The 2022 MLB final four teams have proven to be evidence to the success that comes with aggressiveness at the trade deadline. The teams that got aggressive were rewarded, and those who were not disappointed.
I wanted to do a mostly quantitative investigation of the aggressive teams of the 2022 trade deadline. I scored each team with at least a 40% chance to make the postseason with a score from 1-15 (1= passive, 15= aggressive), because there were 15 teams. I compared their odds of making the postseason and following rounds then to what ended up happening. Here’s what I gathered.
To clarify, rtg = deadline aggressiveness rating (1= passive, 15= aggressive).
team | Notable Acquisitions | rtg | Expected Outcome on July 31 here | Actual Outcome (October 6) | Difference |
HOU | Trey Mancini Christian Vasquez Will Smith- RP | 11 | 100% playoffs 99.9% make LDS 60.2% make LCS 33.8% make WS 16.2% Win WS | BYE 57.6% make LCS 35.6% make WS 17.2% Win WS | -2.6 LCS +1.8 WS +1 WS-W WS |
PHI | David Robertson Brandon Marsh No. Syndergaard Edmundo Sosa | 13 | 60.8% playoffs 27.9% make LDS 11.1% make LCS 4.5% make WS 2.1% Win WS | 56% make LDS 25.3% make LCS 11.1% make WS 5.9% Win WS | +39.2 POST +28.1 LDS +14.3 LCS +6.6 WS +3.8 WS-W WS |
NYY | Frankie Montas Harrison Bader Andr. Benintendi Scott Effross | 14 | 100% playoffs 98.6% make LDS 56.4% make LCS 29.3% make WS 12.5% Win WS | BYE 55.7% make LCS 24.7% make WS 10% Win WS | +1.3 LCS -4.6 WS -2.5 WS-W LCS-L |
SD | Juan Soto Josh Bell Brandon Drury Josh Hader | 15 | 81.2% playoffs 38.7% make LDS 17.4% make LCS 8% make WS 4.3% Win WS | 43.1% make LDS 20% make LCS 9.6% make WS 5.1% Win WS | +4.4 LDS +2.6 LCS +1.6 WS +0.8 WS-W LCS-L |
CLE | nobody | 1 | 40.5% playoffs 18.9% make LDS 6.4% make LCS 2.1% make WS 0.5% Win WS | 44% make LDS 17.5% make LCS 6% make WS 1.8% Win WS | 44% make LDS 17.5% make LCS 6% make WS 1.8% Win WS |
LAD | Joey Gallo | 4 | 100% playoffs 99% make LDS 54.5% make LCS 29.1% make WS 17.6% Win WS | BYE 48.9% make LCS 26.3% make WS 15.3% Win WS | +1 LDS -5.6 LCS -2.8 WS -2.3 WS-W LDS-L |
ATL | Robbie Grossman Jake Odorizzi Rasiel Iglesias | 9 | 99.1% playoffs 66.9% make LDS 35.7% make LCS 19.5% make WS 11.5% Win WS | BYE 58.2% make LCS 28.7% make WS 16.9% Win WS | +0.9 POST +33.1 LDS +22.5 LCS +9.2 WS +5.4 WS-W LDS-L |
SEA | Luis Castillo Jake Lamb Curt Casali Matthew Boyd | 12 | 77.2% playoffs 35.5% make LDS 14.1% make LCS 6.2% make WS 2% Win WS | 48.7% make LDS 20.4% make LCS 10.6% make WS 4.1% Win WS | +22.8 POST +13.2 LDS +6.3 LCS +4.4 WS +2.1 WS-W LDS-L |
NYM | Daniel Vogelbach Darin Ruf Mychal Givens | 5 | 99.9% playoffs 87.3% make LDS 47.5% make LCS 24.9% make WS 14.8% Win WS | 56.9% make LDS 31.1% make LCS 18.4% make WS 11.6% Win WS | +0.1 POST -30.4 LDS -16.4 LCS -6.5 WS -3.2 WS-W WC-L |
STL | Jordan Montgomery Jose Quintana | 8 | 47% playoffs 20.4% make LDS 7.5% make LCS 2.6% make WS 1.1% Win WS | 44% make LDS 16.5% make LCS 5.9% make WS 2.7% Win WS | +53 POST +23.6 LDS +9 LCS +3.3 WS +1.6 WS-W WC-L |
TOR | Jordan Montgomery Jose Quintana | 6 | 97.3% playoffs 57.2% make LDS 27.4% make LCS 14.6% make WS 6.5% Win WS | 51.3% make LDS 21.9% make LCS 12% make WS 5% Win WS | +2.7 POST -5.9 LDS -5.5 LCS -2.6 WS -1.5 WS-W WC-L |
TB | David Peralta Jose Siri | 7 | 54.8% playoffs 26.9% make LDS 11.2% make LCS 4.7% make WS 1.6% Win WS | 56% make LDS 26.8% make LCS 11.1% make WS 4.4% Win WS | +45.2 POST +29.1 LDS +15.6 LCS +6.4 WS +2.8 WS-W WC-L |
MIL | Taylor Rogers Trevor Rosenthal | 3 | 89.6% playoffs 49.5% make LDS 22% make LCS 9.7% make WS 5.2% Win WS | MISSED POSTSEASON | -89.6 POST -49.5 LDS -22 LCS -9.7 WS -5.2 WS-W MISSED |
CWS | Jake Diekman | 2 | 57.1% playoffs 29.2% make LDS 11.9% make LCS 4.9% make WS 1.7% Win WS | MISSED POSTSEASON | -57.1 POST -29.2 LDS -11.9 LCS -4.9 WS -1.7 WS-W MISSED |
MIN | Tyler Mahle Jorge Lopez Michael Fulmer | 10 | 45.2% playoffs 20.5% make LDS 7.3% make LCS 2.4% make WS 0.7% Win WS | MISSED POSTSEASON | -45.2 POST -20.5 LDS -7.3 LCS -2.4 WS -0.7 WS-W MISSED |
If you can't really understand the complicated numbers on the chart, just understand that the teams that were aggressive often had surpassed projections of them before the deadline and succeeded in the postseason compared to the July 31st models. Teams who were passive suffered.
As you can see, being aggressive helps! Pretty obvious, but I wanted to go more in depth. I then went to R, a programming language, to statistically analyze how teams exceeded expectations or failed to live up to them. As you can expect, it’s pretty obvious that being aggressive works in the short term.
For my first graph, I compared the deadline “scores” I gave the team to the percent change that they would make the final four teams. I’ve already explained the x-axis score, and the y-axis is simply the difference between their chances of making the conference finals on July 31, before the deadline, and their chances of making the conference finals on October 6th, when the regular season ended. The correlation value wasn’t great, at a 0.3727681 (1 is good and 0 is horrendous), but it indicated some correlation with being aggressive and regular-season success.
Score = deadline aggressiveness rating. lscoe = how much the team's chances of making the LCS (final four) increased from July 31 to October 6.
Now, the real fuel behind my argument is how aggressiveness affected playoff results. I measured the percentile result of each team compared to July 31st’s projections, seeing how far they got in the postseason and what the predicted chance of that happening was. For this, I subtracted the average percent chance between them reaching where they got and them reaching a round farther, to have more accurate stats. For example, the Mets had about a 6th percentile result, while the Cardinals had about a 69th percentile result. The correlation for this graph was 0.5587597, showing that aggressiveness at the deadline has a much bigger impact on playoff performance and pays off more in October.
Score = deadline aggressiveness rating. Resultile = percentile of result based on Fangraphs's July 31 model.
You’ve seen the stats now. You’re probably wondering why you needed some teenager on the internet to tell you that trading prospects for proven players results in winning; but the same teams that are doing this now were doing this four years ago. The teams that bought in 2018 aren’t totally regretting it now, they’re totally fine because the guys that they gave up only had a chance to become stars in the MLB, and whatever happens in the future isn’t nearly as predictable as what happens in that direct season.
There are obviously some flaws, and my judgments shouldn’t be the only basis of any opinion, but would you rather have a 15% chance to win the world series for 4 seasons and a 5% chance for the last two, or a 10% chance to win the World Series for 6 years? It just takes simple math to pick the first choice, and that’s why teams who aren’t aggressive at the deadline are letting their fans down.