Fun With Early-Season Park Factors

The introduction of granular ball-in-play data has changed baseball analysis in numerous ways. While traditional methods of evaluation remain invaluable, they can now be supplemented by hard data that can explain what our eyes are telling us, just as our eyes can at times help explain the numbers.

Park factors have been a part of baseball analysis for at least a generation now. Some versions are calculated very simply, others are much more complex. Most would agree that a single year is way too little data upon which to generate meaningful park factors; rolling three- or four-year metrics are often utilized.

Well, I would submit that there is a lot we can learn from park factors generated over very short periods of time, provided that granular exit speed and angle data is integrated. Today, let’s look at some fairly crude context-adjusted park factors based on data from opening day through May 11 of this season.

OK, here’s the quick-and-dirty on the method. Through May 11, 26,650 balls were put into play during MLB regular-season contests. They resulted in an overall batting average of .323 and slugging percentage of .523. Fly balls generated a .314 AVG and .839 SLG; line drives a .662 AVG and .874 SLG; and ground balls a .227 AVG and .249 SLG. (Oh, and pop ups generated a .021 AVG and .037 SLG.) Each BIP type was split into “buckets” separated by 5 mph increments. The top fly-ball bucket begins at 105 mph, and the top liner and grounder buckets begin at 110 mph.

For each ballpark, the actual production derived from that park’s actual BIP mix was compared to the projected production, assuming that each BIP bucket generated MLB average production for that BIP type/exit-speed combination. Convert everything to run values, and voila, park factors, both overall and by BIP type.

Below is a somewhat busy table upon which we’ll base today’s analysis:

Overall & Fly Ball Park Factor Data Thru 5/11/2016

	ALL AVG	ALL SLG	PRJ AVG	PRJ SLG	16 PK FCT	15 PK FCT	FLY AVG	FLY SLG	PRJ AVG	PRJ SLG	16 PK FCT
COL	0.375	0.641	0.319	0.508	148.3	122.7	0.454	1.231	0.317	0.846	209.3
MIL	0.361	0.621	0.340	0.561	117.7	106.1	0.371	1.094	0.339	0.916	133.4
AZ	0.353	0.624	0.335	0.566	116.3	100.7	0.418	1.168	0.362	1.027	130.9
CIN	0.315	0.577	0.313	0.514	113.1	106.0	0.363	1.070	0.302	0.810	162.3
TEX	0.345	0.578	0.335	0.533	111.5	104.6	0.366	0.956	0.334	0.851	124.0
NYY	0.338	0.585	0.326	0.550	110.3	111.8	0.345	0.986	0.321	0.878	121.8
BOS	0.363	0.586	0.342	0.573	108.6	112.0	0.422	1.047	0.340	0.954	132.7
HOU	0.327	0.534	0.324	0.499	108.0	115.4	0.317	0.832	0.300	0.747	119.1
SD	0.324	0.511	0.317	0.501	104.3	116.9	0.262	0.687	0.283	0.740	85.8
BAL	0.335	0.526	0.330	0.521	102.7	101.6	0.344	0.882	0.338	0.892	100.1
SF	0.334	0.500	0.325	0.504	102.1	89.2	0.292	0.695	0.296	0.756	89.5
MIN	0.334	0.533	0.324	0.543	101.4	100.4	0.305	0.815	0.301	0.882	91.6
TB	0.293	0.512	0.300	0.505	98.9	95.3	0.276	0.870	0.290	0.797	107.9
PHL	0.307	0.536	0.318	0.526	98.5	97.5	0.322	0.921	0.313	0.891	106.7
MIA	0.321	0.487	0.324	0.501	96.5	81.0	0.328	0.770	0.325	0.809	95.3
SEA	0.303	0.492	0.315	0.498	95.0	96.7	0.294	0.819	0.308	0.782	101.8
DET	0.331	0.534	0.334	0.559	94.8	97.0	0.290	0.797	0.349	0.954	69.5
STL	0.318	0.540	0.329	0.552	94.4	101.3	0.325	0.871	0.329	0.908	94.0
KC	0.319	0.485	0.321	0.513	94.3	98.5	0.264	0.640	0.312	0.820	65.0
NYM	0.314	0.476	0.319	0.508	92.4	96.1	0.265	0.700	0.305	0.783	78.1
WAS	0.301	0.464	0.308	0.496	91.6	92.3	0.253	0.684	0.295	0.802	73.1
PIT	0.318	0.485	0.330	0.512	91.5	90.1	0.309	0.753	0.300	0.758	101.5
TOR	0.321	0.514	0.329	0.552	90.9	97.3	0.335	0.858	0.329	0.929	92.0
CWS	0.286	0.453	0.305	0.468	90.4	103.0	0.250	0.685	0.275	0.716	87.9
ATL	0.316	0.459	0.324	0.504	89.3	97.5	0.238	0.565	0.286	0.733	63.1
CLE	0.334	0.528	0.347	0.575	88.5	101.2	0.277	0.743	0.322	0.880	72.2
LAD	0.280	0.447	0.301	0.471	88.1	96.3	0.312	0.796	0.312	0.783	102.0
OAK	0.298	0.451	0.311	0.496	87.5	85.8	0.267	0.711	0.307	0.818	75.6
CUB	0.292	0.462	0.314	0.507	84.9	103.7	0.230	0.640	0.293	0.784	64.8
LAA	0.292	0.477	0.318	0.525	83.4	94.2	0.272	0.779	0.320	0.872	76.9
MLB	0.323	0.523	0.323	0.523	100.0	100.0	0.314	0.839	0.314	0.839	100.0

The table is presented in descending 2016 Park Factor order. The first four columns show actual and projected AVG and SLG on all BIP, based on the method described above. The next column, in bold, shows the 2016 overall park factors, through May 11, followed by 2015 full-season park factors, utilizing the same method. The remaining columns present actual and projected fly ball production, along with 2016 year-to-date fly ball park factors. They are singled out here, as they tend to represent the primary driver of the overall park factors.

The identity of our most hitter-friendly park, Coors Field, should not come as much of a surprise. Just exactly how extreme it is, however, and how quickly into a season it asserts its identity just might. On the other side of the scale, the identities of some of the more pitcher-friendly parks in the early going might surprise you. Let’s dig a little deeper into some of the underlying data behind some of the more interesting early-season park factor situations.

Mile-High Facts and Figures

When you hit a fly ball at 105 mph or higher, it’s a homer almost all of the time; MLB hitters are batting .920 AVG-3.424 SLG on such BIP this season. In Coors Field, the real differences occur in the next two BIP buckets, from 100-105 and 95-100 mph. In all 30 parks combined, hitters have batted .631 AVG-2.122 SLG on 100-105 mph, and .260 AVG-.778 SLG on 95-100 MPH fly balls. At Coors, they’re hitting .811 AVG-.2.730 SLG and .532 AVG-1.660 SLG, respectively.

From 100-105 mph, the incidence of both doubles and homers at Coors is dramatically higher than at the average ball park. The altitude not only carries more balls over the wall, it also carries more of them to open spaces unable to be covered by the outfielders. Those are some pretty big gaps. The excess production compared to MLB average is simply staggering in the 95-100 mph bucket, however.

Whereas both doubles and homers occur in far greater frequency at 100-105 mph in Coors, the homers are a more singular driver in the 95-99 mph bucket. Over 10% of the 95-99 mph homers hit in all of MLB through May 11 were hit at Coors. (Amazingly, even more were hit in Cincinnati, though that is in part due to the Reds’ early cluster of home dates.) Around 12% of 95-99 mph fly balls hit through May 11 in all ballparks went over the fence; 28% of those hit in Coors Field did.

So Coors has a massive 209.3 fly-ball park factor through May 11, driving its overall park factor of 148.3, which is substantially higher than 2015’s overall 122.7 mark. Another way to look at it: all of the BIP hit at both Coors and Citi Field as of that date “should have” generated a .319 AVG-.508 SLG. Primarily due to park factors, the actual results are much different. Like .375 AVG-.641 SLG (Coors) vs. .314 AVG-.476 SLG (Citi). Context indeed is important.

Fun with Fenway

Overall, Fenway Park’s park factors of 108.6 thus far in 2016 and 112.0 in 2015 don’t look that interesting. Fenway is quite a different animal, however; we can learn quite a bit by focusing on its typically high fly-ball park factor of 132.7 thus far this season.

Most fly-ball park factors are driven by home runs, or lack thereof. In Boston, it’s all about the doubles. The average major-league ballpark yielded 16.5 fly-ball doubles through May 11; there were already 45 of them at Fenway through that date. The primary culprit? That large structure erected in left field.

Let’s not minimize the contribution of the strong Red Sox hitting (combined with their somewhat subpar pitching) toward this result. Fly balls have been hit harder in only two ballparks thus far this season, in Arizona and Detroit. That said, the actual production in Fenway has clearly been aided by the Monster’s huge inflationary effect on the two-base hit.

Fly balls at 90-95 mph are part of the notorious “donut hole” that extends from 75-95 mph. Hitters bat around .100 with no power on such fly balls. About 6% of all such fly balls have gone for doubles as of May 11; in Boston, 21% of such flies did. Fully one-seventh of all of the 90-95 mph fly-ball doubles hit in the game through that date were hit in Boston.

There is a slight mitigating “Monster” effect that holds the overall Fenway park factor in check. A lower percentage of 100+ mph fly balls go for homers there, as the Monster gets in the way, turning them into even more doubles. Ten percent of 105+ MLB fly balls have gone for doubles through May 11; 20% of them did at Fenway.

The New Marlin Dimensions

Well, we’ve got some early data on the effects of the moved-in fences at Marlins Park; if the club’s goal was to make it a more neutral setting, they appear to have succeeded. The park has always rated as extremely pitcher-friendly by any measure, both overall and with respect to fly balls. Thus far in 2016, the fly-ball park factor is a very centrist 95.3, and the overall factor has spiked from 81.0 in 2015 — most pitcher-friendly of all — to 96.5 thus far in 2016.

In the 100-105 mph fly-ball bucket, production has still fallen a bit short of MLB average at .600 AVG-1.800 SLG, but rates very close to average at all other levels. The irony of all of this is that the new dimensions have helped all hitters on both clubs at Marlins Park, with one exception: the home team’s best player.

Giancarlo Stanton has been the preeminent ball-striker in the game for a few years now. He lives in that 105+ mph fly-ball bucket, which generates fly balls that fly out of Yellowstone. When you look up at the end of the year, Christian Yelich, Marcell Ozuna and others will have set new single-year home-run standards, thanks in large part to the new dimensions. Stanton, on the other hand, is almost totally unaffected by the change.

The Cold Spring

One of the first things that jumped out at me when I saw these numbers were the extreme pitcher-friendly states of the open-air ballparks hugging the Great Lakes. Wrigley Field, US Cellular and Jacobs Field have played very pitcher-friendly in the early going. I live in the Milwaukee suburbs, so I have first-hand experience with the primary reason why.

While our winter wasn’t as extreme as it can be, and has been in the recent past, late March, all of April and early May have been a real bear up here. Cold, wind, rain, yuck… Heck, this past Saturday, May 14, was a wonderfully spirited day with snow flurries and a high around 40. This has had a pronounced negative impact on batted balls, hence the puny overall and fly-ball park factors for tenants of generally neutral ballparks such as the Cubs (84.9 overall, 64.8 fly ball), White Sox (90.4, 87.9) and Indians (88.5, 72.2).

The Brewers, conversely, have a roof. As usual, fly balls have been flying out of Miller Park (117.7 overall, 133.4 fly ball park factor). The roof has been open for a total of four, count ’em four innings thus far in 2016.

The cold, rainy weather conditions in both the upper Midwest and the Northeast has largely held down run scoring in a large number of ballparks this season. Since this is a zero-sum game, and all park factors must average out to 100, this has driven the park factors higher for hitter-friendlier parks in warmer weather areas. It will be interesting to check back in a couple of months to see if expected regression occurs in both directions as weather conditions begin to even out a bit.