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# Measure Pitching with WHIP

Measure how many base runners a pitcher allows by using WHIP.

Walks plus hits per inning pitched (WHIP) is a simple statistic for measuring pitcher effectiveness. In short, it measures the average number of base runners a pitcher allows per inning. WHIP is correlated with pitcher effectiveness, though its most important use is as a fantasy statistic (it’s actually called composite ratio in the book Rotisserie League Baseball [Bantam Books]). Here is the formula for WHIP:

`	WHIP = (BB + H) / (IPOuts / 3)`

## Running the Hack

### Summary statistics.

We’ll start with the `p_and_t` table from “Measure Pitching with ERA” [Hack #47] , and we’ll use this code to load the table into R (using Open Database Connectivity, or ODBC, this time):

```	attach(p_and_t)
WHIP <- (BB + H) / IPouts * 3
p_and_t\$WHIP <- WHIP```

Now, let’s calculate summary statistics for consistency:

```	>qualify <- IPouts > 3 * teamG
>p_and_t\$qualify <- qualify
>summary(subset(WHIP, yearID > 1910 & qualify))
Min. 1st Qu.  Median    Mean 3rd Qu.    Max.
0.7373  1.2110  1.3090  1.3150  1.4150  1.9820```

### Top 10.

We’ll start with the `p_and_t` table from “Measure Pitching with ERA” [Hack #47] , and we’ll use this SQL code to calculate the top 10 players of all time, by WHIP:

` select f.franchName as Team, concat(m.nameLast, ", ", m.nameFirst, " (", p.yearID, ")") as Player, round((p.H + p.BB)/p.IPOuts * 3,3) as WHIP, p.IPOuts from p_and_t p inner join master m inner join teamsFranchises f where substring(p.teamIDs,1,3)=f.franchID and p.idxLahman=m.idxLahman ...`

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