Where Park Factors Fail: Case Study of an Extreme Park Effect
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Park factors describe how parks affect baseball outcomes on average. But what happens at the extremes? Originally presented at Saberseminar in 2015.
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Where Park Factors Fail: Case Study of an Extreme Park Effect
- 1. Where Park Factors Fail CASE STUDY OF AN EXTREME PARK EFFECT
- 2. How do parks really affect outcomes? Park factors are great! ◦ Calculated as averages, and should be applied to averages ◦ E.g. when calculating wRC+ you adjust baseline up or down based on home park, not the player But what happens at the extremes? ◦ Do parks really affect all players equally? Probably not. Difficult to analyze ◦ Measuring a park effect requires large samples ◦ Most parks are fairly neutral ◦ Extreme parks tend to get altered SABERSEMINAR 2015 @BLABABOUTBALL
- 3. If only there were an old park with an extreme effect… SABERSEMINAR 2015 @BLABABOUTBALL
- 4. (Mostly) unchanged since 1940 At least one extreme park effect ◦ 30%+ impact on doubles, >25% for both LHH and RHH Fenway fits the bill on both fronts SABERSEMINAR 2015 @BLABABOUTBALL
- 5. Found a park… how do we examine it? Split hitters into extreme groups and see if they’re affected differently To do that: ◦ Calculate 2B/PA deltas for visitors to Fenway vs. other road games, 1956-2014 ◦ Group hitters into quartiles each year by projected 2B/PA rate (using Marcel) ◦ Find weighted averages by quartile and hand And the results say… SABERSEMINAR 2015 @BLABABOUTBALL
- 6. For RHH, Fenway doesn’t discriminate ∆=0.008 ∆=0.004 ∆=0.009 ∆=0.008 0 0.01 0.02 0.03 0.04 0.05 0.06 1st Quartile 2nd Quartile 3rd Quartile 4th Quartile Actual RHH 2B/PA rates, by projected rate quartiles Ex-Fenway 2B/PA rate Fenway 2B/PA delta SABERSEMINAR 2015 @BLABABOUTBALL
- 7. What about for LHH? ∆=0.007 ∆=0.008 ∆=0.009 ∆=0.015 1.19x 1.20x 1.21x 1.34x 0 0.01 0.02 0.03 0.04 0.05 0.06 1st Quartile 2nd Quartile 3rd Quartile 4th Quartile Actual LHH 2B/PA rates, by projected rate quartiles Ex-Fenway 2B/PA rate Fenway 2B/PA delta SABERSEMINAR 2015 @BLABABOUTBALL
- 8. Do Fenway’s changes matter? Yes… 90 100 110 120 130 140 150 160 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Average 2B/PA Fenway Park Effect, by Batter Hand L (5 yr avg) R (5 yr avg) SABERSEMINAR 2015 @BLABABOUTBALL Roofsuites EMCClub MonsterSeats BudweiserRFRoof CocaColaPartyDeck
- 9. … But not for RHH/LHH weirdness -0.010 -0.005 0.000 0.005 0.010 0.015 0.020 0.025 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 2010 2015 Q4 Delta - Q1 Delta, by Batter Hand L (10 yr avg) R (10 yr avg) SABERSEMINAR 2015 @BLABABOUTBALL Roofsuites EMCClub MonsterSeats BudweiserRFRoof CocaColaPartyDeck
- 10. So what is the explanation? It’s all about asymmetry: SABERSEMINAR 2015 @BLABABOUTBALL Data source: Gameday 2007 hit data, converted to feet using method from Peter Jensen: http://www.hardballtimes.com/using-gameday-to-build-a-fielding-metric-part-1/ 75th percentile distance, by batter quartile 25th percentile distance, by batter quartile
- 11. Conclusions Shocking revelation! Some lefties can exploit Fenway’s dimensions more than others. More interesting: at the extremes, park effects can impact different types of players differently But… there may not be another park effect like this one, now or ever SABERSEMINAR 2015 @BLABABOUTBALL
- 13. Appendix: Pitchers are not the difference Avg 2B/PA allowed vs. batter hand Avg wOBA allowed vs. batter hand Batter group P faced ex-Fenway P faced at Fenway P faced ex-Fenway P faced at Fenway LHH 4th quartile 0.042 0.046 0.334 0.331 LHH 1st quartile 0.041 0.046 0.335 0.332 Difference 0.001 0.001 -0.001 -0.001 Batter group P faced ex-Fenway P faced at Fenway P faced ex-Fenway P faced at Fenway RHH 4th quartile 0.041 0.043 0.323 0.329 RHH 1st quartile 0.041 0.043 0.324 0.330 Difference -0.001 0.001 -0.001 -0.001 SABERSEMINAR 2015 @BLABABOUTBALL
Notas do Editor
- SPEED UP … SPEED UP … SPEED UP … SPEED UP
- DON’T DWELL ON PHOTO – JUST MENTION AND MOVE ON
- This is how the overall doubles park factor has evolved RHH in blue, LHH in green You can see it dipped dramatically for all hitters for a period. Not coincidentally, this is after club seating was added and Sox hitters swore it was affecting fly balls.
- Now let’s look at the DIFFERENCE in park effects for the most and least prolific doubles hitters.
- Spray chart for a full year of lefty balls in the air, EXCLUDING Fenway High-double hitters in blue, low-double in red Have added contours that show 75th and 25th percentile distance around the park LHH: Fenway’s dimensions following the shape of batted ball distribution, so shifting distribution outward slightly can have a disproportionate effect on outcomes. It’s especially true in LF where most LHH flyballs go. This is exactly what we see in the results. RHH: This isn’t the case for RHH. There are very few areas of the park where a small shift in the distribution dramatically changes the interaction with the field dimensions, and especially not in RF.