Category Archives: scatter

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

Guard v Forward FanDuel Fantasy Points for Each NBA Team

Guard v Forward Fantasy Points
Guard v Forward Fantasy Points

This set of small multiple scatter plots shows the guard’s v forward’s fantasy points for each NBA team through Nov 22, 2015. Each scatter plot show the performance of a team. The horizontal position of each dot gives the total fantasy points for that team’s starting forwards and the vertical position that for the starting guards.

The Hornets in the upper left show the most negative correlation: when the guards get a lot of fantasy points the forwards get few. At the other extreme in the lower right the Nuggets show the most positive correlation: when their guards do well so do their forwards.

Also notable is the relatively tight correlation (seen by the narrow shaded region of normalcy) for the Jazz, Thunder and Grizzlies and that the Wizard’s Forwards are most consistent in their Fantasy output.

How might this inform your Fantasy choices?

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

S(FP@position=F and date and team) as Forwards,S(FP@position=G and date and team) as Guards,R(team) @ season=2015 and team and date|$1,$2@$3 as ‘Guard v Forward Fantasy Points\n all NBA teams in 2015’?polyfit=1&transparency=0.3&polyfit_show=0&marker_size=10&symmetric=1

Guard v Forward Fantasy Points for NBA teams in 2014

scatter_nbap_forwardsFP_guardsFP_2014
These scatter plots show the combined fantasy points of the starting guards v combined fantasy points of the starting forward for each NBA player-game in 2014: that is, each dot represents player performance in a single game.
This matplotlib graphic was made at SportsDatabase.com
with the SDQL

S(FP@position=F and date and team) as Forwards,S(FP@position=G and date and team) as Guards,R(team) @ season =2014 and team and date|$1,$2@1 as ‘Guard v Forward Fantasy Points\n all NBA teams in 2014’?polyfit=3&transparency=0.3&polyfit_show=0

A small change of the SDQL breaks this relationship down by team.
scatter_nbap_forwardsFP_guardsFP_xteam_2014

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

S(FP@position=F and date and team) as Forwards,S(FP@position=G and date and team) as Guards,R(team) @ season =2014 and team and date|$0001,$2@$3 as ‘Guard v Forward Fantasy Points\n all NBA teams in 2014’?polyfit=2&transparency=0.3

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

Third Period Goals vs First Period Goals NHL teams through March 12, 2015

Third Period Goals vs First  Period Goals NHL teams through March 12, 2015
Third Period Goals vs First Period Goals NHL teams through March 12, 2015

This scatter plot shows the Third Period Goals vs First Period Goals NHL teams through March 12, 2015.

The Penguins score the most in the first; The Lightning score most in the third.

The six teams below the diagonal score more in the first than the third.

This matplotlib graphic was made at SportsDatabase.com
with the SDQL
S(period scores[0]),S(period scores[2]),R(team)@team and season=2014|int($1) as First Period Goals,int($2) as Third Period Goals,$3@1 as ‘Third Period Goals vs First Period GoalsnNHL teams through March 12, 2015’?marker_size=36&polyfit=1&polyfit_show=1&polyfit_error_scale=1&marker_size=60

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

Goals Allowed vs First Period Goals Allowed for NHL teams through Feb 25, 2015

Devils Defend Early, Canadiens Later; Oilers Leak.

This icon-scatter-plot shows the Goals Allowed vs First Period Goals Allowed for NHL teams through Feb 25, 2015.

Also shown is the linear fit and the shaded region of normalcy.

Teams above the dashed line defend better in later periods.
Teams below the dashed line defend better in the first period.

While the Devils allow the fewest goals in the first period, by the end of the game they are about average.
The Canadiens allow the fewest goals overall, and are about sixth best in the first period.

This matplotlib graphic was made at SportsDatabase.com
with the SDQL S(o:period scores[0]),S(o:goals),R(team)@team and season=2014|int($1) as First Period Goals Allowed,int($2) as Goals Allowed,$3@1 as ‘Goals Allowed vs First Period Goals AllowednNHL teams through Feb 25, 2015’?marker_size=36&polyfit=1&polyfit_show=1&polyfit_error_scale=0.8&marker_size=60

Goals vs First Period Goals for NHL teams through Feb 24, 2015

Goals vs First  Period Goals for NHL teams through Feb 24, 2015
Goals vs First Period Goals for NHL teams through Feb 24, 2015

This scatter plot shows the Goals vs First Period Goals for NHL teams through Feb 24, 2015.

Also shown is the linear fit and shaded region of normalcy.

Teams towards the upper left do better later in the game.

Teams to the lower right score early and fade late.

The Penguins scored the most in first period with 62 goals.

The Lightning scored the most goals with 203, even though six teams outscored them in the first.

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

S(period scores[0]),S(goals),R(team)@team and season=2014|int($1) as First Period Goals,int($2) as Goals,$3@1 as ‘Goals vs First Period GoalsnNHL teams through Feb 24, 2015’?marker_size=36&polyfit=1&polyfit_show=1&polyfit_error_scale=1&marker_size=60