UPDATE: Well things started pretty poorly for the Giants dropping the first two games at home but at the very least the Giants managed to avoid the sweep last night.

I promised to updated things if things changed and well they have. With Johnny Cueto of the Reds suffering an injury the Reds have shuffled their rotation. The Giants also made a change, moving Tim Lincecum from starter to the bullpen.

I have updated the projections and updated the odds of each team winning the series. Things look better for the Giants who improved from a 15 percent chance of winning to 28 percent after last night’s victory but they still have long odds.

UPDATED ODDS AS OF 10/10

Games Reds Giants

3

0%

0%

4

49%

0%

5

23%

28%

Total

72%

28%

Original post with updates:

After missing out last year the welcome pangs of nervousness have returned … the San Francisco Giants are back in the playoffs.

In the National League Division series the Giants face the NL Central Champion Cincinnati Reds. The Reds are very good and this series shouldn’t be easy for either team.

Here is the statistical breakdown for each squad:

Offense

AVG OBP SLG wOBA wRC+
Giants 0.269 0.327 0.397 0.315 99
Reds 0.251 0.315 0.411 0.314 93

 

Pitching

ERA- FIP- xFIP-
Giants 97 101 101
Reds 83 93 97

 

The Giants have the edge on offense, while the Reds have the edge in pitching. Neither edge is huge and at least based on the eyeball test it looks like they might balance themselves out.

Next let’s move on to the projection. In case you forgot or haven’t seen the explanation, here is a quick description of how the model works:

  • I start by estimating the runs scored and allowed for each team given the starting pitcher, bullpen, defense and each team’s offense.
  • The data used in the projection model is based on the current season’s statistics to date and if a player has less than a full season of data it is supplemented with the ZiPS projections
  • The estimated run differential is then converted into a projected winning percentage using the pythagorean expectation.
  • Then, it’s converted into an odds of winning the game using the log5 method developed by Bill James

Probables:

Saturday, October 6, 6:30 PM: Johnny Cueto vs. Matt Cain

Sunday, October 7, 6:30 PM: Bronson Arroyo vs. Madison Bumgarner

Tuesday, October 9, 2:30 PM: Homer Bailey vs. Ryan Vogelsong

Wednesday, October 10, 1:00 PM: Mike Leake vs. Barry Zito

Thursday, October 11, 10:00AM**: Mat Latos vs. Matt Cain

**If necessary

Odds (UPDATED 10/10):

Reds Giants
Game 1

43%

57%

Game 2

37%

63%

Game 3

49%

51%

Game 4

49%

51%

Game 5

44%

56%

 

The Giants are favored in every game with Game 3 and Game 5 both looking like toss-ups. What drives the Giants’ advantage is their ability to score runs of all things; if someone told us this would be the case last year, we’d never believe it.

The Reds have the pitching advantage in every game expect for Game 2, where Bumgarner has an edge over Arroyo — the Reds’ worst pitcher of the four scheduled to start in the NLDS. In addition, the last thing the Giants want to see is the Reds’ bullpen so getting out to a quick start will be extremely important.

Here is how the different permutations turn out for the series, with the odds of each team winning in a certain number of games:

Games Reds Giants

3

8%

19%

4

14%

24%

5

17%

19%

Total

39%

61%

The Giants starting at home provides a substantial advantage. The chance of a sweep for the Reds is very small while the Giants have nearly a one-in-five chance at taking this series in three games.

If the Giants are able to take the first two games of the series they push their odds of winning to 90%, while a split at home means advancing to the NLCS becomes a 50/50 proposition.

As reassuring these numbers are, this is still a short series where random fluctuations can cause havoc. At the very least the Giants have the benefit of starting at home to try to build a commanding lead in the series.