Park Factors to (Maybe) Monitor

Every baseball stadium is different.  This is an obvious fact, but its obviousness can obscure its importance.  Every baseball stadium is different, so baseball is different in every stadium.  Some of these differences are easy to discern such as HRs in Denver and Cincinnati.  Others though are more easily masked — did you know that the White Sox’ U.S. Cellular Field raises walks by 7%?  Each game is a combination of outcomes affected by each team’s talent and, to a lesser extent, these park factors.  FanGraphs is nice enough to publish its park factors here.

With the league-wide increase in exit velocity and home runs, I was interested to know if any park factors may be changing as well.  With roughly half of the 2016 season in the books, I thought now was as good a time as any to take a look.  Rather than go through the laborious calculations necessary to find park factors like those at FanGraphs, I came up with a quick and not at all exact way to look at just this season.  Essentially, I found each team’s home and away rates of 1B, 2B, 3B, HR, SO and BB per plate appearance.  I then compared each to league average on the same scale as wRC+ (100 is average).  I then calculated a quick park factor on the same scale for each of the above stats as follows (1B factor shown below):

((Team Home 1B Rate – (Team Away 1B Rate – 100)) + 100) / 2 = 1B Park Factor

For example, the Marlins have hit 4% more singles than average at home (104 1B+), and 27% more singles than average on the road (127 1B+), so the Marlins Park 1B park factor would be 88 (depresses singles by 12%).

I am fully aware of the many problems with the methodology (ignores half of the data, small sample, not enough regression included, team road schedules aren’t guaranteed to have average park factors, etc.), but like I said, I wanted something quick, and I am only focused on the extremes anyway.  This should at least show us which parks to consider monitoring or examining further.

2015 FanGraphs vs. 2016 Observed Park Factors
2015 FanGraphs 2016 Observed
Team 1B 2B 3B HR SO BB Team 1B 2B 3B HR SO BB
Angels 100 96 91 93 102 97 Angels 98 87 80 105 101 103
Astros 99 100 108 105 103 101 Astros 93 103 138 101 104 102
Athletics 99 100 105 93 97 101 Athletics 97 97 145 90 98 94
Blue Jays 97 108 105 106 102 99 Blue Jays 107 116 74 90 103 102
Braves 100 99 93 96 103 101 Braves 106 85 125 94 99 102
Brewers 99 100 102 112 101 102 Brewers 95 106 131 113 98 104
Cardinals 100 99 95 94 98 99 Cardinals 101 104 42 88 96 98
Cubs 99 99 102 102 101 102 Cubs 96 84 105 100 98 111
Diamondbacks 99 99 102 100 98 111 Diamondbacks 99 105 120 102 100 99
Dodgers 98 98 78 102 100 96 Dodgers 98 91 69 116 98 101
Giants 99 97 115 84 100 100 Giants 103 97 163 83 100 109
Indians 100 103 81 101 101 99 Indians 109 121 21 105 93 120
Mariners 98 87 85 98 102 97 Mariners 96 96 92 108 97 108
Marlins 101 100 117 88 98 101 Marlins 88 109 42 102 99 102
Mets 96 95 87 101 101 100 Mets 98 86 80 108 98 111
Nationals 104 102 84 97 97 98 Nationals 104 90 70 98 93 109
Orioles 101 99 86 108 99 100 Orioles 103 93 118 105 89 109
Padres 98 95 97 98 102 101 Padres 99 98 100 94 96 102
Phillies 98 99 92 107 103 102 Phillies 93 87 128 94 104 104
Pirates 101 99 89 90 96 96 Pirates 106 88 157 101 92 110
Rangers 103 101 110 105 98 102 Rangers 106 105 153 86 95 113
Rays 99 95 98 96 102 100 Rays 99 99 98 84 105 95
Red Sox 103 114 105 96 100 100 Red Sox 102 123 90 87 94 109
Reds 99 98 92 113 103 101 Reds 97 94 100 121 102 99
Rockies 110 108 128 113 95 102 Rockies 103 134 170 109 86 114
Royals 101 103 114 93 96 99 Royals 104 113 141 100 90 106
Tigers 101 98 126 98 95 99 Tigers 105 97 135 105 96 105
Twins 102 101 106 98 98 99 Twins 105 101 171 86 87 98
White Sox 99 97 91 108 103 107 White Sox 100 99 86 108 97 107
Yankees 100 97 84 110 101 101 Yankees 94 102 86 120 97 116
Data pulled at All-Star Break

I know that is a lot to digest, and I apologize it is not sortable due to my lack of coding skill — but there are some interesting differences buried in that table.

1B Park Factor

Two parks stick out at the extreme ends for singles.  The aforementioned Marlins Park went from slightly single-friendly to the worst park for singles.  I don’t have a good explanation for this, though the fences were moved in prior to this season which we would expect to set off a ripple affect with the park factors.  The Blue Jays’ Rogers Centre went the opposite direction of the Marlins, showing a move from slightly below-average for singles to the second-best park for singles.  The Jays did change to a dirt infield from turf for 2016, but I would expect that to decrease 1Bs rather than increase them.  Maybe dirt slows infielders down giving them less range?  The Jays have recorded more infield and bunt hits at home than on the road as well, which would increase singles.

2B Park Factor

Coors Field has seen a marked increase in doubles (and triples) in 2016 with a small decrease in HRs, which is very interesting considering they raised several areas of the outfield walls.  The Cubs, Braves, Nationals, Phillies and Pirates have all seen at least a 10-point decrease in 2Bs.  Of that group, the Braves, Phillies and Pirates seem to have traded those doubles for triples which I wouldn’t necessarily expect to hold up as a change in the park factor given the limited samples.  The Phillies also made a change to a longer-cut grass, so a decrease in 1Bs and 2Bs makes some sense.  I am not sure what is going on in Chicago (wind patterns?) and Washington as the decrease in doubles does not seem to be offset by an increase in other similar batted balls.

3B Park Factor

As expected with the extremely limited number of triples, there is a ton of variation across the half-season sample.  The two most likely to represent a true change to the park factors in my mind are the decrease in triples in Marlins Park (moved fences in) and the increase in triples at Coors Field (raised fences), though both likely won’t hold up to this magnitude.

HR Park Factor

There have been large and unexpected decreases in home runs in Toronto and Texas, while the Marlins and Dodgers have seen upticks in homers at home.  Probably nothing but small-sample noise here.  It will be worth checking more rigorously to see if these hold up, particularly at Marlins Park given the change to the fences.

Strikeout and Walk Park Factors

Given the way I have calculated each component park factor, I expected all of them to need an adjustment for home-field advantage.  Interestingly, that was not the case for 1Bs, 2Bs and HRs as the average observed park factor for each was 100 across the league.  I wrote off the 108 average observed 3B factor as small-sample noise, but I believe I picked up some measure of home-field advantage in strikeouts and walks.  On average across the league, home parks decreased strikeouts by 3% and increased walks by 5%.  These have been regressed and the samples for each are among the largest of the component park factors (more PAs end in a K than any specific batted-ball outcome, and there are more BBs than anything except 1Bs), so it feels like this reflects something.

The extreme parks for changes in strikeouts are the Twins’ Target Field and Diamondbacks’ Chase Field.  Adjusting for the home-field difference (the unadjusted numbers are shown in the table above), the Twins’ park seems to be decreasing strikeouts by about 8% more than usual, while the Diamondbacks’ stadium is increasing Ks by 8% more than FG expects.  The Twins did make a change to their CF seating that could be affecting the hitters’ ability to pick up pitches (and thus strike out less), but if that is the case an increase in walks would also be expected — and that is not the case, as the Twins have actually walked less than expected when including the home-field adjustment.

For changes in BBs (after adjusting for home field), the parks in Oakland and Cleveland stick out.  The Coliseum has allowed 12% less walks than expected, while the Indians’ Progressive Field has inflated walks by 16%.  These may be worth exploring as both parks have also affected strikeouts, with the A’s park increasing strikeouts and the Indians’ park decreasing Ks.  It is possible hitters are not picking up the ball in Oakland while they are seeing it well in Cleveland.

***

So there you have it.  Noisy, likely inaccurate 2016 park factors.  It will be very interesting to see if any of the observed changes detailed above turn out to reflect a true change in the park factors.  My best guess is Colorado, Miami and Toronto will need some type of adjustment from the 2015 park factors given the fairly significant changes to each park debuting in 2016.  It would be fascinating to hear thoughts from the players on the extreme differences found above as well.  The fact that each park is so different is part of baseball’s appeal to me.  Every game really is totally unique, all the way down to the field itself.





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evo34
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evo34

For checking half-season PFs, how about good old fashioned runs scored?