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American League East · 2016

Tampa Bay Rays 2016

Team WAR
30.7
17.4 bat / 13.2 pitch
Win %
.420
pyth .473
Run diff
-41
4.15 / 4.40 per g
wRC+
103
ERA
4.18
FIP 4.19
Home runs
213

The Tampa Bay Rays went 68-94 in 2016, a .420 winning percentage — 28th of 30 record in baseball. They scored 672 runs and allowed 713, a run differential of -41. The offence ranked 24th of 30 in MLB for runs scored, while their 4.18 staff ERA was 16th of 30. Their 103 team wRC+ was 3% above league average — 11th of 30 in MLB. Evan Longoria led the position players at 4.2 WAR, and Chris Archer the rotation at a 4.02 ERA.

The 2016 season

Month by month, the streaks, and the record in the games that are argued about.

They finished 5th in the AL East, 25 games back. They were as far as 27 games back on September 26. Their best month was August at 14-15, their worst July at 9-16. The longest runs were a 4-game winning streak from May 4 to May 8 and an 11-game losing streak from June 16 to June 26. They were 36-45 at home and 32-49 on the road, 13-27 in one-run games and 47-74 against clubs that finished .500 or better. The most lopsided win was 15-1 against the Padres on August 16; the heaviest defeat, 11-2 against the Orioles on September 6.

Record by month. March games count toward April, October’s toward September.
MonthWLPctRSRADiff
March/April1112.4787680-4
May1116.407130131-1
June1117.393115148-33
July916.36090100-10
August1415.483144118+26
Sept/Oct1218.400117136-19
Splits. Extra innings are blank for a season whose games predate the innings count.
GamesW-LPct
Home36-45.444
Road32-49.395
One-run games13-27.325
Extra innings4-3.571
Within the division32-44.421
Against .500+ clubs47-74.388
Decided by 5+ runs18-22.450
Last 103-7.300

American League East standings, 2016

Final standings. The division page has the rest of its season.

American League East, 2016. Games back of the best record in the division.
TeamWLPctGBRSRADiffWAR
Boston Red Sox9369.574—878694+18450.6
Toronto Blue Jays8973.5494759666+9337.3
Baltimore Orioles8973.5494744715+2929.7
New York Yankees8478.5199680702-2231.9
Tampa Bay Rays6894.42025672713-4130.7

2016 Tampa Bay Rays roster

The players whose season belongs to this club, by position and then by dbWAR. A player traded mid-season is listed with the club he played most of his games for, so a deadline arrival may appear on his other club’s page instead.

Catchers 3

Infielders 8

Outfielders 9

Starting pitchers 7

Relief pitchers 16

Where the offence comes from

Roster contribution by share of the team total.

1,302 team hits
Evan Longoria173Evan Longoria — 173 hits (13.3%)Logan Forsythe135Logan Forsythe — 135 hits (10.4%)Brad Miller133Brad Miller — 133 hits (10.2%)Corey Dickerson125Corey Dickerson — 125 hits (9.6%)Steven Souza Jr.106Steven Souza Jr. — 106 hits (8.1%)Kevin Kiermaier90Kevin Kiermaier — 90 hits (6.9%)Logan Morrison84Logan Morrison — 84 hits (6.5%)Brandon Guyer78Brandon Guyer — 78 hits (6.0%)Steve Pearce76Steve Pearce — 76 hits (5.8%)Tim Beckham49Tim Beckham — 49 hits (3.8%)Nick Franklin47Nick Franklin — 47 hits (3.6%)Curt Casali42Curt Casali — 42 hits (3.2%)Jennings40Desmond Jennings — 40 hits (3.1%)Mikie Mahtook36Mikie Mahtook — 36 hits (2.8%)Luke Maile27Luke Maile — 27 hits (2.1%)Hank Conger24Hank Conger — 24 hits (1.8%)Motter15Taylor Motter — 15 hits (1.2%)Shaffer12Richie Shaffer — 12 hits (0.9%)Jaff Decker — 8 hits (0.6%)Jake Odorizzi — 1 hits (0.1%)Juniel Querecuto — 1 hits (0.1%)
Each rectangle is a player, sized by his share of the team's hits; darker means a larger share. Top 30 contributors. Select a different statistic above, or click a player for his page.

Batting

25 players, ranked by dbWAR.

Evan Longoria3B16068517336980.273.318.521.3551274.2
Brad MillerSS15160113330816.243.304.482.3381153.2
Logan Forsythe2B12756713520526.264.333.444.3401162.7
Kevin KiermaierCF10541490123721.246.331.410.3261072.1
Steve Pearce1B833027613350.288.374.492.3751411.8
Brandon GuyerLF100345789323.266.372.423.3541261.6
Nick FranklinLF60191476266.270.328.443.3341120.8
Corey DickersonLF14854812524700.245.293.469.3231040.8
Logan Morrison1B1053988414434.238.319.414.3211030.8
Tim BeckhamSS63215495162.247.300.434.3181010.7
Steven Souza Jr.RF11946810617497.247.303.409.312960.5
Richie Shaffer1B185412140.250.315.438.3251060.1
Curt CasaliC80256428250.186.273.336.272690.0
Jake OdorizziP241010.250.250.250.219320.0
Desmond JenningsLF60225407202.200.281.350.281750.0
Blake SnellP130000.000.333.000.232410.0
Luke MaileC39126273150.227.252.361.26362-0.0
Matt AndrieseP110000.000.000.000.000-121-0.0
Drew SmylyP120000.000.000.000.000-121-0.0
Chris ArcherP380000.000.125.000.087-60-0.0
Juniel Querecuto2B4111020.091.091.273.147-19-0.1
Hank CongerC46137243100.194.265.306.25758-0.1
Taylor MotterLF299315290.188.290.300.27067-0.2
Jaff DeckerRF19578011.154.211.173.1794-0.5
Mikie MahtookCF60196363110.195.231.292.23140-1.0

Pitching

23 pitchers, ranked by dbWAR.

Chris Archer3333201.191902334.023.811.2410.43.1
Matt Moore3333198.1131201784.084.171.298.12.2
Jake Odorizzi3333187.210601663.694.311.198.01.8
Blake Snell191989.0680983.543.391.629.91.8
Matt Andriese2919127.28811094.373.781.227.71.8
Drew Smyly3030175.171201674.884.491.278.61.3
Alex Colomé57056.22437711.912.921.0211.31.1
Xavier Cedeño54041.1340433.702.641.199.41.0
Dylan Floro12015.0010144.202.281.878.40.4
Ryan Garton37039.1121334.353.961.407.60.3
Tyler Sturdevant16018.1010143.933.471.316.90.2
Chase Whitley5114.1000152.513.501.129.40.2
Ryan Webb18017.1000115.193.901.735.70.1
Eddie Gamboa7013.1020111.354.271.277.40.1
Taylor Motter100.100000.003.153.000.00.0
Enny Romero52045.2201505.914.791.539.9-0.1
Alex Cobb5522.0120168.595.601.776.5-0.1
Erasmo Ramírez64190.27112633.774.761.286.3-0.1
Justin Marks409.000061.006.261.786.0-0.2
Danny Farquhar35035.1100463.065.101.3611.7-0.2
Brad Boxberger27024.1430224.815.531.738.1-0.3
Dana Eveland33023.0010219.005.892.228.2-0.3
Steve Geltz27026.2020235.747.911.247.8-1.0

Attendance

Announced gate at 81 home dates, 2016.

Average
15,879
81 home dates
Median
13,976
Total
1,286,163
Best
40,135
2016-06-17
Quietest
10,117
2016-04-13
On the road
30,091
what they drew away

By situation

Day and night divide the home schedule, and so do weekend and weekday. The road line is a different question.
SplitGamesAvgMedLowHigh
All home8115,87913,97610,11740,135
Night5115,28313,55410,11740,135
Day3016,89215,36910,25131,042
Weekend4019,00617,67911,16840,135
Weekday4112,82712,23910,11724,110
On the road8130,09131,45612,97646,960

Through the season

Average home crowd by month.
MonthGamesAverage
Apr1515,854
May1117,859
Jun1317,709
Jul1316,470
Aug1712,990
Sep1215,562

By season

23148.011574.00.005060708091011121314151617181920212223242526

Announced gate — tickets distributed, which is the figure every reference publishes and is not the same as people through the turnstile. A game the feed reports no gate for is left out rather than counted as empty. Seasons before attendance was carried into the lake are absent from the trend rather than shown as zero.

Game time

First pitch to final out across 162 completed games, 2016.

Regulation
2:58
155 games
All games
3:01
Extra innings
3:54
7 of them
Longest
4:38
2016-06-15, 13 inn
Shortest
2:23
2016-04-15

By situation

Regulation and extra innings divide the season, and so do home and road. Day and night overlap both.
SplitGamesAvgMedFastestLongest
All1623:013:002:104:38
Regulation1552:582:582:104:16
Extra innings73:544:003:254:38
Home813:012:592:234:38
Road813:013:002:104:16
Day583:022:592:214:16
Night1043:003:002:104:38

Through the season

Average completed game by month.
MonthGamesAverage
Apr152:47
May112:58
Jun133:17
Jul132:59
Aug173:00
Sep123:05

By season

192.296.10.005060708091011121314151617181920212223242526

Regulation games only, in minutes. 178 minutes this season.

Elapsed time from first pitch to final out. The feed does not itemise delays, so a rain delay is inside these numbers with no way to subtract it. Games called early are excluded — five innings in ninety-three minutes is not a short game — but they still count in attendance, because the crowd turned up.

Record versus run differential

Tampa Bay Rays are 68-94, a .420 win rate, while their -41 run differential implies .473. That is about 9 wins behind it, which tends to regress upward.