Category Archives: MLB

MLB Win Percentage vs Number of Games for One Run Games

 mlb_wins_games_for_1rungames_20160826.png August 27, 2016 98 kB 800 × 800 Edit Image Delete Permanently URLTitleCaptionAlt TextDescription ATTACHMENT DISPLAY SETTINGS  Alignment Link To Size                                         1 selected Clear   Insert into post 
mlb_wins_games_for_1rungames_20160826.png
August 27, 2016

This scatter plot show winning percentage (vertical axis) vs number of game (of the horizontal axis) for each MLB team in 2016 through August 26.

The Mariners have the most (47);
The Rangers the highest win rate (77.78%)

This matplotlib graphic was made at SportsDatabase.com
with the SDQL

S(1) as Number of One Run Games, A(W) as Winning Percentage of One Run Games, R(team) @ team and (math.fabs(runs-o:runs)=1 and season=2016) as ‘Winning Percentage of One Run Games v Number of One Run Games\nfor MLB teams through Aug 26, 2016′ ?ymin=0.2 &ymax=0.8 &polyfit=1

Cubs Historically Efficient

scat_mlb_rp10h_runs_xseason_20160704

These scatter plots show the average runs per 10 hits vs average runs for MLB teams. Each of the small multiples represents a season starting with 2005 in the upper left through 2016 (through July 4) in the lower right.

The highest average runs per game was achieved by the Yankees in 2007.

The most outstanding team over this time period was the 2015 Blue Jays.

The scatter plot for 2016 at the lower right shows that the Cubs are on pace to set the highest runs per hit efficiency in more than 10 years and that Atlanta and the Royals are near the historic futility of the 2013 Marlins and the 2010 Mariners.

This matplotlib graphic was made at SportsDatabase.com
with the SDQL

A(runs),A(10*runs)/A(hits),Replace(team),R(season)@team and season|$1 as Runs,$2 as Runs Per 10 Hits,$3@$4 and ($4>2004) as ‘Runs per 10 Hits vs Runs\nMLB Teams since 2005’?marker_size=38&width=1600

Winning Percentage v Number Played for in one runs games through Aug 19,2015

Winning Percentage v Number of Games\nin one runs games through Aug 19,2015
Winning Percentage v Number of Games in one runs games through Aug 19,2015

This scatter plot shows winning percentage in 1 run games vs number of such games through Aug 19,2015.

The Cardinals have the most one run games at 46. The Pirates and Royals have the best winning precentage at 63%. The Blue Jays have the lowest winning percentage at just 33%.

This matplotlib graphic was made at SportsDatabase.com
with the SDQL

S(1),S(100*(W))/S(1),Replace(team)@team and season=2015 and abs(runs-o:runs)=1|$1 as Games,($2) as Wins,$3@1 as ‘Winning Percentage v Number of Games\nin one runs games through Aug 19,2015′ ?marker_size=40

Runs v Home Runs for MLB Teams in the 2014 regular season

Runs v Home Runs for MLB Teams in the 2014 regular season
Runs v Home Runs for MLB Teams in the 2014 regular season

This scatter plot shows Runs v Home Runs for MLB Teams in the 2014 regular season.

The Orioles homered the most; The Angels scored the most; The Padres scored the fewest runs with the 4th fewest homers.

The least squares fit shows a slope of 1.2 runs per hit. The Angles and Tigers are above of the shaded region of normalcy with their high run output with relatively few home runs. The Padres are below this region with few runs compared with homers.

This matplotlib graphic was made at SportsDatabase.com with the SDQL
S(runs),S(home runs),R(team)@team and season=2014 and playoffs=0|$2 as Home Runs,$1 as Runs,$3@1 as ‘Runs v Home Runs for MLB Teamsnin the 2014 regular season’?marker_size=40&polyfit=1&polyfit_show=1

Number of Wins vs Number of Times Winning After 5 Innings for MLB teams in the 2014 regular season

Number of Wins vs Number of Times Winning After 5 for MLB teams in the 2014 regular season
Number of Wins vs Number of Times Winning After 5 for MLB teams in the 2014 regular season

This scatter plot shows the Number of Wins vs Number of Times the Team was Winning After 5 innings for MLB teams in the 2014 regular season.

The linear fit and shaded region or normalcy are also shown.

Teams to the top won the most games;
Teams to the right were winning the most after 5 innings;
Teams to the lower right fade late;
Teams to the upper left comeback.

This matplotlib graphic was made at SportsDatabase.com
with the SDQL S(M5>0),S(margin>0),R(team)@team and season=2014 and playoffs=0|($1) as Winning after 5,($2) as Wins,$3@1 as ‘Number of Wins vs Number of Times Winning After 5nMLB teams 2014 regular season’?polyfit=1&marker_size=40&polyfit_error_scale=0.6&yticks=5

How Long Royals Starters Lasted in 2014

How Long Royals Starters Lasted in 2014
How Long Royals Starters Lasted in 2014

This set of small multiple histograms shows the distribution of how long each of the Royals starters lasted in 2014.

The finger-like structure is due to starters often being pulled after a complete number of innings.

Shields lasted mostly for 7 or 6 full innings and was only knocked out before the 5th one time.

Shields, Vargas and Guthrie each had one complete game.

This matplotlib graphic was made at SportsDatabase.com
with the SDQL

int(3*innings pitched) as Outs @ name and (team=Royals and season=2014 and order=1 and name[0] not in ‘AL’) as ‘How Long Royals Starters Lasted in 2014’?height=500

How Many Outs each Starter got for the Rockies in 2014

How Many Outs each Starter got for the Rockies in 2014
How Many Outs each Starter got for the Rockies in 2014

This set of histograms shows how many outs each starter got for the rockies in 2014.

Belisle and Hernandez started only once.

Chatwood started 4 times and went 5, 6 (twice), and 7 innings.

De La Rosa had the most starts and was often pulled after 6 innings (18 outs).

This matplotlib graphic was made at SportsDatabase.com
with the SDQL

int(3*innings pitched) as Outs,’Number of Games’ @ name and (team=Rockies and season=2014 and order=1) as ‘How Many Outs each Starter for the Rockies got in 2014’?columns=5&height=500

Innings Pitched (times 3) for Giants Starters in 2013

Innings pitched times 3 for Giants starters in 2013
Outs (innings pitched times 3) for Giants starters in 2013

I’m just learning about matplotlib’s coloring rules.  Here I am using: plt.get_cmap(‘gist_rainbow’) and might have to look a little harder there.

I like this histogram because we see from a distance that Giants starters most often go 7 innings, followed by 6 and 5.

I like this because we see quickly that Lincecum and Petit had complete games and for 8 complete innings we can just about read off: 2 for Lincecum; 3 for Bumgarner, 3 for Cain; and 1 for Vogelsong.

To improve it; show each game as a block, rather than bars of some length. This reinforces the idea of a unit and we can count small stacks.

Also, I had trouble with the colors in the green-blue. Is that me?

 

 

Small Multiples: starter’s innings pitched for each MLB team in 2013

This beautiful small multiple set shows how many outs the starter got in 2013. The Tigers starters got 21 outs 49 times during 2013 and the Braves starters lasted 18 outs also 49 times.

The finger-like structure is due to the starting going a complete number of innings.

The bands in the histograms represent different starters; only experts can guess who is blue.

The Nationals like their starters to finish the inning; Cleveland and the Angles less so.

It looks like there are a lot of stories in there.

See anything interesting?