The 2005 White Sox Went 14-5 Against The Indians Despite A -.033 OPS Differential In Those Games (and the Indians had an overall OPS differential of .098 while the Sox had .040)

All data from Baseball Reference and the BR Play Index. My formula for estimating winning pct based on OPS differential is

Pct = .5 + 1.33*OPSDIFF

That is based on a regression. So it estimates the Indians to have a .631 pct or 102 wins while the Sox would have .553 and 90 wins. Yet the Sox actually went 99-63 and the Indians went 93-69.

In the 19 games, the Sox had a .667 OPS and the Indians had .700. There were nine 1-run games and the Sox won them all. The White Sox only outscored the Indians 80-75 in their games.

These stats slightly over state the improbability, but only slightly. The Sox had a 3 game lead with a three game left in Cleveland. But given that at that point the Sox led the season series 11-5, they were assured of having the tie-breaker on their side if the two teams had an identical record since the worst the Sox could do against the Indians would be 11-8, thus taking the season series.

The Sox won all of those last three of those games, two by 1 run and one by 2 runs. But that still means that the Sox had been 7-0 in all the 1-run games between the teams before that. They had only outscored the Indians 70-69 in their first 16 games. And still went 11-5.

The Sox had a 15 game lead at the close of play on Aug. 1. By Sept. 22, that had fallen to 1.5 games. It was still 1.5 on Sept. 24 with 8 games left.

The Sox lost 2 of 3 to the Indians over Sept. 19-21 in Chicago, winning only the middle game 7-6 in 10 innings. By winning that one, they got their lead up to 3.5 games. A loss would have meant a 1.5 game lead (which it still fell to anyway two days later).

The Indians outhit the Sox 14-11 in that game, out HRed the Sox 3-2 and out walked them 5-4. The Indians committed 2 errors and had 1 unearned run.

For the whole season, The Sox had the following OPS differentials in High, Medium and Low leverage situations: .102, .018, .034. The Indians had .044, .098, .123.  I do have a regression equation that uses the OPS differentials in the High, Medium and Low cases. Here it is

Pct = .5 + .306*LOW +.420*MED + .564*HIGH

That estimates the Sox to win 93.2 games and the Indians 97.8. Not as big as 12 mentioned at the beginning based on total OPS, but still fairly large. Maybe the Sox had a much higher OPS in High leverage cases in the games between the two teams.

In games between the two teams, here is the Sox OPS in High, Medium and Low leverage situations: .798, .661, .599. For the Indians they were .584, .739, .748. So here are the Sox OPS differentials in their games with the Indians in High, Medium and Low leverage situations: .214, -.078, -.149.

In games between the two teams, the Sox had an OPS of .729 with runners on and the Indians had .651. From the 7th inning on, with the score tied or either team ahead by 1 run, the Sox had an OPS of .784 and the Indians had .705.

Here are the scores of all the games between the two teams that year and the OPS each team had. It shows the OPS each team had. The Diff column is the Sox OPS minus the Indians OPS. The Indians had a higher OPS in 11 of the games, yet won only 5. The Indians had a higher OPS in 8 of the first 16 games and won only 5 of those.

Date	Loc	Sox R	Ind R	Inn	Sox OPS	Ind OPS	Diff
Apr 4	CHI	1	0		0.351	0.181	0.170
Apr 6	CHI	4	3		0.655	0.454	0.201
Apr 7	CHI	5	11	11	0.648	0.653	-0.005
Apr 11	CLE	2	1		0.654	0.618	0.036
Apr 13	CLE	5	4	10	0.644	0.616	0.028
Apr 14	CLE	6	8		0.664	0.660	0.004
Jun 3	CHI	6	4		0.727	0.704	0.023
Jun 4	CHI	6	5		0.731	0.707	0.024
Jun 5	CHI	4	6	12	0.729	0.708	0.021
Jul 14	CLE	1	0		0.740	0.753	-0.013
Jul 15	CLE	7	1		0.739	0.751	-0.012
Jul 16	CLE	7	5		0.739	0.748	-0.009
Jul 17	CLE	4	0		0.739	0.747	-0.008
Sep 19	CHI	5	7		0.749	0.782	-0.033
Sep 20	CHI	7	6	10	0.750	0.784	-0.034
Sep 21	CHI	0	8		0.748	0.786	-0.038
Sep 30	CLE	3	2	13	0.748	0.790	-0.042
Oct 1	CLE	4	3		0.748	0.788	-0.040
Oct 2	CLE	3	1		0.747	0.787	-0.040

Team OPS Differentials And Expected Wins At The Halfway Point (Or Who Is Leveraging Wins)

This is through games Monday, July 3. Some teams are doing better than expected and some worse. But it will turn out that the biggest outliers see their expected win differences shrink quite a bit when High, Medium and Low leverage situations are taken into account. To predict or estimate a team's winning pct I use

Pct = 1.3465*OPSDIFF + .5

That is based on a regression done on all teams from 2010-2014. I used team averages over the period for both pct and OPSDIFF.

The table below shows each team's OPS so far this season along with their OPS allowed (OPSA), their actual winning pct and then the differential in their win total from what the formula would predict.

The Orioles have a large negative OPS differential yet are still close to a .500 team at .488. So they have won about 9 more games than expected. I will have some discussion below about the Orioles as well as the Twins and Yankees (who have won about 8 fewer games than expected). Also, at the end of this post is a table with each team's actual win and loss totals through Monday.

TEAM	OPS	OPSA	Pct	W Diff
Baltimore	0.730	0.821	0.488	9.05
Minnesota	0.740	0.797	0.512	7.29
Colorado	0.755	0.756	0.576	6.61
LA Angels	0.697	0.740	0.494	4.54
Kansas City	0.716	0.734	0.512	2.99
San Diego	0.682	0.764	0.415	2.05
Milwaukee	0.773	0.769	0.529	2.04
Atlanta	0.734	0.757	0.494	2.01
San Francisco	0.679	0.776	0.393	1.97
Pittsburgh	0.707	0.763	0.446	1.76
Boston	0.763	0.720	0.578	1.69
Texas	0.739	0.762	0.482	1.07
Seattle	0.748	0.766	0.488	1.04
Cincinnati	0.774	0.826	0.427	-0.26
Arizona	0.782	0.682	0.627	-0.68
Houston	0.836	0.699	0.675	-0.81
Toronto	0.721	0.749	0.451	-0.91
Detroit	0.759	0.784	0.444	-1.77
NY Mets	0.770	0.781	0.463	-1.79
Philadelphia	0.697	0.794	0.346	-1.92
LA Dodgers	0.790	0.656	0.655	-2.16
Chicago Sox	0.737	0.753	0.451	-2.23
Chicago Cubs	0.741	0.719	0.500	-2.43
St. Louis	0.746	0.729	0.488	-2.88
Washington	0.815	0.721	0.590	-3.01
Cleveland	0.768	0.707	0.543	-3.15
Miami	0.742	0.748	0.444	-3.85
Oakland	0.731	0.751	0.422	-4.26
Tampa Bay	0.777	0.729	0.512	-4.43
NY Yankees	0.803	0.697	0.543	-8.06

Orioles: Their run differential is -75, so I thought maybe they had a great record in 1-run games. It is good at 12-8, but I don't think that accounts for winning 9 extra games. With runners in scoring position, their OPS is .856 while just .711 with none on. So far this year, for all of MLB, those numbers are .771 and .734. Maybe that has helped the Orioles score more runs than expected. But maybe not.

Over the years 2010 - 2012 here is the regression generated team runs per game based on OBP and SLG

R/G = 14.71*OBP +  10.37*SLG - 4.57

The O's have an overall OBP of .308 and SLG of .422. The equation estimates that they would score 4.34 runs per game while it was actually 4.44. Not a big difference.

Their pitching might explain things. They have allowed an .830 OPS with none on but just .786 with RISP. So that is .044 better, combined with the .037 differential for all of MLB in the opposite direction and we have a .081 swing. So that could explain quite a bit. The O's pitchers are just doing well with RISP.

But the O's pitchers have allowed OBP and SLG of .355 & .466. That estimates to 5.48 runs per game while the actual is 5.34. Combine that with the extra 0.10 from offense and we have a swing of .24 runs per game. Over 82 games, that is about 20 runs or just 2 extra wins.

Hard to see what is going on. I would have expected a much better record in 1-run games. If we give them to extra wins there, we are still only at 4 extra wins far below the 9 we get. But, their overall predicted pct is .377. Over 20 1-run games, that would be 7.5 wins, or 4.5 less than they actually have, accounting for half the difference.

So I looked at their OPS and OPSA in close and late situations. They are .698 and .710, respectively. I thought they might have a big positive differential here, but they don't.

The O's hitters have in High, Medium & Low leverage cases their hitters have an OPS of .752, .783 and .682. Their pitchers have .741, .783 and .883. So the positive differential in high cases probably helps. See comments on Twins.

Twins: They are 9-4 in 1-run games and they have a -55 run differential. So maybe they have 2-3 more wins than expected in 1-run games but that is far below the extra 7 wins. Their pitchers and hitters don't do any better than they normally do with runners on or with RISP (alot worse in some cases). They have a .633 OPS win close and late situations while they give up .676. Not sure how they are doing so well in 1-run games.

They do allow a only a .689 OPS in high leverage situations while it is .841 & .803 in medium and low cases. So maybe when it is close and late they do really well with runners on. In High, Medium & Low cases, their hitters have .761, .746 and .730. So that means they have a very good differential in high leverage cases.

Yankees: They are 9-16 in 1-run games. This probably explains alot of why they have won 8 fewer games than expected. In High, Medium & Low leverage cases their hitters have an OPS of .716, .822 and .825. Their pitchers have .725, .717 and .672. So the negative differential in high cases probably hurts.

But I do have a regression equation that uses the OPS differentials in the High, Medium and Low cases. Here it is

Pct = .5 + .306*LOW +.420*MED + .564*HIGH

Using this equation, Yankees have won only 3.4 fewer games than expected. The Orioles and Twins have won 3.53 and 2.77 more games than expected, respectively. Only one team ends up more than 5 wins off, the A's at -5.31. So taking into account how teams do based on leverage makes a big difference. Maybe differences still exist because of errors, turning DPs and/or base running. Also, I used OBP & SLG instead of OPS, things might still get more accurate.

TEAM	OPSDiff	W	L	Pct
Arizona	0.100	52	31	0.627
Atlanta	-0.023	40	41	0.494
Baltimore	-0.091	40	42	0.488
Boston	0.043	48	35	0.578
Chicago Cubs	0.022	41	41	0.500
Chicago Sox	-0.016	37	45	0.451
Cincinnati	-0.052	35	47	0.427
Cleveland	0.061	44	37	0.543
Colorado	-0.001	49	36	0.576
Detroit	-0.025	36	45	0.444
Houston	0.137	56	27	0.675
Kansas City	-0.018	42	40	0.512
LA Angels	-0.043	43	44	0.494
LA Dodgers	0.134	55	29	0.655
Miami	-0.006	36	45	0.444
Milwaukee	0.004	45	40	0.529
Minnesota	-0.057	42	40	0.512
NY Mets	-0.011	38	44	0.463
NY Yankees	0.106	44	37	0.543
Oakland	-0.020	35	48	0.422
Philadelphia	-0.097	28	53	0.346
Pittsburgh	-0.056	37	46	0.446
San Diego	-0.082	34	48	0.415
San Francisco	-0.097	33	51	0.393
Seattle	-0.018	41	43	0.488
St. Louis	0.017	40	42	0.488
Tampa Bay	0.048	43	41	0.512
Texas	-0.023	40	43	0.482
Toronto	-0.028	37	45	0.451
Washington	0.094	49	34	0.590