# Dice Baseball¶

The 538 Riddler for March 22, 2019 asks us to simulate baseball using probabilities from a 19th century dice game called Our National Ball Game:

1,1: double         2,2: strike    3,3: out at 1st  4,4: fly out
1,2: single         2,3: strike    3,4: out at 1st  4,5: fly out
1,3: single         2,4: strike    3,5: out at 1st  4,6: fly out
1,4: single         2,5: strike    3,6: out at 1st  5,5: double play
1,5: base on error  2,6: foul out                   5,6: triple
1,6: base on balls                                  6,6: home run



The rules left some things unspecified; the following are my current choices (in an early version I made different choices that resulted in slightly more runs):

• On a b-base hit, runners advance b bases, except that a runner on second scores on a 1-base hit.
• On an "out at first", all runners advance one base.
• A double play only applies if there is a runner on first; in that case other runners advance.
• On a fly out, a runner on third scores; other runners do not advance.
• On an error all runners advance one base.
• On a base on balls, only forced runners advance.

• Exactly one outcome happens to each batter. We call that an event.
• I'll represent events with the following one letter codes:
• K, O, o, f, D: strikeout, foul out, out at first, fly out, double play
• 1, 2, 3, 4: single, double, triple, home run
• E, B: error, base on balls
• Note the "strike" dice roll is not an event; it is only part of an event. From the probability of a "strike" dice roll, I compute the probability of three strikes in a row, and call that a strikeout event. Sice there are 7 dice rolls giving "strike", the probability of a strike is 7/36, and the probability of a strikeout is (7/36)**3.
• Note that a die roll such as 1,1 is a 1/36 event, whereas 1,2 is a 2/36 event, because it also represents (2, 1).
• I'll keep track of runners with a list of occupied bases; runners = [1, 2] means runners on first and second.
• A runner who advances to base 4 or higher has scored a run (unless there are already 3 outs).
• The function inning simulates a half inning and returns the number of runs scored.
• I want to be able to test inning by feeding it specific events, and I also want to generate random innings. So I'll make the interface be that I pass in an iterable of events. The function event_stream generates an endless stream of randomly sampled events.
• Note that it is consider good Pythonic style to automatically convert Booleans to integers, so for a runner on second (r = 2) when the event is a single (e = '1'), the expression r + int(e) + (r == 2) evaluates to 2 + 1 + 1 or 4, meaning the runner on second scores.
• I'll play 1 million innings and store the resulting scores in innings.
• To simulate a game I just sample 9 elements of innings and sum them.

# The Code¶

In [1]:
%matplotlib inline
import matplotlib.pyplot as plt
import random

In [2]:
def event_stream(events='2111111EEBBOOooooooofffffD334', strike=7/36):
"An iterator of random events. Defaults from Our National Ball Game."
while True:
yield 'K' if (random.random() < strike ** 3) else random.choice(events)

def inning(events=event_stream(), verbose=False) -> int:
"Simulate a half inning based on events, and return number of runs scored."
outs = runs = 0 # Inning starts with no outs and no runs,
runners = []    # ... and with nobody on base
for e in events:
if verbose: print(f'{outs} outs, {runs} runs, event: {e}, runners: {runners}')
# What happens to the batter?
if   e in 'KOofD':  outs += 1         # Batter is out
elif e in '1234EB': runners.append(0) # Batter becomes a runner
# What happens to the runners?
if e == 'D' and 1 in runners: # double play: runner on 1st out, others advance
outs += 1
runners = [r + 1 for r in runners if r != 1]
elif e in 'oE': # out at first or error: runners advance
runners = [r + 1 for r in runners]
elif e == 'f' and 3 in runners and outs < 3: # fly out: runner on 3rd scores
runners.remove(3)
runs += 1
elif e in '1234': # single, double, triple, homer
runners = [r + int(e) + (r == 2) for r in runners]
elif e == 'B': # base on balls: forced runners advance
runners = [r + forced(runners, r) for r in runners]
# See if inning is over, and if not, whether anyone scored
if outs >= 3:
return runs
runs += sum(r >= 4 for r in runners)
runners = [r for r in runners if r < 4]

def forced(runners, r) -> bool: return all(b in runners for b in range(r))


# Testing¶

Let's peek at some random innings:

In [3]:
inning(verbose=True)

0 outs, 0 runs, event: E, runners: []
0 outs, 0 runs, event: 4, runners: [1]
0 outs, 2 runs, event: E, runners: []
0 outs, 2 runs, event: 1, runners: [1]
0 outs, 2 runs, event: f, runners: [2, 1]
1 outs, 2 runs, event: B, runners: [2, 1]
1 outs, 2 runs, event: 1, runners: [3, 2, 1]
1 outs, 4 runs, event: E, runners: [2, 1]
1 outs, 4 runs, event: o, runners: [3, 2, 1]
2 outs, 5 runs, event: o, runners: [3, 2]

Out[3]:
5
In [4]:
inning(verbose=True)

0 outs, 0 runs, event: 1, runners: []
0 outs, 0 runs, event: B, runners: [1]
0 outs, 0 runs, event: O, runners: [2, 1]
1 outs, 0 runs, event: 1, runners: [2, 1]
1 outs, 1 runs, event: 3, runners: [2, 1]
1 outs, 3 runs, event: 1, runners: [3]
1 outs, 4 runs, event: f, runners: [1]
2 outs, 4 runs, event: o, runners: [1]

Out[4]:
4

And we can feed in any events we want to test the code:

In [5]:
inning('2EBB1DB12f', verbose=True)

0 outs, 0 runs, event: 2, runners: []
0 outs, 0 runs, event: E, runners: [2]
0 outs, 0 runs, event: B, runners: [3, 1]
0 outs, 0 runs, event: B, runners: [3, 2, 1]
0 outs, 1 runs, event: 1, runners: [3, 2, 1]
0 outs, 3 runs, event: D, runners: [2, 1]
2 outs, 3 runs, event: B, runners: [3]
2 outs, 3 runs, event: 1, runners: [3, 1]
2 outs, 4 runs, event: 2, runners: [2, 1]
2 outs, 5 runs, event: f, runners: [3, 2]

Out[5]:
5

That looks good.

# Simulating¶

Now, simulate a million innings, and then sample from them to simulate a million nine-inning games (for one team):

In [6]:
N = 1000000
innings = [inning() for _ in range(N)]
games = [sum(random.sample(innings, 9)) for _ in range(N)]


Let's see histograms:

In [7]:
def hist(nums, title):
"Plot a histogram."
plt.hist(nums, ec='black', bins=max(nums)-min(nums)+1, align='left')
plt.title(f'{title} Mean: {sum(nums)/len(nums):.3f}, Min: {min(nums)}, Max: {max(nums)}')

hist(innings, 'Runs per inning:')

In [8]:
hist(games, 'Runs per game:')