The Relationship Between OPS Differential And Winning Percentage Using 5 Year Averages

See a recent post called The Relationship Between Team OPS Differential And Winning Percentage, By Decades. I used regression analysis to see how big the impact of OPS differential was on winning.

Here, instead of using individual years, I used the average OPS differential and average winning pct for all 30 teams over the last 5 years.

The regression equation from using individual years was

Pct = 1.325*OPSDIFF + .5

The r-squared was .827 and the standard error was .029. Over 162 games, that is 4.639 wins

The regression equation from using the 5 year average was

Pct = 1.3465*OPSDIFF + .5

The r-squared was .869 and the standard error was .017. Over 162 games, that is 2.72 wins. That is a big drop from the first regression. In a given year, luck will play a role. But the more seasons and data that are used the more accurate the relationship. By combining the years, some of the good and bad luck evens out.

The table below shows the prediction for each team. It seems strange the 6 most extreme teams are all pretty far from the rest of the pack. The Orioles were predicted to have a .476 pct but it was actually .505. That means they won 4.762 more games per season than their OPS differential would estimate.

Team	OPSDIFF	W-L%	Pred	Diff	Per 162
BAL	-0.018	0.505	0.476	0.029	4.762
PHI	-0.001	0.526	0.498	0.028	4.532
NYY	0.026	0.563	0.535	0.028	4.473
ATL	0.027	0.554	0.536	0.018	2.949
CLE	-0.021	0.487	0.472	0.014	2.349
MIN	-0.053	0.443	0.429	0.014	2.266
SFG	0.018	0.538	0.525	0.013	2.157
CIN	0.017	0.535	0.523	0.012	1.912
SDP	-0.023	0.481	0.470	0.012	1.899
PIT	-0.018	0.481	0.476	0.006	0.939
NYM	-0.024	0.473	0.467	0.006	0.931
KCR	-0.023	0.475	0.470	0.006	0.894
ARI	-0.020	0.475	0.473	0.002	0.371
STL	0.041	0.557	0.555	0.002	0.360
TOR	-0.009	0.489	0.487	0.002	0.251
LAA	0.023	0.532	0.531	0.001	0.149
WSN	0.024	0.530	0.533	-0.003	-0.415
SEA	-0.037	0.446	0.450	-0.004	-0.640
TBR	0.040	0.550	0.554	-0.004	-0.687
LAD	0.030	0.536	0.541	-0.004	-0.709
OAK	0.029	0.535	0.539	-0.005	-0.738
TEX	0.035	0.539	0.547	-0.008	-1.247
CHW	-0.008	0.479	0.489	-0.010	-1.642
MIL	0.016	0.509	0.522	-0.013	-2.115
HOU	-0.078	0.380	0.395	-0.015	-2.379
DET	0.050	0.552	0.567	-0.015	-2.446
FLA	-0.029	0.444	0.461	-0.016	-2.612
CHC	-0.032	0.427	0.458	-0.030	-4.918
BOS	0.034	0.514	0.546	-0.032	-5.231
COL	-0.017	0.444	0.478	-0.033	-5.404

Here is a graph of the relationship