document_title: Memory errors

question_text: loss of memory due to the passage of time during which the memory trace is not used

text: Memory errors

text: Overview[edit]

text: There are several different types of memory errors, in which people may inaccurately recall details of events that did not occur, or they may simply misattribute the source of a memory. In other instances, imagination of a certain event can create confidence that such an event actually occurred. Causes of such memory errors may be due to certain cognitive factors, such as spreading activation, or to physiological factors, including brain damage, age or emotional factors. Furthermore, memory errors have been reported in individuals with schizophrenia and depression. The consequences of memory errors can have significant implications. Two main areas of concern regarding memory errors are in eyewitness testimony and cases of child abuse.

text: Types of memory errors[edit]

text: Blocking[edit]

text: The feeling that a person gets when they know the information, but can not remember a specific detail, like an individuals name or the name of a place is described as the "tip-of-the-tongue" experience.The tip-of-the-tongue experience is a classic example of blocking, which is a failure to retrieve information that is available in memory even though you are trying to produce it.[2] The information you are trying to remember has been encoded and stored, and a cue is available that would usually trigger its recollection.[2] The information has not faded from memory and a person is not forgetting to retrieve the information.[2] What a person is experiencing is a complete retrieval failure, which makes blocking especially frustrating.[2] Blocking occurs especially often for the names of people and places, because their links to related concepts and knowledge are weaker than for common names.[2] The experience of blocking occurs more often as we get older; this "tip of the tongue" experience is a common complaint amongst 60- and 70-year-olds.[2]

text: Transience[edit]

text: Transience refers to forgetting what occurs with the passage of time.[3] Transience occurs during the storage phase of memory, after an experience has been encoded and before it is retrieved.[3] As time passes, the quality of our memory also changes, deteriorating from specific to more general.[3] German philosopher named Hermann Ebbinghaus decided to measure his own memory for lists of nonsense syllables at various times after studying them. He decided to draw out a curve of his forgetting pattern over time. He realized that there is a rapid drop-off in retention during the first tests and there is a slower rate of forgetting later on.[3] Therefore, transience denotes the gradual change of a specific knowledge or idea into more general memories.[4]

text: Absentmindedness[edit]

text: Absentmindedness is a gap in attention which causes memory failure. In this situation the information does not disappear from memory, it can later be recalled. But the lack of attention at a specific moment prevents the information from being recalled at that specific moment. A common cause of absentmindedness is a lack of attention. Attention is vital to encoding information in long-term memory. Without proper attention, material is much less likely to be stored properly and recalled later.[5] When attention is divided, less activity in the lower left frontal lobe diminishes the ability for elaborative memory encoding to take place, and results in absentminded forgetting. More recent research has shown that divided attention also leads to less hippocampal involvement in encoding.[5] A common cause of absentmindedness is not being able to remember to carry out actions that had been planned to be done in the future, for example, picking up grocery items, and remembering times of meetings.[6]

text: False memories[edit]

text: False memories, sometimes referred to as confabulation, refer to the recollection of inaccurate details of an event, or recollection of a whole event that never occurred. Studies investigating this memory error have been able to successfully implant memories among participants that never existed, such as being lost in a mall as a child (termed the lost in the mall technique) or spilling a bowl of punch at a wedding reception.[7] In this case, false memories were implanted among participants by their family members who claimed that the event had happened. This evidence demonstrates the possibility of implanting false memories on individuals by leading them to remember such events that never occurred. This memory error can be particularly worrisome in judicial settings, in which witnesses may have false recollections of a crime after it has happened, especially when told by others that particular things may have happened which did not.[8] Another area of concern regarding false memories is in cases of child abuse.

text: Problem of bias[edit]

text: The problem of bias, which is the distorting influences of present knowledge, beliefs, and feelings on recollection of previous experiences.[9] Sometimes what people remember from their past says less about what actually happened than about what they personally believe, feel, and the knowledge they have acquired at the present time.[9] An individuals current moods can bias their memory recall, researchers have found.[9] There are three types of memory biases, consistency bias, change bias and egocentric bias.[9] Consistency bias is the bias to reconstruct the past to fit the present.[9] Change bias is the tendency to exaggerate differences between what we feel or believe in the present and what we previously felt or believed in the past.[9] Egocentric bias is a form of change bias, the tendency to exaggerate the change between the past and the present in order to make ourselves look good in any given situation.[9]

text: Misinformation effect[edit]

text: The misinformation effect refers to the change in memory due to the presentation of information that is relevant to the target memory, such as leading questions or suggestions.[10] Memories are likely to be altered when questions are worded differently or when inaccurate information is presented. For example, in one experiment participants watched a video of an automobile accident and were then asked questions regarding the accident. When asked how fast the automobiles were driving when they smashed into each other, the speed estimate was higher than when asked how fast the automobiles were driving when they hit, bumped or collided into each other. Similarly, participants were more likely to report there being shattered glass present when the word smashed was used instead of other verbs.[11] Evidently, memory recollection can be altered with misleading information after the event.

text: Source confusion[edit]

text: Source confusion or unconscious transference,[12] involves the misattribution of the source of a memory. For instance, an individual may recall seeing an event in person when in reality they only witnessed the event on television.[12] Ultimately, the individual has an inability to remember the source of information in which the content and the source become dissociated. This may be more likely for more distant memories, such as childhood memories.[7] In more severe cases of source confusion, you can take fictional stories you heard from when you were younger and assimilated these stories being your childhood. For example, say your father told you stories about his life when he was a child every night before you went to sleep when you were a child. When you grow up, you might mistakenly remember these stories your dad told you as your own and integrate them into your childhood memories.[13]

text: Imagination inflation[edit]

text: Imagination inflation refers to when a person remembers details of a memory that are exaggerated versions of the actual event or remember an entire memory that never occurred due to the act of imagination.[14] That is, when one imagines an event occurring, their confidence that this event actually did occur increases. One reason for this may be due to the act of imagination increasing the familiarity of the event. When the event seems more familiar, it may become more likely for people to report it actually occurring. For instance, in an experiment participants were asked to imagine playing inside and then running outside toward a window, falling and breaking it, while other participants did not imagine anything. Participants who had imagined this scenario reported an increased level of confidence that the event had actually happened in comparison to those who did not imagine the event.[7] This error can be caused simply by imagining an event.

text: Deese–Roediger–McDermott (DRM) paradigm[edit]

text: Deese-Roediger-McDermott paradigm refers to the incorrect recall of features of an event that were not actually present, due to the features being related to a common theme.[15] This paradigm has been demonstrated with the use of word lists and subsequent recognition tests. For example, experiments have shown that if a research participant is presented with the words: bed rest awake tired dream wake snooze snore nap yawn drowsy, there is a high likelihood that the participant will falsely recall that the word sleep was in the list of words. These results show a significant illusion in memory, in which people remember items that were never presented simply due to their relation with other items in a common theme.[1]

text: Schematic errors[edit]

text: Schematic errors refer to the use of a schema to help reconstruct parts of an experience that cannot be remembered. This may include parts of the schema that did not actually take place, or aspects of a schema that are stereotypical of an event.[16] Schemas can be described as mental guidelines (scripts) for events that are encountered in daily life.[16] For example, when going to the gas station, there is a general pattern of how things will occur (i.e. turn car off, get out of car, open gas tank, punch the gas button, put nozzle into the tank, fill up the tank, put the nozzle back, close the tank, pay, turn car on, leave). Schemas make the world more predictable, allowing expectations to be formed of how things will enfold and to take note of things that happen out of context.[16] However, schemas also allow for memory errors, in that if certain aspects of a scene or event are missing from memory, people may incorrectly remember having actually seen or experienced them because they are usually a regular aspect of the schema. For example, an individual may not remember paying the waiter, but may believe they have done so, as this is a regular step in the script of going to a restaurant. Similarly, a person may recall seeing a fridge in a picture of a kitchen, even if one was not actually depicted due to existing schemas which suggest that kitchens almost always contain a fridge.[16]

text: Intrusion errors[edit]

text: Intrusion errors refer to when information that is related to the theme of a certain memory, but was not actually a part of the original episode, become associated with the event.[17] This makes it difficult to distinguish which elements are in fact part of the original memory. One idea regarding how intrusion errors work is due to a lack of recall inhibition, which allows irrelevant information to be brought to awareness while attempting to remember.[18] Another possible explanation is that intrusion errors result from a lack of new context integration into a viable memory trace, or into an already existing memory trace that is related to the appropriate memory.[18] More explanations involve the temporal aspect of recall, meaning that as the time difference between the study periods of different lists approaches zero, the amount of intrusions between the lists tends to increase,[19] the semantic aspect, meaning that the list of target words may have induced a false recall of non-target words that happen to have a similar or same meaning as the targets,[20] and the similarity aspect, for example subjects who were given list of letters to recall were likely to replace target vowels with non-target vowels.[21] Intrusion errors can be divided into two categories. The first are known as extra-list errors, which occur when incorrect and non-related items are recalled, and were not part of the word study list.[18] These types of intrusion errors often follow the DRM Paradigm effects, in which the incorrectly recalled items are often thematically related to the study list one is attempting to recall from. Another pattern for extra-list intrusions would be an acoustic similarity pattern, this pattern states that targets that have a similar sound to non-targets may be replaced with those non-targets in recall.[22] One major type of extra-list intrusions is called the "Prior-List Intrusion" (PLI), a PLI occurs when targets from previously studied lists are recalled instead of the targets in the current list. PLIs often follow under the temporal aspect of intrusions in that since they were recalled recently they have a high chance of being recalled now.[19] The second type of intrusion error is known as intra-list errors, which is similar to extra-list errors, except it refers to irrelevant recall for items that were on the word study list.[18] Although these two categories of intrusion errors are based on word list studies in laboratories, the concepts can be extrapolated to real-life situations. Also, the same three factors that play a critical role in correct recall (recency, temporal association and semantic relatedness) play a role in intrusions as well. .[19]

text: Time-slice errors[edit]

text: Time-slice errors occur when a correct event is in fact recalled; however the event that was asked to be recalled is not the one that is recalled. In other words, the timing of events is incorrectly remembered.[23] As discovered in a study by Brewer (1988), often the event or event details that are recalled occurred within a short time proximity to the memory required to be recalled.[23] There are three possible theories as to why time-slice errors occur. First, they may be a form of interference, in which the memory information from one time impairs the recall of information from a different time.[24] (see interference below). A second theory is that intrusion errors may be responsible, in that memories revolving around a similar time period thus share a common theme, and memories of various points of time within that larger time period become mixed with each other and intrude on each other's recall. Last, the recall of memories often have holes due to forgotten details. Thus, individuals may be using a script (see schema errors) to help fill in these holes with general knowledge of what they know happened around this time. Since scripts are a time-based knowledge structure, which puts details of a memory in sequence to make it easier to understand, time-slice errors can occur if a detail is mistakenly placed in the wrong sequence.[24]

text: Personal life effects[edit]

text: Personal life effects refer to the recall and belief in events as declared by family members or friends for having actually happened.[25] Personal life effects are largely based on suggestive influences from external sources, such as family members or a therapist.[7] Other influential sources may include media or literature stories which involve details that are believed to have been experienced or witnessed, such as a natural disaster close to where one resides, or a situation that is common and could have occurred, such as getting lost as a child. Personal life effects are most powerful when claimed to be true by a family member, and even more powerful when a secondary source confirms the event having happened.[7] Personal life effects are believed to be a form of source confusion, in which the individual cannot recall where the memory is coming from[26] Therefore, without being able to confirm the source of the memory, the individual may accept the false memory as true. Three factors may be responsible for the implantation of false autobiographical memories. The first factor is time. As time passes, memories fade. Therefore, source confusion may result due to time delay.[7] The second factor is the imagination inflation effect. As the amount of imagination increases, so does one’s familiarity for the contents of the imagination. Thus, source confusion may also occur due to the individual confusing the source of the memory for being true, when in fact it was imaginary.[26] Lastly, social pressure to recall the memory may affect the individual’s belief in the false memory. For example, with increase in pressure, the individual may lower their criteria for validating a memory, and come to accept a false memory for being true.[26] Personal life effects can be extremely crucial to recognize in cases of recovered memories, especially those of abuse, in which the individual may have been led to believe they had been abused as a child by a therapist during psychological therapy, when in fact they had not been. Personal life effects can also be important in witness testimonies, in which suggestions from authorities may incorrectly implant memories regarding witnesses a particular detail about a crime (see the Childhood Abuse and Eye Witness Testimony sections below).

text: Memory error relating to food[edit]

text: In a study done by J. Mojet and E.P. Köster, participants were asked to have a drink, yoghurt, and some biscuits for breakfast. A few hours later, they were asked to identify and the items they had during breakfast out of five variations of the drinks, yoghurts, and biscuits. The results showed that participants remember the texture of the foods much better than for fatty content, although they could discern the difference of both among the different items. Participants were also most certain about foods that they did not have during breakfast, but were the least certain about foods that they said were in their breakfast and about foods that were in their breakfast but were not recognized. This suggests that incidental and implicit memory for foods are more focused on discerning new and potentially unsafe food rather than remembering the details of familiar foods.[27]

text: Causes[edit]

text: Cognitive factors[edit]

text: Spreading activation

text: One theory on how memory works is through a concept called spreading activation. Spreading activation refers to the firing of connected nodes in associated memory links.[28] The theory states that memory is organized in a theoretical web of associated ideas and related features. Each feature, or node, is connected to related features or ideas, which in turn are themselves connected to other related nodes.[29]

text: Spreading activation can also demonstrate how memory errors may occur. As the network of memory associations increases in the number of connections–the connection density–the likelihood of memory gaps and errors occurring also increases. Put simply, the amount of activation a secondary connection receives depends on how many connections the initial node has associated with it. This is because the initial node must divide the amount of activation it spreads to related nodes by the number of connecting nodes it is associated with. If node 1 has three connecting nodes, and node 2 has 15 connecting nodes, the three connecting nodes from node 1 will receive greater activation levels (the activation level is divided less) than for the 15 connecting nodes from node 2, and the components of these nodes will be more easily brought to mind. What this means is that, with more connections a node has, the more difficulty there is bringing to mind one of its connecting features.[30] This can lead to memory errors, in that if the connection density is so great that there is not enough activation reaching the secondary nodes, then the person may not recall a target memory that is actually present, and a memory error occurs.

text: Activation levels to secondary nodes is also determined by the strength of the association to the primary node.[28] Some connections have greater association with the primary node (e.g. fire truck and fire or red, versus fire truck and hose or Dalmatian), and thus will receive a greater portion of the divided activation than less associated connections. Thus, associations that receive less activation will be out-competed by associations with stronger connections, and may fail to be brought into awareness, again causing a memory error.

text: Connection density

text: The connection densities, or neighbourhood densities[31] of memory arrangements help distinguish which elements are a part of, or related to, the target memory. As the density of neural networks increases, the number of retrieval cues (associated nodes) also increases, which may allow for enhanced memory of the event.[30] However, too many connections can inhibit memory in two ways. First, as described under the sub-section Spreading Activation, the total activation being spread from node 1 to connecting nodes is divided by the number of connections. With a greater number of connections, each connecting node receives less activation, which may result in too little activation for the memory cue to be brought to awareness. Connection strength, in which more strongly connected associations receive more activation than less-related associations, may also prevent specific connections from being brought to awareness due to being out-competed by the stronger associations.[31] Second, with more connections branching from various other nodes, there is a greater probability of linking associated connections of different memories together (transplant errors) so that memory errors occur and incorrect features are recalled.

text: Retrieval cues

text: A retrieval cue is a type of hint that can be used to evoke a memory that has been stored but cannot be recalled. Retrieval cues work by selecting traces or associations in memory that contain specific content. With regards to the theory of spreading activation, retrieval cues use associated nodes to help activate a specific or target node.[32] When no cues are available, recall is greatly reduced, leading to forgetting and possible memory errors. This is called retrieval failure, or cue-dependent forgetting.

text: Retrieval cues can be divided into two subsets, although they are by no means used independent of each other. The first are called feature cues, in which information of the content of the original memory, or related content, is used to aid recall.[32] The second category is context cues, in which information based on the specific context (environment) in which the memory or learning occurred is used to aid recall.[32]

text: Although retrieval cues are usually helpful in helping to remember something, they can produce memory errors in three ways. First, incorrect cues can be used, leading to recall of an incorrect memory. Second, although the correct retrieval cues may be used, they may still produce an incorrect memory. This is likely to occur with high connection densities, in which the incorrect (but associated) node was activated and thus recalled, instead of the target memory. Third, the retrieval cue chosen may be correct and associated with the target memory, but it may not have a strong connection to the target memory, and thus may not produce enough activation to produce the target memory.

text: Encoding specificity

text: Encoding specificity is when retrieval is successful to the extent that the retrieval cues used to help recall, match the cues the individual used during learning or encoding.[33] Memory errors due to encoding specificity means that the memory is likely not forgotten, however, the specific cues used during encoding the primary event are now unavailable to help remember the event. The cues used during encoding are dependent on the environment of the individual at the time the memory occurred. In context-dependent memory, recall is based on the difference between the encoding and recall environments.[20] Recall for items learned in a particular context is better when recall occurs in the same place as when the initial memory occurred. This is why it is sometimes useful to “return to the scene of the crime” to help witnesses remember details of a crime, or for explaining why going to a specific location such as a residence or community setting, may lead to becoming flooded with memories of things that happened in that context. Recall can also depend on state-dependency, or the conditions of one's internal environment, at both the time of the event and of recall.[34] For example, if intoxicated at the time the memory actually occurred, recall for details of the event is greater when recalling while intoxicated. Associated with state-dependency, recall can also depend on mood-dependency, in which recall is greater when the mood for when the memory occurred matches the mood during recall.[23] These specific dependencies are based on the fact that the cues used during the initial event can be specific to the context or state one was in. In other words, various features of the environment (both internal and external) can be used to help encode the memory, and thus become retrieval cues. However, if the context or state changes at the time of recall, these cues may no longer be available, and thus recall is hindered.

text: Transfer-appropriate processing

text: Memory errors can also depend on the method of encoding used when initially experiencing or learning information, known as transfer-appropriate processing.[35] Encoding processes can occur at three levels: visual form (the letters that make up a word), phonology (the sound of a word), and semantics (the meaning of the word or sentence). With relation to memory errors, the level of processing at the time of encoding and at the time of recall should be the same.[36] Although semantic processing generally produces greater recall that shallower levels of processing, a study by Morris et al. demonstrated that what might be the key factor to greater recall is transfer-appropriate processing–when the level of processing at the original memory/learning time matches the level of processing used to help recall. In other words, if learning occurred by rhyming the target words to other words, then recall is best if testing is also at the phonological level of processing, such as a rhyming recognition test. Thus, memory errors can occur when the levels of processing between encoding and recall do not match.[36]

text: Interference

text: Interference occurs when specific information inhibits learning and /or recall for a specific memory.[37] There are two forms of interference. First, proactive interference has to do with difficulty in learning new material based on the inability to override information from older memories.[38] In such cases, retrieval cues continue to be associated and aimed at recalling previously learned information, affecting the recall of new material. Retroactive interference is the opposite of proactive interference, in which there is difficulty in the recall of previously learned information based on the interference of newly acquired information. In this case, retrieval cues are associated with the new information and not the older memory.[39] thus affecting recall of older material. Interference of either form can produce memory errors, in which there is interference with the recall of material. In other words, previously used retrieval cues are no longer associated with prior memories, and thus memory confusion or even an inability to recall the memory can occur.

text: Physiological factors[edit]

text: Brain damage

text:
Human Cerebrum

Frontal lobe
Temporal lobe
Parietal lobe
Occipital lobe

Damage in the temporal lobe (green) and frontal lobe (blue) are associated with resulting memory errors

text: Neuroimaging studies have provided evidence for links between brain damage and memory errors. Brain areas implicated include the frontal lobe and medial-temporal regions of the brain. Such damage may result in significant confabulations and source confusion.[8] The prefrontal cortex is in charge of making heuristic judgments and systematic judgments, which involve analyzing the qualities of memories and the retrieval and evaluation of supporting or disconfirming information.[8] Thus, if the frontal region is damaged, these abilities will be impaired and memories may not be retrieved or evaluated correctly. For example, one patient who suffered frontal lobe damage after an automobile accident reported memories of the support his family provided for him after the accident, which in reality, was false.[40]

text: The temporal region of the brain contains the hippocampus, which plays a significant role in memory.[41] Thus, damage in this region may impair the function of this brain structure and result in memory problems.

text: Age

text: Studies have shown that the likelihood of memory errors occurring increases as age increases. Possible reasons for this are increased source confusion for the event and findings that older persons have decreased levels of processing when first presented with new information.[42][43] Source confusion refers to the inability to distinguish how one came upon different information. Older individuals can become confused with where they learnt information (e.g. TV, radio, newspaper, word of mouth, etc.), who presented them with the information (e.g. which of two experimenters presented them with facts and which presented them with irrelevant information), and whether the information came from an imagined source, and is thus not factual, or a real world source.[43] This in itself is a form of memory error but can also create larger memory errors. When an older individual is confused whether the information is factual or was imagined they can begin to accept imagined memories as real and thus begin to rely on new false information.[43] Levels of processing refers to the manner in which someone encodes information into their memory and how deeply it is encoded.[43] There are three different levels of processing ranging from shallow to deep, deep being stored in long-term memory for a longer period and thus better remembered. The three levels are; visual form, being the shallowest form, phonology, being a medium level of processing, and semantics (meaning), which is the deepest form of processing.[43] The visual form of processing relies on the ability to see information and break it down into its components (e.g. see the word "dog", composed D, O, and G). Phonology relies on creating links to information through sound such as cues and tricks for memory (e.g. Dog rhymes with Fog).[43] Finally, semantics refer to the creation of meaning behind information such as adding detail to allow the information to create links throughout our memory with other memories and thus be held in long-term memory for a longer period (e.g. A dog is a four-legged pet that often chases cats and chews on bones).[43] Older individuals often begin to lose the quick ability to add meaning to new information, which leads to shallower processing and easier forgetting of the information gained.[43] Both of these possible factors can decrease the validity of the memory due to retrieval for details of the event being more difficult to perform. This leads to details of memories being confused with others or lost completely, which lead to many errors in recall of a memory.

text: Emotion

text: The emotional impact of an event can have a direct impact on how the memory is first encoded, how it is later recalled, and what details of the event are accurately recalled. Highly emotional events tend to be recalled easily due to their emotional impact,[44] as well as their distinctiveness relative to other memories (highly emotional events do not occur on a regular basis, and thus are easily separated from other events that are more commonly met). Emotional events may affect memory not only because of their distinctiveness, but also because of their arousal on the individual.[45] Studies have found that prime or central features of such highly emotional events tend to be accurately recalled, whereas subtle details of the events are not remembered, or are remembered with vague consistency. Memory errors related to highly emotional events are influenced in ways such as:

text: • Whether the event was positive or negative in nature - The nature of the event can affect memory, negative events tend to be remembered with greater accuracy than positive events.[23]

text: • Implicit theories of consistency and change - This term was coined by Ross (1989), and is used to describe the phenomena of memory change based on the belief of how the person felt at the time of the event compared to their current feelings about it.[23] In other words, the memory of one's emotion towards an event can change depending on their current emotional state toward the same event. If a person believes their feelings at both times continue to be the same, then the current emotion to "remember" how they felt about the event at a previous time is used. If feelings are believed to have changed, then recall of the emotional involvement in the past event is adjusted to the current feelings.

text: • Intrusion errors - This term refers to the inclusion of details that may have been commonly experienced in the event, but not by the individual. For example, in the September 11 terrorist attacks, many people may state that they remember hearing about the attacks on the television news, as this was a common way of finding out this information, whereas they may have actually heard about it from a neighbour or on the radio.[46]

text: • Mood-congruency - Items/events are better recalled when the mood of the individual at the time of the event and the time of recall are the same. Thus, if the mood at the time of recall does not match the mood experienced at the time the event occurred, there is an increased chance that complete recall will be affected/interrupted.[47]

text: Memory errors in Abnormal Psychology[edit]

text: Abnormal psychology is the branch of psychology that studies unusual patterns of behavior, emotion and thought, which may or may not be understood as a mental disorder. Memory errors can commonly be found in types of abnormal psychology such as Alzheimer's Disease, depression and schizophrenia.

text: Alzheimer's Disease[edit]

text: Alzheimer’s Disease is characterized by progressive memory impairment and decline, usually beginning short-term memory.[37] As it is a progressive disease, Alzheimer’s usually begins with memory errors before proceeding to long-term memory stores. One form of memory error occurs in contrast to the theory of retrieval cues in being a reason for the occurrence of memory errors. As noted above, memory errors may be due to the lack of cues that can trigger a memory trace and bring it to awareness. However, studies have shown that the opposite may be true for patients with Alzheimer’s, such that cues may actually decrease perform on priming tasks.[48] Patients also demonstrate errors known as misattribution errors, otherwise known as source confusion. However, studies show that these misattribution errors are dependent on whether the task is a familiarity or recollection tas.[49] Although patients tend to exhibit a higher level of false recognitions than control groups.[50] researchers have shown that they may exhibit less false-recognition early in the test due to familiarity being slower to develop. However, the observation of increasing instances of misattribution errors can be seen once familiarity does occur.[49] This may be related to the retrieval cue speculation, in that familiar memories often contain cues we know, and thus may be the reason why familiarity can contribute to memory errors. Lastly, many studies have shown that Alzheimer’s patients commonly suffer from intrusion errors. Relative to the findings that retrieval cues may actually hurt recall performance, one study by Kramer et al. showed that intrusions are most commonly associated with cue-recall tasks.[51] This study suggests that cues may lead to intrusions because patients may have a difficult time distinguishing between cues and distractions,[51] which may help explain why cues increase memory errors in patients with Alzheimer’s. Since verbal intrusions are a common aspect of Alzheimer’s.[52] some researchers believe that this characteristic may be helpful in the diagnosis of the disease.[53]

text: Depression[edit]

text: Memory errors can occur in patients with depression or with depressive symptoms. Patients with depressive symptoms have a tendency to experience what is known as the negative triad, which is the perspective use of negative schemas and self-concepts to relate to the external world. Due to this negative triad, depressive patients have a tendency to have a much greater focus on, and recall for, negative details and events over positive ones. This may lead to memory errors related to the positive details of memories, impairing the accuracy or even complete recall of such memories. Depressed patients also experience deficits in psychomotor speed and in free recall of material both immediate and delayed. This suggests that material has been encoded but that patients are particularly impaired with regard to search and retrieval processes.[54] Diverse aspects of memory such as short-term memory, long-term memory, semantic memory and implicit memory, have been studied and linked to depression. Short-term memory, a temporary store for newly acquired information, seems to show no major impairments in the case of depressive patients who do seem to complain about poor concentration, which by itself can cause simple memory errors.[54] Long-term memory, large capacity able to retain information over long periods of time, does however show impairment in the case of depressed individuals. They tend to have difficulties in recall and recognition for both verbal and visuo-spatial material with intervals of a few minutes or even hours creating complex memory errors in relation to speech and surrounding details.[54] Individuals suffering with depression also showed a specific deficit in retrieving information meaningfully organized in their semantic memory, conceptual knowledge about the real world.[54] Therefore, depressive patients can show memory errors for the most meaningful events in their lives, unable to recall these specific moments vividly like someone not suffering from depression might. In the case of implicit memory, when previous information influences ongoing responses, there has been little to no proof of a deficit in relations to depressed individuals.[54]

text: Schizophrenia[edit]

text: Memory errors, specifically intrusion errors and imagination inflation effects, have been found to occur in patients diagnosed with schizophrenia. Intrusion errors can commonly be found in the recall portion of a memory test when a participant includes items that were not on the original list that was presented.[55] These types of errors are linked to problems with self-monitoring, increased positive and disorganized symptoms (confusion within the brain), and poor executive functioning.[55] Intrusion errors are found to be more likely in patients with positive schizophrenic symptoms, which involve an excess of normal bodily functions (e.g. delusions), versus negative schizophrenic symptoms, which involve a decrease in normal bodily functions (e.g. refusal to speak).[56] Possible reasons for this are reduced function in the central executive of the working memory, as well as defects in self-reflectivity, organization and reasoning. Self-reflectivity is the ability to recognize and reason about one’s own thought process, recognize that one has thoughts, and that those thoughts are one’s own and differentiate between cognitive operations.[55] Self-reflectivity has been shown to be one of the biggest deficits faced by schizophrenics and data suggests that verbal memory intrusions are linked to deficits in the ability to identify, organize, and reason about one's own thoughts in patients with schizophrenia.[55] Imagination inflation effects were also common memory errors in patients with schizophrenia. This effect refers to events that individuals have imagined so vividly in their minds that this adds belief to the fact that the event truly occurred, although it did not. Possible reasons for this are increased source confusion and/or decreased source recollection of an event, which shows poor use of source-monitoring processes.[57] Source-monitoring processes allow one to distinguish between a memory that we may believe has happened because it seems familiar and one that has truly occurred. In the case of schizophrenics, whose abilities to reason through their thoughts is impaired, something that they have imagined and thus, seems familiar can easily be mistaken for an actual event, especially in the case of quick heuristic processes and snap judgments.[57] Continuously imagining an action or event makes this action more and more familiar thus making it harder for a patient with schizophrenia to distinguish its source, questioning whether it is familiar because they have imagined it or if it is familiar because it happened. This leads to many memory errors for these individuals who are led to believe by their imagination of the event that it is real, has occurred and thus is stored in their memory for that reason.[57]

text: Consequences of memory errors[edit]

text: Memory errors often lead to the belief of new memories, which are problematic. In the case of eyewitness testimony new false memories can often lead to wrong information and lack of conviction or wrongful conviction of individuals. Also in the case of child abuse, memory errors can lead to the creation of false traumatic childhood memories, which can lead to false accusations and loss of trust.

text: Eyewitness testimony[edit]

text: Memory errors can occur in eyewitness testimonies due to a number of features commonly present in a trial, all of which may influence the authenticity of the memory, and may be detrimental to the outcome of the case at hand. Such features include:

text: • Leading questions – refers to how wording of questions can influence how an event is remembered. This can result from a misinformation effect or an imagination inflation effect.[58] The misinformation effect occurs when information is presented after the events in question have occurred which leads to memory errors in later retrieval.[59] Studies have suggested that witnesses may misattribute accuracy to misleading information because the sources of misleading information and witnessed information become confused.[59] Misleading information can be acquired through reading of the newspaper, watching the news, being interviewed or when sitting in the courthouse during the trial. When witnesses are asked to recall specific details of an event they can begin to doubt their memory, which can cause memory errors. Misinformation can manifest itself as a memory leading the individual to believe it as true and witnesses may also begin to doubt their own memories of the event deciding instead that they must be wrong.[59] Memory errors also occur through the imagination inflation effect. As stated earlier, the imagination inflation effect takes place when an individual imagines an event to the point where it is believed as a memory of an actual event.[58] During trial, witnesses hear many different possible occurrences of events and are led to imagine these situations. Through imagining and rehearsal of the occurrences, witnesses may begin to see vividness and validity in the stories simply from rehearsal, not factual memories.[58] This can create problems for witnesses when trying to distinguish between imagined events and the actual occurrence of the events. Small but largely significant details become easily mixed and these occurrences of memory errors can make or break a trial.

text: • Weapons Focus Effect–refers to the fact that witnesses are highly likely to pay close attention to the weapon being used during an event, which creates a reduction in the ability to remember other details regarding the crime.[60] This can in turn create memory errors leaving the witness less able to remember details such as what the assailant was wearing or what distinctive features could be found on their body or face. One explanation for why witnesses tend to gravitate toward the weapon being used is said to be that the arousal of the witness is increased.[61] When arousal becomes increased the number of perceptional cues being utilized by the brain decreases.[61] This allows the individual to focus on the weapon cue and ignore other cues such as distinct scars or a bright red shirt. The weapons focus effect can also refer to how the report of the use of weapons in the case can influence the memory of the event, leading to a false memory of having heard a weapon being fired even if the witness did not.[61] For example, if a newspaper reports that the victim was beaten with a hammer, upon reading this, the witness will begin to believe that a hammer was in fact used, even if they at no point saw a hammer. This can cause many memory errors and conflict of stories for witnesses. As a society we believe that newspapers or televised news reports have fact behind them. If they report the hammer being used, a witness might begin to second-guess their memory wondering if they missed the hammer or failed to remember that detail.[60] Also, their story may become mixed with the media's representation of the story and the knife that they did see will be forgotten and instead be replaced with the hammer that was reported.[61]

text: • Familiarity Effect–refers to the tendency of individuals to develop a preference for things simply because they are familiar.[62] This can leave an individual to identify familiar people as guilty, even if they are not. When we are continuously exposed to the same object or person we begin to develop a positive attraction towards said object or person. Simply their familiarity creates a positive sense when re-exposed to the individual or object. In reality one can know very little about a person but by seeing them over and over again can gain unconscious positive recall for their face. This can create memory errors when individuals are asked to identify a criminal and someone familiar to them is placed in the line up. When a familiar face is in among the individuals that the witness is being asked to study, the witness will find himself or herself gravitating towards the familiar face whether or not this is who they witnessed committing the crime. This leaves them more likely to ignore the cues that are leading them towards other individuals and concentrate on the familiar face, resulting in a false accusation. The sense of familiarity can play a large role in the identification of criminals but when the familiarity of a criminal is mixed in with the familiarity of other individuals, choosing the right person can become quite difficult.

text: Child abuse[edit]

text: Memory errors regarding the recovery of repressed childhood abuse can occur due to post-event suggestions from a trusted source, such as a family member, or more commonly, a mental health professional. Due to possible relationships between childhood abuse and mental illness later in life, some mental health professionals believe in the Freudian theory of repressed memories as a defense mechanism for the anxiety that recall of the abuse would cause. Freud said that repression operates unconsciously in individuals who are not able to recall a threatening situation or may even forget that the abusive individual was ever part of their lives. Therefore, mental health professionals will sometimes seek to uncover possible instances of childhood abuse in patients, which may lead to suggestibility and cause a false memory of childhood abuse to arise, in an attempt to seek a cause to a mental illness[63] No matter the confidence in the memory, this does not necessarily equate to the memory being true. This is an example of the misinformation effect and false memory effect. The fact that memories are not retrieved as whole entities but rather are reconstructed from information remaining in memory and other related knowledge make them easily susceptible to memory errors.[64] This explains why working with mental health professionals and leading questions can sometimes manifest false memories by creating knowledge of possible events and asking individuals to focus on if these events actually took place[65] Individuals begin to overthink these situations visualizing them in their mind and overanalyzing them. This in turn leads to the belief of situations and vivid memories. Patients are left with memories they believe are real and new events from their childhood which can lead to stress and trauma in their adult life and loss of relationships with those who are believed to be the abuser.


document_title: Erum (name)

question_text: what is the meaning of name iram in urdu

root

text: Erum (name)

text: Erum is a Muslim name meaning "Jannat" in Persian and Urdu which means 'Heaven' in English, with different spellings such as Irum and Iram.

tag: p

text: In Persian folklore it also refers to the story of King Shaddad who wanted to compete with God and said that he would create Baghe 'Erum' (heaven on earth). To create this heaven he used up all his wealth and power even snatching from the poor. He made it so beautiful that it was heard to have fountains of wine and milk and rocks of the most precious gems that one could ever imagine. His cruelty is said to have upset God and God decided to punish him, so that he would never lay eyes on Erum. Just when Shaddad was about to enter the gates of Erum he tripped on the steps and died on the spot.

text: Notable persons with this name[edit]

text: Erum Ali, Indian fashion designer

tag: ul

text: Given names


document_title: List of Twenty20 International records

question_text: who has scored the most t20 runs for india

question_tokens: who has scored the most t20 runs for india

text: List of Twenty20 International records

text: Listing notation[edit]

text: Team notation

text:
(100/3) indicates that a team scored 100 runs for three wickets and the innings was closed, either due to a successful run chase or if no overs remained (or are able) to be bowled.
(100) indicates that a team scored 100 runs and was all out, either by losing all ten wickets or by having one or more batsmen unable to bat and losing the remaining wickets.

text: Batting notation

text:
(100*) indicates a batsman scored 100 runs and was not out.
(75) indicates that a batsman scored 75 runs and was out after that.

text: Bowling notation

text:
(5/40) indicates that a bowler has captured 5 wickets while giving away 40 runs.
(19.5 overs) indicates that a team bowled 19 complete overs (each of six legal deliveries), and one incomplete over of just five deliveries.

text: Currently playing

text: Record holders who are currently playing T20Is (i.e. their record details listed could change) are shown by .

text: Team records[edit]

text: Overall results[edit]

text:
Team

Mat

Won

Lost

Tie+W

Tie+L

NR

Win %

 Afghanistan

66

44

22

0

0

0

66.66

 Australia

106

56

47

0

2

1

54.28

 Bangladesh

79

23

54

0

0

2

29.87

 Bermuda

3

0

3

0

0

0

0.00

 Canada

19

4

14

0

1

0

23.68

 England

104

49

50

1

0

4

49.50

 Hong Kong

24

10

14

0

0

0

41.66

 ICC World XI

4

1

3

0

0

0

25.00

 India

104

65

36

1

0

2

64.21

 Ireland

67

27

33

0^

0

6

45.08

 Kenya

29

10

19

0

0

0

34.48

   Nepal

11

3

8

0

0

0

27.27

 Netherlands

49

26

21

0

0

2

55.31

 New Zealand

111

54

49

2

3

3

52.31

 Oman

17

5

11

0

0

1

31.25

 Pakistan

133

83

47

1

2

0

63.53

 Papua New Guinea

9

3

6

0

0

0

33.33

 Scotland

50

20

26

0^

0

3

43.90

 South Africa

103

60

42

0

0

1

58.82

 Sri Lanka

106

54

50

1

0

1

51.90

 United Arab Emirates

26

9

17

0

0

0

34.61

 West Indies

98

46

45

2

1

4

50.53

 Zimbabwe

59

13

45

1

0

0

22.88

The result percentage excludes no results and counts ties (irrespective of a tiebreaker) as half a win.Last updated: 8 July 2018[2]

^  On 17 June 2018, a T20I between Scotland and Ireland was ended in a tie, though no Super Over was played. It was the tenth T20I match to end in a tie, and the first since the ICC playing conditions were implemented in September 2017, not to end with a Super Over.

tag: table

text: Highest innings totals[edit]

text:
Score

Batting team

Opposition

Venue

Date

Scorecard

263/3 (20.0 overs)

 Australia

 Sri Lanka

Pallekele

6 September 2016

Scorecard

260/5 (20.0 overs)

 India
 Sri Lanka
Indore
22 December 2017
Scorecard

260/6 (20.0 overs)

 Sri Lanka

 Kenya

Johannesburg

14 September 2007

Scorecard

248/6 (20.0 overs)

 Australia
 England
Southampton
29 August 2013
Scorecard

245/5 (18.5 overs)

 Australia
 New Zealand
Auckland
16 February 2018
Scorecard

Updated: 16 February 2018[3]

text: Highest successful chases[edit]

text:
Score

Batting team

Opposition

Venue

Date

Scorecard

245/5 (18.5 overs)

 Australia
 New Zealand
Auckland
16 February 2018
Scorecard

236/6 (19.2 overs)

 West Indies
 South Africa
Johannesburg
11 January 2015
Scorecard

230/8 (19.4 overs)

 England
 South Africa
Mumbai
18 March 2016
Scorecard

215/5 (19.4 overs)

 Bangladesh
 Sri Lanka
Colombo
10 March 2018
Scorecard

211/4 (19.2 overs)

 India
 Sri Lanka
Mohali
12 December 2009
Scorecard

Updated: 10 March 2018[4]

text: Lowest innings totals[edit]

text:
Score

Batting team

Opposition

Venue

Date

Scorecard

39 (10.3 overs)

 Netherlands
 Sri Lanka
Chittagong
24 March 2014
Scorecard

53 (14.3 overs)

   Nepal
 Ireland
Belfast
13 July 2015
Scorecard

56 (18.4 overs)

 Kenya
 Afghanistan
Sharjah
30 September 2013
Scorecard

57 (19.3 overs)

 New Zealand
 Sri Lanka
Chittagong
31 March 2014
Scorecard

60 (13.4 overs)

 West Indies
 Pakistan
Karachi
1 April 2018
Scorecard

Qualification: Only completed innings in matches that did not have overs reduced are included. Updated: 12 March 2017
[5]

If the qualification is removed, there are 14 innings that have scores lower than the 39 scored by the Netherlands. Six of those innings were 0/0 (0 overs), of which four came in matches abandoned with a toss and two were in no results.[6]
The lowest innings total that a team has scored in a loss is 29/1 by Zimbabwe. Batting second, Zimbabwe were chasing a total of 174 which was set by Sri Lanka. After 5 overs were completed in Zimbabwe's innings, rain interrupted play with Zimbabwe at 29/1. With no further play possible, the par score was calculated and Zimbabwe were adjudged to be short by 14 runs.[7]
The lowest innings total that a team has scored in a win is 36/1 by New Zealand against Zimbabwe. Batting second, New Zealand were chasing a total of 85 when after 8.1 overs were completed, rain prevented any further play from occurring. The par score was calculated and New Zealand were adjudged to be ahead by 7 runs.[8]
The lowest innings total that a team has scored after batting 20 overs is 70 by Bermuda against Canada. Canada went on to win the match by 8 wickets.[9]

text: Highest margin of victory (by runs)[edit]

text:
Margin

Teams

Venue

Date

Scorecard

172 runs

 Sri Lanka (260/6) beat  Kenya (88)
Johannesburg
14 September 2007
Scorecard

143 runs

 Pakistan (203/5) beat  West Indies (60)
Karachi
1 April 2018
Scorecard

143 runs

 India (213/4) beat  Ireland (70)
Malahide
29 June 2018
Scorecard

130 runs

 South Africa (211/5) beat  Scotland (81)
London
7 June 2009
Scorecard

119 runs

 New Zealand (243/5) beat  West Indies (124)
Mount Maunganui
3 January 2018
Scorecard

Updated: 29 June 2018
[10]

text: Highest margin of victory (by balls remaining)[edit]

text:
Balls Rem

Teams

Venue

Date

Scorecard

90 balls

 Sri Lanka (40/1) beat  Netherlands (39)
Chittagong
24 March 2014
Scorecard

76 balls

 Ireland (72/0) beat  Kenya (71)
Dubai (DSC)
14 March 2012
Scorecard

74 balls

 New Zealand (74/1) beat  Kenya (73)
Durban
12 September 2007
Scorecard

73 balls

 Afghanistan (75/0) beat  Ireland (71)
Dubai
20 January 2017
Scorecard

72 balls

 Ireland (54/2) beat    Nepal (53)
Belfast
13 July 2015
Scorecard

Updated: 12 March 2017
[11]

text: Highest margin of victory (by wickets)[edit]

text:
Margin

Teams

Venue

Date

Scorecard

10 wickets

 New Zealand (171/0) beat  Pakistan (168/7)
Hamilton
17 January 2016

Scorecard

10 wickets

 England (143/0) beat  New Zealand (139/8)
Wellington
15 February 2013
Scorecard

10 wickets

 South Africa (132/0) beat  Pakistan (129/8)
Johannesburg
2 February 2007
Scorecard

10 wickets

 England (128/0) beat  West Indies (125)
London (Oval)
23 September 2011
Scorecard

10 wickets

 New Zealand (127/0) beat  Zimbabwe (123/8)
Harare
15 October 2011
Scorecard

10 wickets

 Kenya (126/0) beat  Scotland (123)
Nairobi (Gym)
4 February 2010
Scorecard

Updated: 12 March 2017[12]

text: Smallest margin of victory (by runs)[edit]

text:
Margin

Teams

Venue

Date

Scorecard

1 run

 West Indies (245/6) beat  India (244/4)
Florida
27 August 2016
Scorecard

1 run

 India (146/7) beat  Bangladesh (145/9)
Bengaluru
23 March 2016
Scorecard

1 run

 Australia (150/7) beat  New Zealand (149/5)
Sydney
15 February 2009
Scorecard

1 run

 South Africa (128/7) beat  New Zealand (127/5)
Lord's
9 June 2009
Scorecard

1 run [a]

 England (202/6) beat  South Africa (127/3)
Johannesburg
13 November 2009
Scorecard

1 run

 New Zealand (133/7) beat  Pakistan (132/7)
Bridgetown
8 May 2010
Scorecard

1 run

 South Africa (120/7) beat  West Indies (119/7)
North Sound
20 May 2010
Scorecard

Updated: 27 August 2016
[13]

^[a]  Rain interrupted play in South Africa's innings with South Africa having scored 127/3 after 13 overs. The par score at this point was 128. Rain prevented the match from resuming and England won by 1 run.

text: Smallest margin of victory (by wickets)[edit]

text:
Margin

Teams

Venue

Date

Scorecard

1 wicket

 England (158/9) beat  Australia (157/4)
Adelaide
12 January 2011
Scorecard

1 wicket

 Netherlands (131/9) beat  Kenya (128)
The Hague
26 July 2012
Scorecard

1 wicket

 Pakistan (174/9) beat  Sri Lanka (172/7)
Colombo (RPS)
1 August 2015
Scorecard

Updated: 3 April 2016
[14]

text: Tied matches[edit]

text:
Teams

Tie Break

Venue

Date

Scorecard

 West Indies (126/8) tied  New Zealand (126/7)

New Zealand won bowl-out
Auckland
16 February 2006
Scorecard

 India (141/9) tied  Pakistan (141/7)

India won bowl-out
Durban
14 September 2007
Scorecard

 Canada (135/7) tied  Zimbabwe (135/9)

Zimbabwe won bowl-out
King City
11 October 2008
Scorecard

 West Indies (155/8) tied  New Zealand (155/7)

West Indies won Super Over
Auckland
26 December 2008
Scorecard

 Australia (214/4) tied  New Zealand (214/6)

New Zealand won Super Over
Christchurch
28 February 2010
Scorecard

 Australia (151/4) tied  Pakistan (151/8)

Pakistan won Super Over
Dubai (DSC)
7 September 2012
Scorecard

 Sri Lanka (174/6) tied  New Zealand (174/7)

Sri Lanka won Super Over
Pallekele
27 September 2012
Scorecard

 West Indies (139) tied  New Zealand (139/7)

West Indies won Super Over
Pallekele
1 October 2012
Scorecard

 England (154/8) tied  Pakistan (154/7)

England won Super Over
Sharjah
30 November 2015
Scorecard

 Scotland (185/4) tied  Ireland (185/6)

No Super Over
Sportpark Het Schootsveld, Deventer
17 June 2018
Scorecard

Even though tie-breakers were used to determine a winner in these matches, for statistical purposes, these matches are considered as ties. Updated: 17 June 2018
[15]

text: Most consecutive wins by a team[edit]

text:
Wins

Team

First win

Last win

11

 Afghanistan
 West Indies at Nagpur, 27 March 2016 (Scorecard)
 Ireland at Greater Noida, 12 March 2017 (Scorecard)

8

 England
 Pakistan at Bridgetown, 6 May 2010 (Scorecard)
 Australia at Adelaide, 12 January 2011 (Scorecard)

8

 Ireland
 Kenya at Mombasa, 22 February 2012 (Scorecard)
 Afghanistan at Dubai (DSC), 24 March 2012 (Scorecard)

8

 Pakistan
 New Zealand at Auckland, 25 January 2018 (Scorecard)
 Zimbabwe  at Harare, 1 July 2018 (Scorecard)

7

 South Africa
 Australia at Johannesburg, 27 March 2009 (Scorecard)
 India at Nottingham, 16 June 2009 (Scorecard)

7

 Pakistan
 New Zealand at London (Oval), 13 June 2009 (Scorecard)
 New Zealand at Dubai (DSC), 13 November 2009 (Scorecard)

7

 India
 Pakistan at Ahmedabad, 28 December 2012 (Scorecard)
 South Africa at Dhaka, 4 April 2014 (Scorecard)

7

 India
 Sri Lanka at Ranchi, 12 February 2016 (Scorecard)
 Bangladesh at Dhaka, 6 March 2016 (Scorecard)

7

 India
 Bangladesh at Colombo, 8 March 2018 (Scorecard)
 England at Manchester, 3 July 2018 (Scorecard)

No results are treated the same as losses and ties in the above table. A no result occurs when a match is abandoned partway through, usually due to rain.Updated: 11 July 2018[16]

text: Most consecutive defeats[edit]

text:
Defeats

Team

First defeat

Last defeat

16

 Zimbabwe
 Sri Lanka at Providence, 3 May 2010 (Scorecard)
 West Indies at North Sound, 3 March 2013 (Scorecard)

12

 Netherlands
 South Africa at Cape Town, 15 September 2007 (Scorecard)
 Australia at Bridgetown, 5 May 2010 (Scorecard)

9

 United Arab Emirates
 Sri Lanka at Dhaka, 25 February 2016 (Scorecard)
 Ireland at Dubai, 18 January 2017 (Scorecard)

8

 Bangladesh
 Pakistan at Kolkata, 16 March 2016 (Scorecard)
 Sri Lanka at Colombo, 4 April 2017 (Scorecard)

No results are treated the same as losses and ties in the above table. A no result occurs when a match is abandoned partway through, usually due to rain.* indicates that the sequence is ongoing   Updated: 12 April 2017[17]

text: Most sixes in an innings[edit]

text:
Sixes

Batting Team

Opposition

Venue

Date

Scorecard

21

 West Indies
 India
Lauderhill
27 August 2016
Scorecard

 India
 Sri Lanka
Indore
22 December 2017
Scorecard

19

 Netherlands
 Ireland
Sylhet
21 March 2014
Scorecard

18

 Australia
 England
Southampton
29 August 2013
Scorecard

 New Zealand
 Australia
Auckland
16 February 2018
Scorecard

Updated: 16 February 2018[18]

text: Most fours in an innings[edit]

text:
Fours

Batting team

Opposition

Venue

Date

Scorecard

30

 Sri Lanka
 Kenya
Johannesburg
14 September 2007
Scorecard

29

 Sri Lanka
 India
Nagpur
9 December 2009
Scorecard

26

 West Indies
 South Africa
Johannesburg
11 January 2015
Scorecard

25

 Australia
 Sri Lanka
Pallekele
6 September 2016
Scorecard

24

 South Africa
 West Indies
Johannesburg
11 September 2007
Scorecard

Updated: 6 September 2016[19]

text: Most sixes in a match[edit]

text:
Sixes

Teams

Venue

Date

Scorecard

32

 West Indies (21) v  India (11)
Lauderhill
27 August 2016
Scorecard

32

 New Zealand (18) v  Australia (14)
Eden Park
16 February 2018
Scorecard

31

 India (21) v  Sri Lanka (10)
Indore
22 December 2017
Scorecard

30

 Ireland (11) v  Netherlands (19)
Sylhet
21 March 2014
Scorecard

28

 Afghanistan (16) v  Ireland (12)
Greater Noida
12 March 2017
Scorecard

Updated: 22 December 2017[20]

text: Highest aggregate runs in a single match[edit]

text:
Runs

Teams

Venue

Date

Scorecard

489

 West Indies (245/6) v  India (244/4)
Florida
27 August 2016
Scorecard

488

 New Zealand (243/6) v  Australia (245/5)[18.5]
Auckland
16 February 2018
Scorecard

467

 South Africa (231/7) v  West Indies (236/6) [19.2]
Johannesburg
11 January 2015
Scorecard

459

 South Africa (229/4) v  England (230/8)
Mumbai
18 March 2016
Scorecard

457

 Australia (248/6) v  England (209/6)
Southampton
29 August 2013
Scorecard

Updated: 7 September 2016[21]

text: Most fours in a match[edit]

text:
Fours

Teams

Venue

Date

Scorecard

47

 India (18) v  Sri Lanka (29)
Nagpur
9 December 2009
Scorecard

44

 South Africa (18) v  West Indies (26)
Johannesburg
11 January 2015
Scorecard

43

 South Africa (24) v  West Indies (19)
London
13 June 2009
Scorecard

43

 Bangladesh (22) v  Pakistan (21)
Kandy
25 September 2012
Scorecard

43

 England (24) v  Australia (19)
Southampton
29 August 2013
Scorecard

43

 Australia (24) v  India (19)
Rajkot
10 October 2013
Scorecard

Updated: 22 December 2017[22]

text: Individual records (batting)[edit]

text: Most career runs[edit]

text:
Runs

Innings

Batsman

Team

T20I career span

2,271

73
Martin Guptill ‡
 New Zealand
2009–present

2,140

70
Brendon McCullum
 New Zealand
2005–2015

2,121

96
Shoaib Malik ‡
 Pakistan
2006–present

2,102

58
Virat Kohli ‡
 India
2010–present

2,086

77
Rohit Sharma ‡
 India
2007–present

Updated: 8 July 2018[23]

text: Most runs in a calendar year[edit]

text:
Runs

Innings

Batsman

Team

Year

641

13
Virat Kohli
 India
2016

520

15
Mohammad Shahzad
 Afghanistan
2016

516

13
Fakhar Zaman
 Pakistan
2018

497

18
Rohit Sharma
 India
2016

472

13
Martin Guptill
 New Zealand
2012

Updated: 8 July 2018[24]

text: Most 50+ Scores[edit]

text:
50+ (100+50)

Innings

Batsman

Team

T20I career span

18 (0+18)

58
Virat Kohli
 India
2010–present

18 (3+15)

77
Rohit Sharma
 India
2007–present

16 (2+14)

73
Martin Guptill
 New Zealand
2009–present

15 (2+13)

52
Chris Gayle
 West Indies
2006–present

15 (2+13)

70
Brendon McCullum
 New Zealand
2005–2015

Updated: 8 July 2018[25]

text: Highest career strike rate[edit]

text:
Strike rate

Balls faced

Batsman

Team

T20I career span

165.68

647
Glenn Maxwell
 Australia
2012–present

163.59

717
Colin Munro
 New Zealand
2012–present

154.96

468
Evin Lewis
 West Indies
2016–present

151.69

795
Aaron Finch
 Australia
2011–present

150.75

932
Shahid Afridi
 Pakistan
2006–2016

Qualification: 250 balls.Updated: 21 February 2018[26]

text: Highest career average[edit]

text:
Average

Innings

Runs

Batsman

T20I career span

53.00
20
742
 Babar Azam ‡
2016–present

48.88
58
2,102
 Virat Kohli ‡
2010–present

45.60
42
1,596
 Aaron Finch ‡
2011–present

42.91
21
515
 Manish Pandey ‡
2015–present

37.95
70
1822
 JP Duminy ‡
2007–present

Qualification: 20 innings
Source:  Cricinfo. Last updated: 8 July 2018.

text: Most career ducks[edit]

text:
Ducks

Innings

Batsman

Team

T20I career span

10
79
Tillakaratne Dilshan
 Sri Lanka
2006–2016

9
45
Luke Wright
 England
2007–2014

9
58
Kevin O'Brien‡
 Ireland
2008–present

8
77
Umar Akmal
 Pakistan
2009–2016

8
91
Shahid Afridi
 Pakistan
2006–2018

Last updated: 3 July 2018[27]

text: Most career sixes[edit]

text:
Sixes

Balls faced

Batsman

Team

T20I career span

103

1123
Chris Gayle
 West Indies
2006–present

103

1709
Martin Guptill
 New Zealand
2009–present

91

1571
Brendon McCullum
 New Zealand
2005–2015

89

1522
Rohit Sharma
 India
2007–present

83

1006
Shane Watson
 Australia
2006–2016

Updated:8 July 2018[28]

text: Most career fours[edit]

text:
Fours

Balls faced

Batsman

Team

T20I career span

223

1567
Tillakaratne Dilshan
 Sri Lanka
2006–2016

216

1410
Mohammad Shahzad
 Afghanistan
2010–present

214

1543
Virat Kohli
 India
2010–present

200

1709
Martin Guptill
 New Zealand
2009–present

199

1571
Brendon McCullum
 New Zealand
2005–2015

Updated:9 July 2018[29]

text: Highest individual score[edit]

text:
Runs

Batsman

Batting team

Opposition

Venue

Date

Scorecard

172

Aaron Finch
 Australia
 Zimbabwe
Harare
3 July 2018

Scorecard

156

Aaron Finch
 Australia
 England
Southampton
29 August 2013
Scorecard

145*

Glenn Maxwell
 Australia
 Sri Lanka
Pallekele
6 September 2016
Scorecard

125*

Evin Lewis
 West Indies
 India
Kingston
9 July 2017
Scorecard

124*

Shane Watson
 Australia
 India
Sydney
31 January 2016
Scorecard

Updated: 3 July 2018[30]

text: Highest individual score (by batting position)[edit]

text:
Runs

Position

Batsman

Batting team

Opposition

Venue

Date

Scorecard

172

Position 1
Aaron Finch
 Australia
 Zimbabwe
Harare
3 July 2018

Scorecard

145*

Position 2
Glenn Maxwell
 Australia
 Sri Lanka
Pallekele
6 September 2016
Scorecard

123

Position 3
Brendon McCullum
 New Zealand
 Bangladesh
Pallekele
21 September 2012
Scorecard

110*

Position 4
K. L. Rahul
 India
 West Indies
Lauderhill
27 August 2016
Scorecard

101*

Position 5
David Miller
 South Africa
 Bangladesh
Potchefstroom
29 October 2017
Scorecard

85*

Position 6
Cameron White
 Australia
 Sri Lanka
Bridgetown
9 May 2010
Scorecard

89

Position 7
Mohammad Nabi
 Afghanistan
 Ireland
Greater Noida
12 March 2017
Scorecard

57*

Position 8
Simi Singh
 Ireland
 Netherlands
Rotterdam
12 June 2018
Scorecard

46

Position 9
Anwar Ali
 Pakistan
 Sri Lanka
Colombo (RPS)
1 August 2015
Scorecard

40

Position 10
Sompal Kami
   Nepal
 Hong Kong
Colombo (PSS)
24 November 2014
Scorecard

18

Position 11
Paul van Meekeren
 Netherlands
 Hong Kong
Dubai
18 January 2017
Scorecard

Updated: 3 July 2018[31]

text: Fastest 50[edit]

text:
Balls

Batsman

Batting team

Opposition

Venue

Date

Scorecard

12

Yuvraj Singh
 India
 England
Durban
19 September 2007
Scorecard

14

Colin Munro
 New Zealand
 Sri Lanka
Auckland
10 January 2016
Scorecard

17

Paul Stirling
 Ireland
 Afghanistan
Dubai (DSC)
24 March 2012
Scorecard

17

Stephan Myburgh
 Netherlands
 Ireland
Sylhet
21 March 2014
Scorecard

17

Chris Gayle
 West Indies
 South Africa
Cape Town
9 January 2015
Scorecard

Updated: 29 August 2016[32]

text: Fastest 100[edit]

text:
Balls

Batsman

Batting team

Opposition

Venue

Date

Scorecard

35

Rohit Sharma
 India
 Sri Lanka
Indore
22 December 2017
Scorecard

35

David Miller
 South Africa
 Bangladesh
Potchefstroom
29 October 2017
Scorecard

45

Richard Levi
 South Africa
 New Zealand
Hamilton
19 February 2012
Scorecard

46

K. L. Rahul
 India
 West Indies
Florida
27 August 2016
Scorecard

46

Francois du Plessis
 South Africa
 West Indies
Johannesburg
11 January 2015
Scorecard

Updated: 22 December 2017[33]

text: Most sixes in an innings[edit]

text:
Sixes

Batsman

Batting team

Opposition

Venue

Date

Scorecard

14 (63)

Aaron Finch
 Australia
 England
Southampton
29 August 2013
Scorecard

13 (51)

Richard Levi
 South Africa
 New Zealand
Hamilton
19 February 2012
Scorecard

11 (48)

Chris Gayle
 West Indies
 England
Mumbai
16 March 2016
Scorecard

10 (41)

Corey Anderson
 New Zealand
 Bangladesh
Mount Maunganui
8 January 2017
Scorecard

10 (43)

Rohit Sharma
 India
 Sri Lanka
Indore
22 December 2017
Scorecard

10 (53)

Colin Munro
 New Zealand
 West Indies
Mount Maunganui
3 January 2018
Scorecard

10 (57)

Chris Gayle
 West Indies
 South Africa
Johannesburg
11 September 2007
Scorecard

Updated: 3 January 2018

text: Most fours in an innings[edit]

text:
Fours

Batsman

Batting team

Opposition

Venue

Date

Scorecard

16 (76)

Aaron Finch
 Australia
 Zimbabwe
Harare
3 July 2018
Scorecard

14 (55)

Herschelle Gibbs
 South Africa
 West Indies
Johannesburg
11 September 2007
Scorecard

14 (52)

Aaron Finch
 Australia
 India
Rajkot
10 October 2013
Scorecard

14 (65)

Glen Maxwell
 Australia
 Sri Lanka
Pallekele
6 September 2016
Scorecard

13 (53)

Ricky Ponting
 Australia
 India
Mumbai
20 October 2007
Scorecard

Number in parentheses represents the number of balls the batsman faced during the innings.Updated: 3 July 2018[34]

text: Most runs off an over[edit]

text:
Runs

Sequence

Batsman

Batting team

Bowler

Venue

Date

Scorecard

36

6–6–6–6–6–6
Yuvraj Singh
 India
 Stuart Broad
Durban
19 September 2007
Scorecard

32

6–6–w–6–6–6–1
Evin Lewis
 West Indies
 Stuart Binny
Lauderhill, Florida
27 August 2016
Scorecard

32

6–6–2–nb–(nb+4)–4–6–2
Jos Buttler
 England
 Wayne Parnell
Edgbaston
12 September 2012
Scorecard

32

4–wk–(nb+6)–(nb+1)–6–6–6–1[a]
Jonny BairstowLuke Wright
 England
 Izatullah Dawlatzai
Colombo (RPS)
21 September 2012
Scorecard

31

6–6–6–6–6–1
David Miller
 South Africa
 Mohammad Saifuddin
Potchefstroom
29 October 2017
Scorecard

Key:
nb – No-ball
(nb+X) – A no-ball was bowled and X runs were scored off the bat
Ynb – A no-ball was bowled with one run scored directly from the no-ball and Y-1 runs being scored from byes or leg byes (however, all Y runs will be scored as no-balls on the scorecard)[35]
w – Wide
wk – Wicket
Updated: 29 October 2017[36]^[a]  The over started with Buttler facing and Wright off strike. Buttler faced the first ball and was dismissed on the second ball of the over. Bairstow came in and faced the next two deliveries and Wright faced the last four deliveries.[37]

text: Individual records (bowling)[edit]

text: Most wickets in a career[edit]

text:
Wickets

Innings

Bowler

Team

T20I career span

98

97
Shahid Afridi
 Pakistan
2006–2018

90

68
Lasith Malinga
 Sri Lanka
2006–2017

85

60
Umar Gul
 Pakistan
2007–2016

85

63
Saeed Ajmal
 Pakistan
2009–2015

77

65
Shakib Al Hasan
 Bangladesh
2006–present

Updated: 01 November 2017[38]

text: Most wickets in a calendar year[edit]

text:
Wickets

Matches

Bowler

Team

Year

28

21
Jasprit Bumrah
 India
2016

27

14
Dirk Nannes
 Australia
2010

25

16
Saeed Ajmal
 Pakistan
2012

23

11
Yuzvendra Chahal
 India
2017

23

15
Rashid Khan
 Afghanistan
2016

23

17
Ravichandran Ashwin
 India
2016

Updated: 8 July 2018[39]

text: Most four-wickets-in-an-innings(and over) in a career[edit]

text:
4+ (4+5)

Matches

Bowler

Team

T20I career span

6 (4+2)

60
Umar Gul ‡
 Pakistan
2007–present

5 (3+2)

39
Ajantha Mendis
 Sri Lanka
2008–2014

4 (4+0)

64
Saeed Ajmal
 Pakistan
2009–2015

Updated: 3 April 2016[40]

text: Best career economy rate[edit]

text:
Economy rate

Overs bowled

Bowler

Team

T20I career span

5.70

131.1
Daniel Vettori
 New Zealand
2007–2014

5.93

121.0
Rashid Khan
 Afghanistan
2015–present

5.98

169.0
Samuel Badree
 West Indies
2012–present

6.02

171.4
Sunil Narine
 West Indies
2012–present

6.07

90.0
Imad Wasim
 Pakistan
2015–present

Qualification: 500 balls bowled. Updated: 21 February 2018[41]

text: Best career strike rate[edit]

text:
Strike rate

Wickets

Overs Bowled

Bowler

Team

T20I career span

12.96

56
121.0
Rashid Khan
 Afghanistan
2015–present

13.0

44
95.5
Ahsan Malik
 Netherlands
2012–present

13.4

66
147.3
Ajantha Mendis
 Sri Lanka
2008–2014

13.9

57
132.5
Imran Tahir
 South Africa
2013–present

14.1

85
200.3
Umar Gul
 Pakistan
2007–present

Qualification: 500 balls bowled.
Updated: 21 February 2018.[42]

text: Best career averages[edit]

text:
Average

Wickets

Runs conceded

Bowler

Team

T20I career span

12.82

56
718
Rashid Khan
 Afghanistan
2015–present

14.42

66
952
Ajantha Mendis
 Sri Lanka
2008–2014

15.85

57
904
Imran Tahir
 South Africa
2013–present

16.59

44
730
Ahsan Malik
 Netherlands
2012–present

16.84

51
859
Graeme Swann
 England
2005–2012

Qualification: 500 balls bowled.
Updated: 21 February 2018.[43]

text: Best figures in a match[edit]

text:
Figures

Bowler

Bowling team

Opposition

Venue

Date

Scorecard

6/8 (4.0 overs)

Ajantha Mendis
 Sri Lanka
 Zimbabwe
Hambantota
18 September 2012
Scorecard

6/16 (4.0 overs)

Ajantha Mendis
 Sri Lanka
 Australia
Pallekele
8 August 2011
Scorecard

6/25 (4.0 overs)

Yuzvendra Chahal
 India
 England
Bangalore
1 February 2017
Scorecard

5/3 (3.3 overs)

Rangana Herath
 Sri Lanka
 New Zealand
Chittagong
31 March 2014
Scorecard

5/3  (2.0 overs)

Rashid Khan
 Afghanistan
 Ireland
Greater Noida
10 March 2017
Scorecard

Updated: 10 March 2017[44]

text: Most runs conceded in an innings[edit]

text:
Runs

Bowling figures

Bowler

Bowling team

Opposition

Venue

Date

Scorecard

69

4–0–69–0
Barry McCarthy
 Ireland
 Afghanistan
Greater Noida
12 March 2017

Scorecard

68

4–0–68–1
Kyle Abbott
 South Africa
 West Indies
Johannesburg
11 January 2015
Scorecard

64

3.1–0–64–0
Ben Wheeler
 New Zealand
 Australia
Auckland
16 February 2018
Scorecard

64

4–0–64–1
James Anderson
 England
 Australia
Sydney
9 January 2007
Scorecard

64

4–0–64–0
Sanath Jayasuriya
 Sri Lanka
 Pakistan
Johannesburg
17 September 2007
Scorecard

64

4–0–64–0
Yuzvendra Chahal
 India
 South Africa
Centurion
21 February 2018
Scorecard

Bowling figures given above are in the form of "Overs-Maidens-Runs-Wickets".
Updated: 21 February 2018[45]

text: Hat-tricks[edit]

text:
Key

Hat-trick taken in a World Cup match

(b)

Bowled

(c)

Caught

(c b)

Caught and bowled

(lbw)

Leg before wicket

(st)

Stumped

Wicket-keeper

text:
No.

Bowler

For

Against

Wickets

Venue

Date

Ref.

1

Brett Lee

 Australia

 Bangladesh

Shakib Al Hasan (c Gilchrist)
Mashrafe Mortaza (b)
Alok Kapali (lbw)

Newlands Cricket Ground, Cape Town

16 September 2007

[46]

2

Jacob Oram

 New Zealand

 Sri Lanka

Angelo Mathews (c and b)
Malinga Bandara (c McCullum)
Nuwan Kulasekara (c Broom)

Premadasa Stadium, Colombo

2 September 2009

[47]

3

Tim Southee

 New Zealand

 Pakistan

Younis Khan (c Brownlie)
Mohammad Hafeez (c McGlashan)
Umar Akmal (lbw)

Eden Park, Auckland

26 December 2010

[48]

4

Thisara Perera

 Sri Lanka

 India

Hardik Pandya (c Senanayake)
Suresh Raina (c Chameera)
Yuvraj Singh (c Gunathilaka)

JSCA International Stadium Complex, Ranchi

12 February 2016

[49]

5

Lasith Malinga

 Sri Lanka

 Bangladesh

Mushfiqur Rahim (b)
Mashrafe Mortaza (b)
Mehedi Hasan (lbw)

R. Premadasa Stadium, Colombo

6 April 2017

[50]

6

Faheem Ashraf

 Pakistan

 Sri Lanka

Isuru Udana (c Hasan Ali)
Mahela Udawatte (c Babar Azam)
Dasun Shanaka (lbw)

Sheikh Zayed Stadium, Abu Dhabi

27 October 2017

[51]

Source: ESPNcricinfo. Last Updated: 27 October 2017

text: Individual records (fielding)[edit]

text: Most catches in T20I career[edit]

text:
Catches

Innings

Fielder

Team

T20I career span

44

81
Ross Taylor ‡
 New Zealand
2006–present

44

52
AB de Villiers
 South Africa
2006–2018

42

76
Suresh Raina ‡
 India
2006–present

41

70
David Warner ‡
 Australia
2009–present

40

101
Shoaib Malik ‡
 Pakistan
2006–present

The list excludes catches made as wicket-keeper  Updated: 4 July 2018[52]

text: Individual records (Wicket-Keeper)[edit]

text: Most dismissals in career[edit]

text:
Dismissals

Catches

Stumpings

Innings

Wicket-keeper

Team

T20I career span

78

49
33
87
MS Dhoni
 India
2006–present

60

28
32
53
Kamran Akmal
 Pakistan
2006–2017

52

25
27
59
Mohammad Shahzad
 Afghanistan
2010–present

51

32
19
58
Denesh Ramdin
 West Indies
2006–2016

47

22
25
58
Mushfiqur Rahim
 Bangladesh
2006–present

Innings refers to when the player was the designated keeper. All figures exclude catches not made as a wicketkeeper.Updated: 21 February 2018[53]

text: Most catches in career[edit]

text:
Catches

Innings

Wicket-keeper

Team

T20I career span

49

87
MS Dhoni
 India
2006–present

32

58
Denesh Ramdin
 West Indies
2006–present

28

53
Kamran Akmal
 Pakistan
2006–2017

30

31
Quinton de Kock
 South Africa
2012–present

26

34
Wesley Barresi
 Netherlands
2012–present

Innings refers to when the player was the designated keeper. All figures exclude catches not made as a wicketkeeper.Updated: 21 February 2018[54]

text: Most stumpings in career[edit]

text:
Stumpings

Innings

Wicket-keeper

Team

T20I career span

33

90
MS Dhoni
 India
2006–present

32

54
Kamran Akmal
 Pakistan
2006–2017

27

59
Mohammad Shahzad
 Afghanistan
2010–present

25

57
Mushfiqur Rahim
 Bangladesh
2006–present

20

56
Kumar Sangakkara
 Sri Lanka
2006–2014

Updated: 03 July 2018[55]

text: Individual records (others)[edit]

text: Most matches played in career[edit]

text:
Matches

Player

Team

T20I Career Span

103

Shoaib Malik
 Pakistan
2006–present

99

Shahid Afridi
 Pakistan
2006–2018

93

Mahendra Singh Dhoni
 India
2006–present

84

Rohit Sharma
 India
2007–present

83

Mohammad Hafeez
 Pakistan
2006–present

Updated: 8 July 2018[56]

text: Most matches as a captain[edit]

text:
Matches

Player

Team

T20I Career Span

72

MS Dhoni
 India
2007–2016

56

William Porterfield
 Ireland
2008–2017

47

Darren Sammy
 West Indies
2011–2016

44

Shahid Afridi
 Pakistan
2009–2018

41

Asghar Stanikzai
 Afghanistan
2015–present

Updated: 15 June 2018[57]

text: Most matches as an umpire[edit]

text:
Matches

Umpire

Country

T20I Career Span

43

Aleem Dar
 Pakistan
2009–present

37

Ian Gould
 England
2006–2016

35

Rod Tucker
 Australia
2009–2016

34

Simon Taufel
 Australia
2007–2012

33

Shaun George
 South Africa
2010–present

Updated: 17 June 2018[58]

text: Most matches as a match referee[edit]

text:
Matches

Referee

Country

T20I Career Span

87

Ranjan Madugalle
 Sri Lanka
2006–present

84

Chris Broad
 England
2005–present

80

Jeff Crowe
 New Zealand
2005–present

61

Javagal Srinath
 India
2006–present

53

David Jukes
 England
2010–present

Updated: 10 March 2017[59]

text: Most Player-of-the Match Awards[edit]

text:
No. of Awards

Player

Team

Matches

T20I Career Span

11

Shahid Afridi
 Pakistan
99
2006–2018

10

Virat Kohli
 India
57
2010–present

9

Chris Gayle
 West Indies
55
2006–present

Mohammad Nabi
 Afghanistan
60
2010–present

Mohammad Shahzad
 Afghanistan
60
2010–present

Shane Watson
 Australia
58
2006–2016

Last updated: 17 March 2018[60]

text: Partnership records[edit]

text: Highest overall partnership runs by a pair[edit]

text:
Runs

Innings

Players

Batting team

Highest

Average

100/50

T20I career span

1154

37
David Warner & Shane Watson
 Australia
133
31.18
3/6
2009–2016

1151

24
Martin Guptill & Kane Williamson
 New Zealand
171*
50.04
3/8
2012–Present

1138

37
Shikhar Dhawan & Rohit Sharma
 India
160
30.75
2/4
2013-present

1046

39
William Porterfield & Paul Stirling
 Ireland
109*
29.05
1/6
2009–Present

831

22
Martin Guptill & Brendon McCullum
 New Zealand
127*
41.55
2/4
2009–2015

An asterisk (*) signifies an unbroken partnership (i.e. neither of the batsmen were dismissed before either the end of the allotted overs or they reached the required score).Updated: 8 July 2018[61]

text: Highest partnerships (any wicket)[edit]

text:
Runs

Partnership

Players

Batting team

Opposition

Venue

Date

Scorecard

223

1st wicket
Aaron Finch & D'Arcy Short
 Australia
 Zimbabwe
Harare
3 July 2018
Scorecard

171*

1st wicket
Martin Guptill & Kane Williamson
 New Zealand
 Pakistan
Hamilton
17 January 2016
Scorecard

170

1st wicket
Graeme Smith & Loots Bosman
 South Africa
 England
Centurion
15 November 2009
Scorecard

165

1st wicket
Rohit Sharma & K. L. Rahul
 India
 Sri Lanka
Indore
22 December 2017
Scorecard

166

2nd wicket
Mahela Jayawardene & Kumar Sangakkara
 Sri Lanka
 West Indies
Bridgetown
7 May 2010
Scorecard

An asterisk (*) signifies an unbroken partnership (i.e. neither of the batsmen were dismissed before either the end of the allotted overs or they reached the required score).Updated: 3 July 2018[62]

text: Highest partnerships (by wicket)[edit]

text:
Partnership

Runs

Batsmen

Batting team

Opposition

Venue

Date

Scorecard

1st wicket

223
Aaron Finch & D'Arcy Short
 Australia
 Zimbabwe
Harare
3 July 2018
Scorecard

2nd wicket

166
Mahela Jayawardene & Kumar Sangakkara
 Sri Lanka
 West Indies
Bridgetown
7 May 2010
Scorecard

3rd wicket

152
Alex Hales & Eoin Morgan
 England
 Sri Lanka
Chittagong
27 March 2014
Scorecard

4th wicket

161
David Warner & Glenn Maxwell
 Australia
 South Africa
Johannesburg
6 March 2016
Scorecard

5th wicket

119*
Shoaib Malik & Misbah-ul-Haq
 Pakistan
 Australia
Johannesburg
18 September 2007
Scorecard

6th wicket

101*
Cameron White & Michael Hussey
 Australia
 Sri Lanka
Bridgetown
9 May 2010
Scorecard

7th wicket

91
Paul Collingwood & Michael Yardy
 England
 West Indies
London
28 June 2007
Scorecard

8th wicket

80
Preston Mommsen & Safyaan Sharif
 Scotland
 Netherlands
Edinburgh
11 July 2015
Scorecard

9th wicket

66
Dwayne Bravo & Jerome Taylor
 West Indies
 Pakistan
Dubai (DSC)
23 September 2016
Scorecard

10th wicket

31*
Wahab Riaz & Shoaib Akhtar
 Pakistan
 New Zealand
Auckland
26 December 2010
Scorecard

An asterisk (*) signifies an unbroken partnership (i.e. neither of the batsmen were dismissed before either the end of the allotted overs or they reached the required score).  Updated: 3 July 2018[63]