As I outlined last week, the 2021 Toronto Blue Jays had a historic run differential for a team that didn’t make the postseason. The point of baseball of course if to win games, not pile up run differential, but there’s a strong correlation between the two at the season level. By that “Pythagorean expectation”, the Jays would have been expected to win 99 games, putting them right in contention for the division rather than clawing for an ultimately elusive wild card.
Likewise, by the rough rule of thumb that about 10 runs translates to a win, a +183 run differential should result in 18 more wins than a .500 team, or the same 99 win level. Had this underperformance been even slightly smaller, the Jays would not have found themselves on the outside looking on. So I wanted to dig into how this came about.
I was particularly interested because looking over Baseball-Reference’s season summary the last week of the season, it wasn’t glaringly obvious what was to blame. The first culprit would be one-run games since underperforming teams often lose a bunch of close games (the only team worse to underperform by more than the Jays, Arizona, went 10-31 in one-run games).
That not always the case, for example, in 2019 the Los Angeles Dodgers won 92 instead of an expected 102, and went 22-22 in one-run games. Funny enough, the 2021 Jays were also .500 at 15-15. That actually represents slight underperformance, since a team 20+ games above .500 would be expected to be above .500 for all splits, but that’s a very minor factor.
The other split there is for blowout (5+ run games). The Jays were often criticized as a team that destroyed bad teams but came up short against tougher opponents, so this is another obvious place to look. Indeed, the Jays were a lopsided 31-15 in blowouts, piling up a +157 differential with 358 runs scored against 201 allowed, The expectation would be for about 34 wins, so the Jays did underperform here. But it’s less than half of the total underperformance, so I couldn’t help but wonder, where’s the rest?
The Jays were 15-18 in two run games, suboptimal but not catastrophic or really moving the dial. Likewise, they were 13-17 in three run games. On the other hand, they went an impressive 17-6 in four run games.
All told, in 138 games decided by six runs or less, the Jays went 69-69 while scoring 590 runs and allowing 591. It doesn’t take any involved math to see that the Jays almost precisely broke even. At most, we can say that in very close games of three runs of less, the Jays were poor at 43-50. In the end that was costly, but it’s also the case that if that the was extent of their underperformance, they should have won ~95 games and hosted the wild card.
What’s crazy is what happened in games decided by more than that:
The Jays went 2-0 in seven-run, 10-run, and 14-run games; a stunning 10-0 in eight-run games; 4-1 in nine run games; 1-1 in twelve-run games; and, thanks to the epic 22-7 early September beatdown of the Orioles, 1-0 in 15-run games. All told, they went 22-2, outscoring their opponents 256-72.
So their entire win-loss margin and entire run differential came in blowouts. What’s interesting is that if one runs this split through the expectations formula, it yields 21.9 expected wins. In other words, they did about as expected in blowout games.
The problem is just it’s really inefficient to pack so much margin into so few games, which is evident by the 10 runs to one win rule of thumb. If an even run differential should in 11-11 over 22 games, +180 should get you 18 more wins, but it’s impossible to win 29 of 22 games.
Let’s now look by opponent. By far the biggest run differential (153-84, +69) came against the abysmal Orioles, proof to some of the narrative that they were a good team that beat up on bad teams. But they went 14-5, roughly the expectation by the expectations formula (though a couple games short of the 10:1 rule of thumb).
Likewise, the Jays went 11-8 against the Yankees with a +11 differential of 79/68, actually slightly outperforming. That was offset by 8-11 against Tampa Bay with a -7 differential (76/83). All told against these three, the Jays went 33-24 with 308 runs scored against 235 allowed. The expectation would be for about 35 wins, so in sum there was slightly underperformance.
But the biggest letdown was against Boston. The Jays went 9-10, despite outscoring them 110-81. That’s three games of underperformance for them, right into the hands of a team that finished one game ahead of them. The four game split in June sticks out particularly, in which the Jays lost two one-run games while winning 7-2 and 18-4 (and to a lesser extent in July, splitting 4-1 games in a double header, but losing 5-4 while winning 13-1 on the bookend).
Against the AL Central, the Jays went 19-15 with 131 runs scored against 109 for a +22 differential. Overall, that’s very close to expectation, with nothing abnormal by team. In 20 interleague games they actually slightly outperformed with a 14-6 record and more modest 110-85 differential (+25).
The West was a different story, as the Jays went 16-16 while scoring 187 and allowing 153 (+24), for about another three wins of underperformance. They went 3-4 against the Angels despite a 41-29 differential, 4-2 against Texas but blowing them out of the water with a 36-13 differential, and then 2-4 against Seattle despite only being outscored 34-31.
One thing that does not stand up to scrutiny however was the narrative that the Jays just padded their run differential beating up on very bad teams but couldn’t perform against the good teams.
Against the four teams they faced who won less than 70 games, the Jays went 23-10 with 227 runs scored and 128 allowed (+99). That is a few games less than expectation, but in line with the overall level for the season.
Likewise, in 89 games against teams above .500, the Jays went 46-43 with 441 runs scored and 393 against. That’s about three wins less than expected (similarly, it was 39-37, 357/324 against postseason teams). The underperformance of wins versus run differential was across the board, not just from blowing out bad teams.