan showing, and a guess at where they’ll end up in the majors as a fuzzy orange patch. We can see that Ohtani did have a drop, but the smallest drop of anyone who started over .900 OPS. Was it because he was young, and young players are more likely to be improving with each year? Or was it because he is a unique human being who can master any new challenge he sets his mind to? Probably a little of both. As far as this impacts Murakami, it had me guessing on the smaller side for his OPS drop, but more closely aligned with Ichiro Suzuki’s, who he’s closest to in both starting age and starting OPS.
Okamoto’s drop puts him at a very MLB-average place. I hear he’s got excellent defensive skills: teams interested in him should know that his value will come from his defense, and not from his bat. This is especially important given that he plays positions that tend to be bat-first (corner infield, and outfield).
Murakami, by this analysis, looks to be an above average bat. But how much so? Enough to make up for his unimpressive defense and baserunning? Some have concerns about his ability to hit major league pitching, and his increasing whiff rate. Will teams look at him and see someone who would benefit from better coaching, coaching they may be able to provide? His raw power will still be there, and that may be enough for some to decide he’ll be a help to the team, and to believe they could improve the rest. If they can, he could become quite the acquisition. It’ll be interesting to watch.
Pete Alonso is one of the best bats in baseball, no question about that. But to get his bat at first base, you have to take with it his awful fielding and awful baserunning. That waters down his value to some extent. But by how much? And how does he compare to players currently on the Red Sox, and other available options?
I’ll present the data here and some other observations, so that you can compare. I’ll finish by talking about whether it makes sense for the Red Sox to add a player or stick with who they have. All the data shown here is from BaseballSavant.
The players to be compared
I picked the 3 first base free agents who were considered the best on the market when this offseason began, and put their stats on the top row of the comparisons below. (I started putting these together weeks ago when Josh Naylor was still a free agent.) On the bottom row I put a top first base trade possibility in Yandy Diaz, and the two top major league first base options on the Red Sox currently, Romy Gonzalez and Triston Casas.
For 5 of the players, I show their 2025 numbers. For Triston Casas, who didn’t play enough in 2024 and 2025 to give us a good idea of what he is, I show his 2023 numbers.
Expected stats
Let’s start with the expected stats. This is where they look at the velocity, launch angle and trajectory of every ball a player put in play, and tally up the probable results based on those numbers.
Focusing primarily on xwOBA, we see that all six players did well, although when you look at the actual values instead of the percentiles, Alonso is clearly separated from the pack, with only Triston Casas giving him a challenge there.
Quality of contact
Now we’ll look at quality of contact.
Alonso had the best overall contact, however Romy Gonzalez had more hard-hit balls. In fact he had the 5th highest Hard Hit% in baseball for players with over 300 PA. (Who was ahead of him? 1. Roman Anthony 2. Kyle Schwarber 3. Shohei Ohtani 4. Aaron Judge.) Yandy Diaz also hit it hard frequently.
But neither Gonzalez nor Diaz get an ideal launch angle (“LA Sweet Spot %”) as much as Alonso does. For both of them it turns out it’s because they hit too many ground balls – Diaz especially. This is likely the reason Diaz’s results aren’t as good as Alonso’s, and for Gonzalez, one of two reasons (we’ll see the other in the next section).
While O’Hearn and Naylor are limited by lower bat speed, O’Hearn improves his results by often having a good launch angle, and Naylor gets a better exit velocity by hitting on the sweet spot of the bat a lot.
Triston Casas’ 2023 comes the closest to Alonso’s 2025 among those pictured here. The differences may only be due to looking at a rookie season versus a veteran in his prime having his best season yet.
Non-contact stats
So that’s what happens when they swing and make contact. What about the numbers when they don’t make contact? Who chases pitches out of the zone too much (Chase %)? Who misses a lot when he swings (Whiff %)? Who walks too little or strikes out too much?
Alonso and O’Hearn are average in these categories. Yandy Diaz is above average, and Romy Gonzalez is well below average. Triston Casas has a great eye, but still manages to swing and miss at an above average pace. Josh Naylor doesn’t chase and doesn’t strike out, but walks an average amount.
Here we have what looks like the other reason Romy Gonzalez doesn’t get better results despite hitting the ball so hard. He chases too much. And while fixing that doesn’t necessarily fix his higher strikeout rate and low walk rate, it ought to at least help.
Fielding and Baserunning
What’s left? Fielding and baserunning.
Here again we see strong similarity between Triston Casas and Pete Alonso. They’re both terribly slow, and awful at both fielding and baserunning. But being slow isn’t the excuse for the rest, because look at Josh Naylor, who is even slower, but manages to be an average baserunner and a decent fielder.
When it comes to baserunning, Romy Gonzalez is the opposite of Josh Naylor. He’s the only one in this group that could be called “fast”, yet he’s still a poor baserunner. Maybe he should get a pointer or two from his teammate Trevor Story, who runs just as fast as Gonzalez but was one of the top baserunners in the game last year. Or maybe we should give him a little credit for being an average or above average baserunner in the past.
As for good fielders, it looks like Ryan O’Hearn is the only one, with Naylor and Gonzalez a little below average. But Gonzalez split his time between first and second base (and some other spots), and when you break his fielding down by position, both in his career and in 2025, he’s been an above-average fielding first baseman, and a below-average fielder everywhere else.
Categorizing these players
So to sum up, I see two basic types of player here.
Pete Alonso and Triston Casas are the power hitters who can get on base, too, but are awful at fielding and baserunning. Yandy Diaz is, too, but with a little less power and a little better baserunning.
In the other category are Josh Naylor and Ryan O’Hearn, who have some power, but not a lot, but still manage to have above-average impact as hitters. And at everything else, they’re average, on the whole.
The 2025 version of Romy Gonzalez belongs in the O’Hearn/Naylor camp, as a well-rounded player with an above-average bat. But he has the raw tools to become much better. He’s got enough speed to become a great baserunner. He’s one of the best in the game at hitting the ball hard, but he hits it on the ground too much, and he misses it too much. And here’s the thing: the parts of his game that are lacking and that are holding him back, are all things he can learn to be better at. He can learn to be a smarter baserunner. He can learn plate discipline. He can learn to hit the ball just a little lower than he does now, to get it into the air more.
The question is, will he?
If he does, he creates a new category, combining the best of O’Hearn/Naylor with the best of Alonso/Casas, and he’d be better than all of them.
Who’s on first?
So what should the Red Sox do? If they can get Pete Alonso in to play first base for them, should they?
Alonso would certainly help the lineup. But if Triston Casas has a healthy year, he’s basically a Pete Alonso clone for much less money.
What if Casas is injured again, though? He sure seems injury prone. Then your backup plan is Romy Gonzalez, who is as good as your second-or-third best first base free agents that were on the market at the start of this offseason. And with the right coaching and effort, could end up being better than all of them in the short term.
So regardless of whether Casas can or can’t play, the Red Sox will have a plus option at first base. They don’t need Alonso to play first base for them.
But Alonso would improve them at DH. But to make that room, they’d need to trade/drop Masataka Yoshida, to whom they owe $36M over the next two years, and probably one of their 4 top-notch outfielders. Not to say they won’t; they may. But they may not.
In the end, Alonso may not add as much value as people think he will, when compared to what the Red Sox would get from the current players who he would replace. All that may not be worth the expected $150M price tag.
If you look at the playoff odds on FanGraphs.com right now, you’ll see the Texas Rangers listed as having a 0.0% chance of making the playoffs this year. But that doesn’t mean they have no chance. It just means their chance is so small that it doesn’t round up to 0.1%; instead it rounds down to 0.0%, as any chance less than 1 in 2000 will do. As it turns out, their chance of making the playoffs is about 1 in 4000 right now.
How we get to that number involves a lot of logical reasoning, complicated by the fact that the Rangers will play a series against one of the four teams they’re chasing, and there will be two series played this week between some of those same four teams.
Let’s set the stage properly. Here are the 8 remaining playoff contenders in the American League:
Only 6 teams in the American League may go to the playoffs. To be one of those 6, the Rangers must pass 2 of the 7 teams ahead of them in the standings (so long as one of them is not a division winner). Fortunately for the Rangers, there are 4 teams they still have a chance to reach. Unfortunately, they’ll be very difficult to reach.
Notice that if the Rangers win all 6 of their remaining games, and the Red Sox lose all 6 of theirs, that the Rangers would only manage to be tied with the Red Sox. But because they hold the tiebreaker over the Red Sox (having won 4 of the 7 games played between them this year), the Rangers would beat out the Red Sox in that case.
The same goes for Detroit. The Tigers must lose all 6 of theirs, and the Rangers must win all 6 of theirs, for the Rangers to tie; because they win the tiebreaker (having won 4 of 6 against the Tigers), the Rangers would beat out the Tigers.
The Rangers did not win their season series against the Astros, however, so must beat them by a game in the final standings, to pass them for a playoff spot. Because they are currently 5 games behind them, that could only happen if the Rangers win all 6 of their remaining games, and the Astros lose all 6 of theirs.
For the Rangers to catch the Guardians, they’ll have to win some of their remaining 3 games against them; those wins would give the tiebreaker to the Rangers. So the Rangers could stand to lose 1 game, or could stand the Guardians winning 1 game, and still beat them for a playoff spot.
Given that there’s only 1 team that isn’t forcing the Rangers to win all their remaining games, but that they need to beat at least 2 of these teams, the only option for the Rangers is to win all their remaining games.
Let’s start a list of requirements like this one:
We’re assuming here that every game a team plays the rest of the way has a 1/2 chance of being a win, and a 1/2 chance of being a loss. Because the Rangers have 6 games remaining, and there’s only 1 way to achieve the stated outcome (Rangers win all 6), that’s 1 outcome out of 26 possible outcomes, or a 1/64 chance of it happening.
What other outcomes must we consider?
Well if none of these teams were playing each other in these final 6 games, it would be a little less complicated. All the outcomes would be independent, so we could calculate the odds of each team’s win totals independently, as a starting point. Our list of requirements would look like this:
Because the Rangers would have to beat at least 2 of these teams, we’d take pairs of outcomes and calculate their odds:
[ (Red Sox lose all) AND (Tigers lose all) ] OR [ (Red Sox lose all) AND (Astros lose all) ] OR [ (Red Sox lose all) AND (Guardians lose 5 or 6) ] OR [ (Tigers lose all) AND (Astros lose all) ] OR [ (Astros lose all) AND (Guardians lose 5 or 6) ]
Notice that we didn’t include (Tigers lose all) AND (Guardians lose 5 or 6). That’s because one of those teams will win the central division; beating a division winner doesn’t help you win a wild card spot. They have to beat at least one of the Red Sox or Astros to get into the playoffs.
So we would multiply odds everywhere there’s an AND above, and then add them everywhere there is an OR above.
This would double-count or triple-count some cases though. For example, it would triple count the case where all three of these occur: (Red Sox lose all) AND (Tigers lose all) AND (Astros lose all). We’d have to subtract out double the odds of that happening.
After making a few more adjustments where 3 of those occur, we’d probably have one final adjustment to make for the case where all 4 occur:
(Red Sox lose all) AND (Tigers lose all) AND (Astros lose all) AND (Guardians lose 5 or 6).
Then we’d multiply our result by the odds of the Rangers winning all their games, because that has to happen in every case of the Rangers making the playoffs.
But we don’t live in that world. We live in a world where, in the final games of the season:
The Tigers play 3 games against the Red Sox The Tigers play 3 games against the Guardians The Rangers play 3 games against the Guardians
Oh my. This reduces the number of games that determine the Rangers’ fate from 30 down to 21. That’s good for the Rangers, because it means a lot fewer games would have to go a certain way for them to make the playoffs, and that gives them better odds.
It also changes how we do this. Now the outcomes we need to consider look like this:
I’ve used highlighting to show outcomes that are related to each other in that they cannot both happen. For example, looking at the two lines in gold, we see that the Red Sox cannot simultaneously lose all their remaining games while also winning all 3 against the Tigers.
Let’s consider those two middle lines right now. If the Tigers lose all their remaining games, that means both the Red Sox and Guardians win at least 3 games. And that means the Rangers can’t beat either of those teams. The only team left that they could beat is the Astros. So if the Rangers beat the Tigers, they must also beat the Astros (and only the Astros) to get into the playoffs. That gives us this:
(Tigers lose all) AND (Astros lose all)
Which is actually this:
(Red Sox win all 3 against the Tigers) AND (Guardians win all 3 against the Tigers) AND (Astros lose all)
And there is no chance of double-counting with other outcomes. This will very much simplify our work to compensate for double countings.
To this we add the following:
[ (Red Sox lose all) AND (Astros lose all) ] OR [ (Red Sox lose all) AND (Guardians lose 5 or 6) ] OR [ (Astros lose all) AND (Guardians lose 5 or 6) ]
But consider that in the end we’ll be multiplying everything by the odds of (Rangers win all), which must happen in every scenario. Because the Rangers play 3 of those games against the Guardians, that means three of the Guardian’s losses have already been accounted for by the (Rangers win all) outcome. So we only need to consider the additional chance that the Guardians lose 2 or 3 against the Tigers. So the above becomes:
[ (Red Sox lose all) AND (Astros lose all) ] OR [ (Red Sox lose all) AND (Guardians lose 2 or 3 to Tigers) ] OR [ (Astros lose all) AND (Guardians lose 2 or 3 to Tigers) ]
Notice that in all 3 of these scenarios, the Tigers become unreachable to the Rangers, because they win at least 2 games. The only double or triple counting in this trio of scenarios is where the Rangers beat everyone but the Tigers:
(Red Sox lose all) AND (Astros lose all) AND (Guardians lose 2 or 3 to Tigers)
That’s a triple-count, so we have to subtract double the odds of that happening.
We can put all this together, with odds, in a new chart:
We add the first four lines then subtract 2 times the last line to compensate for double counting:
Which we multiply by the odds of the Rangers winning all 6 of their remaining games, to give 65/262144. That’s about 1 in 4033, or 0.0248%.
Had it not been for teams playing each other, the odds would have been 1 in about 16,186. So the Ranger’s chances of making the playoffs are about 4 times better because of these teams playing against each other.
The Cleveland Guardians haven’t secured the tiebreaker against the Detroit Tigers for the AL Central division title.
But they have.
What on Earth am I talking about? Read on …
Right now the Tigers are one game ahead of the Guardians with 6 games left to play. It’s therefore very possible that they end up tied for the division lead. In that case, the division winner would be decided by a tiebreaker.
The tiebreaker is based on which team has won more games in their head-to-head matchups this season. The Guardians have won 6 of the 10 games played between them and the Tigers so far this year, and the Tigers have won 4. But there are 3 more to be played, and they’ll be played today through Thursday. Whichever team ends up with 7 or more wins against the other wins the tiebreaker between them.
So for Detroit to win the tiebreaker, they’ll need to win all three of the remaining games. But that would put Detroit 4 games ahead of Cleveland with only 3 games left to play in the season. Cleveland would not be able to make up that ground, so would not be able to win the division (not even by a tie and a tiebreaker).
The only way for a tie to come about this year is therefore if Cleveland wins at least one game against Detroit. And if that happens, Cleveland reaches the required 7 wins to hold the tiebreaker.
Basically, if the tiebreaker matters, then the Cleveland Guardians will hold it.
And that also means that whichever team wins this three game series between them, will find themselves in the lead for the division, just as was the case with the Seattle Mariners/Houston Astros series this past weekend.
And that makes the Guardians/Tigers series the most impactful series happening right now. Definitely one to keep an eye on!
There is a very very narrow range of circumstances under which the Toronto Blue Jays do not make the playoffs. So narrow, in fact, that if we assume every game remaining in the MLB this year has a 50% chance of being won by either team, the odds of the Blue Jays failing to make the playoffs are 1 about 793,072. That equates to a 99.999874% chance that they make the playoffs.
So how do we work out such numbers? Buckle up for a logic roller coaster ride.
To fail to get into the playoffs, every one of the Yankees, Red Sox, Mariners, Astros, Tigers, and Gaurdians would have to beat the Blue Jays, and these are the only 6 teams capable of surpassing the Blue Jays at this point.
At this point, the Blue Jays can end up with at most 73 losses, if they lose all 7 of their remaining games. So surpassing them would especially require a lot of winning by the Gaurdians and Astros (with 71 losses each currently) and the Red Sox and Tigers (with 70 losses each).
But these teams are limited in how much winning they can do the rest of the way, because there will be 6 games played between them. The Tigers and the Gaurdians will play 3 games against each other, and the Tigers and the Red Sox will play 3 against each other. That means there will be at least 6 losses spread around among those 3 teams.
So let’s consider the possible outcomes of the Tigers/Gaurdians series. For each outcome, let’s assume the Blue Jays lose all 7 of their remaining games, ending with a record of 89-73. Let’s also assume both the Tigers and the Gaurdians win all 4 of their other remaining games.
Except that we can’t assume that. Because if the Tigers win all their other 4 games, that means they deliver 3 losses to the Red Sox, who end up at best 89-73, the same as the Blue Jays. Because the Blue Jays end up with 7 wins and 6 losses against the Red Sox, they win the tiebreaker with the Red Sox and are in the playoffs. So the Tigers must lose a game to the Red Sox, and the Red Sox must win their other 4 games not against the Tigers, for the Blue Jays to have a chance at elimination here.
So we’ll assume the Tigers lose 1 more game (versus the Red Sox) outside of the Tigers/Gaurdians series, and the Guardians don’ t lose any others.
If the Gaurdians sweep the Tigers, the Tigers end up 88-74, a game behind the Blue Jays, and the Blue Jays are in the playoffs.
If the Tigers sweep the Guardians, the Gaurdians end up 88-74, a game behind the Blue Jays, and the Blue Jays are in the playoffs.
If the Gaurdians win 2 of 3, the Tigers end up 89-73, tied with the Blue Jays. Because the Blue Jays had 4 wins and 3 losses in their games against the Tigers this year, they win the tiebreaker between the teams, and are in the playoffs.
That leaves the scenario where the Tigers win 2 of 3. Then the Tigers end up 90-72, ahead of the Blue Jays, while the Guardians tie the Blue Jays at 89-73. So as a tiebreaker we look and see that the Blue Jays and Gaurdians each won 3 games against each other this year. We have to use the second tiebreaker, which is records within their own divisions. The Gaurdians end up 36 and 16 against their weaker division; the Blue Jays 25 and 27 against their stronger division. The Gaurdians therefore win this tiebreaker, and the Blue Jays are out of the playoffs – if the other 3 teams surpass them too, that is.
That’s the only scenario in which the Blue Jays are eliminated.
What if The Tigers lose one more game against another opponent? Then they end up with the same record as the Blue Jays, and the Blue Jays are in because they win the tiebreaker with the Tigers. So the Tigers must only lose the one game against the Red Sox.
That covers what must happen with the Tigers, Gaurdians, and Red Sox. What of the Yankees, Mariners, and Astros?
The Blue Jays hold the tiebreaker over the Yankees, so the Yankees must get to at least 90 wins, and therefore must win at least 3 of their last 7 games.
The Blue Jays hold the tiebreaker over the Mariners, so the Mariners must win at least 4 of their last 7 games.
The Astros hold the tiebreaker over the Blue Jays, so they must win at least 5 of their last 7 games.
So now we must get the odds of all these things happening and multiply them together to get the odds that the Blue Jays miss the playoffs. We assume in every game that the teams have an equal chance of winning. The following table contains all the odds:
The reason the Mariners and Astros are lumped together in the last line is that they play one more game against each other, so their odds of reaching their respective win totals are linked because of that game.
When you multiply all these odds together you get 693,198 divided by 2 to the 39th power, which is about 1 in 793,072, or 0.000126%. That’s the odds that they don’t make the playoffs; so the odds that they make the playoffs are about 99.999874%.
We are at nearly the halfway point in the season, and I’ve been noticing the Red Sox do some similar things to last season. They sure seem to be hitting the .500 mark a lot. They’ve been 18-18, 19-19, 20-20, and more. Now they’re 40-40. So I wondered, how are they stacking up to last season, when I granted them the title of the Most .500 Team in Baseball?
They are excelling, actually. Right now they have the lead.
If you measure by who has the most nearly .500 record, they lead all of baseball there:
If you look at that “Games above .500” column, the Red Sox are the only team at .500. And while teams that have played an odd number of games can be no closer than 1 game from .500, no teams are that close. The Sox are clear “winners” in this category.
We can also look at the number of times a team has been at .500 during the season. This gives an idea of whether the team has consistently played like a .500 team through the year. This time we’re looking at that “Times at .500” column:
Showing just the top 8 teams here. The Red Sox and the Reds are clear leaders in this category.
One more. We can look at which teams have the smallest difference between runs scored by them and runs scored against them. This we have in the Run diff column. Negative numbers mean the team allowed more runs than they scored.
The Red Sox are among the 4 leaders here.
But what I find more interesting is to consider balancing a team’s record against their run differential, because some teams have a positive run differential but a losing record, or vice versa. We have four good examples of this, this year. Now there are those who take a team’s run differential and convert it into a number of expected wins and losses for a team. So I took the difference of those for each team to get an expected number of games above .500 for those teams (see the “Expected GA .500” column). Then I averaged this with their actual games above .500 to see where the expected and actual balance out. These averages are listed in the “Ave GA XGA” column.
The Braves, Rangers, Blue Jays, and Gaurdians all have this contradiction of either a losing record and more runs scored than allowed, or vice versa. And there with them in the top 6 spots are the Red Sox.
There’s one team near the top of all these lists – The Boston Red Sox. If they go on to have a mediocre second half, they could repeat as Most .500 Team two years in a row. But with Alex Bregman coming back before long, and the rookies and second-year players getting better, and the pitching getting better, the Red Sox are looking like a team that will finish pretty well above .500 this time, so a repeat may not be in the cards. But they sure are off to a “good” start.
The merit method of awarding wins fixes all the injustices that the current method of awarding wins punishes starting pitchers with. The latest of these injustices happened to Garrett Crochet, ace of the Boston Red Sox, last night. He threw 8 scoreless, 3-hit innings before giving up a game-tying solo home run to baseball’s best hitter, Aaron Judge, with one out in the top of the ninth. With only one run of support from his teammates, that tie score made Crochet ineligible to earn a win, as he was removed from the game at that point, and the current rules say the win goes to the pitcher who was the active pitcher when the winning team took its final lead. So the win went to Garrett Whitlock, who retired the two batters he faced in the top of the 10th inning. Whitlock performed well. But who did more to earn the win? The guy who faced 2 batters over 1 inning of work, giving up no runs, or the guy who faced 30 batters over 8 and 1/3 innings, giving up 1 run to a top offense and the Red Sox’ arch rivals?
Using that method, we take the 2 runs that the Red Sox scored in Friday’s game and divide by 9 and 2/3, which is the number of innings the Red Sox were at bat. This gives us the average number of runs the Red Sox scored in each inning, the fraction 6/29. Then we simply credit each Red Sox pitcher with this number of runs for every inning they pitched. And then we subtract from this the number of runs they gave up. This gives each pitcher a number of “Runs Ahead”. Then we give the win to the pitcher with the greatest number of Runs Ahead.
The cool thing about this method is that adding the Runs Ahead of all the winning team’s pitchers always gives you a positive number, and adding all the Runs Ahead of the losing team’s pitchers always gives you a negative number. This method also assigns the losing pitcher as the one with the most negative Runs Ahead value.
Here’s a table showing the numbers discussed above for the Red Sox pitchers in last night’s game. In the first three columns in the table below we see IP, RCr/IP, and RCr, which stand for Innings Pitched, Runs Credited per inning pitched, and Runs Credited, respectively. You get the third column (Runs Credited) by multiplying together the first two.
Pitcher
IP
RCr/IP
RCr
R
RA
Garrett Crochet
8 ⅓
6/29
50/29
1
21/29
Aroldis Chapman
⅔
6/29
4/29
0
4/29
Garrett Whitlock
1
6/29
6/29
0
6/29
Runs Ahead (RA) calculations for Red Sox pitchers in victory over New York Yankees, June 13, 2025
Then you subtract runs allowed (R) from this to get each pitcher’s number of Runs Ahead (RA) for that game. Because Garrett Crochet had the highest number of Runs Ahead for the winning team, he would be awarded the win by the merit method. But by current rules, the win went to the other Garrett (Whitlock).
I hope someday to convince MLB league officials to change to the merit method for awarding wins. It fixes so many things that are just not right about the current method.
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